One of the most requested comparisons has been putting JigsawStack AI Web Scraper against Firecrawl.
Before we jump into the tests we ran, we need to understand what makes a good web scraper or even what’s web scraping in the first place.
Traditionally, developers wrote large, complex codebases on top of heavy infrastructure to load and extract content from websites. They used browser engines like Puppeteer, Playwright, or Selenium, followed by CSS selectors and various techniques to get the data they needed.
Today, we have AI scrapers that do the same thing in seconds, fully managed and automated through simple prompting.
So what makes a good AI Web scraper?
Extracts data with the accuracy of a developer-written script
Automatically handles errors, browser crashes, popups, and other blockers
Auto unblocker for websites protected by Cloudflare, Captcha, and more
Fully managed scaling from 1 to 10,000 requests and back in seconds
Smart actions such as auto-scrolling to load and extract dynamic content
Rotates IPs intelligently to avoid being blocked or flagged as a bot
Gives developers control with support for custom CSS selectors
Summary Comparison
Firecrawl vs JigsawStack AI Scraper
◐ = partial ❌ = inaccurate/fails ✅ = accurate/succeeds
| Feature / Goal | Firecrawl | JigsawStack AI Scraper |
| 💽 Accurate data extractions | Extracted data correctly from 1 out of 6 websites ❌ | Extracted data from all tested sites accurately, following the expected schema ✅ |
| ❤️🩹 Automatic error handling | Frequently threw errors or returned false positives when encountering blocked sites ❌ | Automatically handles errors, retries when needed, and unblocks sites to extract complete data ✅ |
| 🔁 Auto unblocker | Blocked on all protected sites, even with proxy and stealth mode enabled ❌ | Successfully unblocked every site tested, including complex ones like LinkedIn and Reddit ✅ |
| ♾️ Fully managed scale | Limited to 5 concurrent browsers on Hobby plan ($16/month) and 50 on Standard plan ($83/month) ❌ | Supports over 10,000 concurrent browser sessions. Fully managed with no limits and usage-based pricing ✅ |
| 🧠 Smart actions (scrolling, etc.) | Does not automatically scroll to load dynamic content. Only partial page data is scraped ❌ | Automatically scrolls, detects dynamic content, and extracts all relevant values without user input ✅ |
| 🌐 Proxies and IP rotation | Proxy feature failed to prevent blocking. Still flagged by bot detectors even in stealth mode ❌ | Rarely needs proxies. When needed, it uses a built-in rotating proxy system that bypasses even Cloudflare bot checks. ✅ |
| 🧑💻 Developer control | No support for advanced configuration such as custom CSS selectors, browser dimensions, or headers ❌ | Offers full developer control, including custom CSS selectors, browser size, custom cookies, proxy support, and Puppeteer-level configuration options ✅ |
Full Comparisons
Something simple
Site: https://news.ycombinator.com
Prompt: ["post_titles", "post_points", "post_username"]
Firecrawl
{
"success": true,
"metadata": {
"viewport": "width=device-width, initial-scale=1.0",
"favicon": "https://news.ycombinator.com/y18.svg",
"title": "Hacker News",
"referrer": "origin",
"language": "en",
"scrapeId": "686271b5-f619-417b-800a-f57b95236a4f",
"sourceURL": "https://news.ycombinator.com/",
"url": "https://news.ycombinator.com/",
"statusCode": 200,
"proxyUsed": "basic"
},
"json": {
"post_titles": [
"Reinvent the Wheel",
"Tachy0n: The Last 0day Jailbreak",
"I used o3 to find a remote zeroday in the Linux SMB implementation",
"Why old games never die, but new ones do",
"Using the Apple ][+ with the RetroTink-5X",
"Lone coder cracks 50-year puzzle to find Boggle's top-scoring board",
"Good Writing",
"The Logistics of Road War in the Wasteland",
"Show HN: Rotary Phone Dial Linux Kernel Driver",
"Please Fund More Science (2020)",
"The Xenon Death Flash: How a Camera Nearly Killed the Raspberry Pi 2",
"Hong Kong's Famous Bamboo Scaffolding Hangs on (For Now)",
"Exposed Industrial Control Systems and Honeypots in the Wild [pdf]",
"Show HN: F2 – Cross-Platform CLI Batch Renaming Tool",
"Postgres IDE in VS Code",
"Scientific conferences are leaving the US amid border fears",
"Trellis (YC W24) Is Hiring founding SDR to help automate healthcare paperwork",
"An Almost Pointless Exercise in GPU Optimization",
"Peer Programming with LLMs, for Senior+ Engineers",
"Live facial recognition cameras may become 'commonplace' as police use soars",
"Is Astrophotography Without Tracking Possible?",
"The Last Nomads",
"Show HN: 1 min workouts for people who sit all day",
"The legacy of the iconic Nakagin capsule tower",
"Find Your People",
"AI, Heidegger, and Evangelion",
"Root for your friends",
"Why Algebraic Effects?",
"voyage-3.5 and voyage-3.5-lite: improved quality for a new retrieval frontier",
"Use ramoops for logging under Linux (2021)"
],
"post_points": [
"112",
"104",
"264",
"26",
"9",
"69",
"118",
"22",
"262",
"51",
"159",
"134",
"26",
"88",
"969",
"18",
"0",
"5",
"58",
"101",
"17",
"5",
"57",
"81",
"702",
"103",
"364",
"267",
"20",
"12"
],
"post_username": [
"zdw",
"todsacerdoti",
"zielmicha",
"airhangerf15",
"zdw",
"DavidSJ",
"oli5679",
"ecliptik",
"sephalon",
"ssuds",
"DamonHD",
"perihelions",
"gnabgib",
"ayoisaiah",
"Dowwie",
"mdhb",
"null",
"atomlib",
"pmbanugo",
"c-oreills",
"astroimagery",
"Thevet",
"melvinzammit",
"pseudolus",
"jl",
"jger15",
"rez0123",
"jiggawatts",
"fzliu",
"zdw"
]
}
}
JigsawStack
{
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"page_position_length": 1,
"context": {
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"Reinvent the Wheel",
"Tachy0n: The Last 0day Jailbreak",
"I used o3 to find a remote zeroday in the Linux SMB implementation",
"Why old games never die, but new ones do",
"Using the Apple ][+ with the RetroTink-5X",
"Lone coder cracks 50-year puzzle to find Boggle's top-scoring board",
"Good Writing",
"The Logistics of Road War in the Wasteland",
"Show HN: Rotary Phone Dial Linux Kernel Driver",
"Please Fund More Science (2020)",
"The Xenon Death Flash: How a Camera Nearly Killed the Raspberry Pi 2",
"Hong Kong's Famous Bamboo Scaffolding Hangs on (For Now)",
"Exposed Industrial Control Systems and Honeypots in the Wild [pdf]",
"Show HN: F2 – Cross-Platform CLI Batch Renaming Tool",
"Postgres IDE in VS Code",
"Scientific conferences are leaving the US amid border fears",
"Trellis (YC W24) Is Hiring founding SDR to help automate healthcare paperwork",
"An Almost Pointless Exercise in GPU Optimization",
"Peer Programming with LLMs, for Senior+ Engineers",
"Live facial recognition cameras may become 'commonplace' as police use soars",
"Is Astrophotography Without Tracking Possible?",
"The Last Nomads",
"Show HN: 1 min workouts for people who sit all day",
"The legacy of the iconic Nakagin capsule tower",
"Find Your People",
"AI, Heidegger, and Evangelion",
"Root for your friends",
"Why Algebraic Effects?",
"voyage-3.5 and voyage-3.5-lite: improved quality for a new retrieval frontier",
"Use ramoops for logging under Linux (2021)",
"endler.dev",
"siguza.net",
"heelan.io",
"pleromanonx86.wordpress.com",
"nicole.express",
"ft.com",
"paulgraham.com",
"acoup.blog",
"gitlab.com/sephalon",
"samaltman.com",
"magnus919.com",
"nytimes.com",
"gsmaragd.github.io",
"github.com/ayoisaiah",
"microsoft.com",
"nature.com",
"ycombinator.com",
"speechmatics.com",
"pmbanugo.me",
"theguardian.com",
"astroimagery.com",
"thedial.world",
"shortreps.com",
"designboom.com",
"foundersatwork.posthaven.com",
"fakepixels.substack.com",
"josephthacker.com",
"antelang.org",
"voyageai.com",
"embear.ch"
],
"post_points": [
"112 points",
"104 points",
"264 points",
"26 points",
"9 points",
"69 points",
"118 points",
"22 points",
"262 points",
"51 points",
"159 points",
"134 points",
"88 points",
"969 points",
"18 points",
"5 points",
"58 points",
"101 points",
"17 points",
"57 points",
"81 points",
"702 points",
"103 points",
"364 points",
"267 points",
"20 points",
"12 points"
],
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"todsacerdoti",
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"DamonHD",
"perihelions",
"gnabgib",
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"mdhb",
"atomlib",
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"astroimagery",
"Thevet",
"melvinzammit",
"pseudolus",
"jl",
"jger15",
"rez0123",
"jiggawatts",
"fzliu"
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"selectors": {
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"post_points": ["span.score", ".subtext .score", "td.subtext span.score", "span.subline > span.score", ".score"],
"post_username": ["a.hnuser", ".subtext .hnuser", "span.subline > a.hnuser", "td.subtext a.hnuser", ".hnuser"]
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"href": "https://nicole.express/2025/apple-ii-more-like-apple-5x.html",
"text": "Using the Apple ][+ with the RetroTink-5X",
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{
"href": "https://news.ycombinator.com/from?site=nicole.express",
"text": "nicole.express",
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"text": "14 comments",
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"text": "Good Writing",
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"text": "7 hours ago",
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{
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"text": "hide",
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{
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"text": "144 comments",
"type": "a"
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{
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"text": "",
"type": "a"
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{
"href": "https://acoup.blog/2025/05/23/collections-the-logistics-of-road-war-in-the-wasteland/",
"text": "The Logistics of Road War in the Wasteland",
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},
{
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"text": "acoup.blog",
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"text": "ecliptik",
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{
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"text": "2 hours ago",
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{
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"text": "11 comments",
"type": "a"
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{
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"text": "Show HN: Rotary Phone Dial Linux Kernel Driver",
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},
{
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"text": "35 comments",
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{
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"text": "DamonHD",
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"text": "10 hours ago",
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},
{
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"text": "hide",
"type": "a"
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{
"href": "https://news.ycombinator.com/item?id=44080533",
"text": "59 comments",
"type": "a"
},
{
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"href": "https://www.nytimes.com/2025/05/24/world/asia/hongkong-bamboo-scaffolding.html",
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"text": "10 hours ago",
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{
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{
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"text": "34 comments",
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]
},
{
"html": "rez0123",
"text": "rez0123",
"attributes": [
{
"name": "href",
"value": "user?id=rez0123"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jiggawatts",
"text": "jiggawatts",
"attributes": [
{
"name": "href",
"value": "user?id=jiggawatts"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "fzliu",
"text": "fzliu",
"attributes": [
{
"name": "href",
"value": "user?id=fzliu"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
}
],
"key": "post_username"
},
{
"selector": "span.subline > a.hnuser",
"results": [
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "todsacerdoti",
"text": "todsacerdoti",
"attributes": [
{
"name": "href",
"value": "user?id=todsacerdoti"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zielmicha",
"text": "zielmicha",
"attributes": [
{
"name": "href",
"value": "user?id=zielmicha"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "airhangerf15",
"text": "airhangerf15",
"attributes": [
{
"name": "href",
"value": "user?id=airhangerf15"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "DavidSJ",
"text": "DavidSJ",
"attributes": [
{
"name": "href",
"value": "user?id=DavidSJ"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "oli5679",
"text": "oli5679",
"attributes": [
{
"name": "href",
"value": "user?id=oli5679"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ecliptik",
"text": "ecliptik",
"attributes": [
{
"name": "href",
"value": "user?id=ecliptik"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "sephalon",
"text": "sephalon",
"attributes": [
{
"name": "href",
"value": "user?id=sephalon"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ssuds",
"text": "ssuds",
"attributes": [
{
"name": "href",
"value": "user?id=ssuds"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "DamonHD",
"text": "DamonHD",
"attributes": [
{
"name": "href",
"value": "user?id=DamonHD"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "perihelions",
"text": "perihelions",
"attributes": [
{
"name": "href",
"value": "user?id=perihelions"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "gnabgib",
"text": "gnabgib",
"attributes": [
{
"name": "href",
"value": "user?id=gnabgib"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ayoisaiah",
"text": "ayoisaiah",
"attributes": [
{
"name": "href",
"value": "user?id=ayoisaiah"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "Dowwie",
"text": "Dowwie",
"attributes": [
{
"name": "href",
"value": "user?id=Dowwie"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "mdhb",
"text": "mdhb",
"attributes": [
{
"name": "href",
"value": "user?id=mdhb"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "atomlib",
"text": "atomlib",
"attributes": [
{
"name": "href",
"value": "user?id=atomlib"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "pmbanugo",
"text": "pmbanugo",
"attributes": [
{
"name": "href",
"value": "user?id=pmbanugo"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "c-oreills",
"text": "c-oreills",
"attributes": [
{
"name": "href",
"value": "user?id=c-oreills"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "astroimagery",
"text": "astroimagery",
"attributes": [
{
"name": "href",
"value": "user?id=astroimagery"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "Thevet",
"text": "Thevet",
"attributes": [
{
"name": "href",
"value": "user?id=Thevet"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "melvinzammit",
"text": "melvinzammit",
"attributes": [
{
"name": "href",
"value": "user?id=melvinzammit"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "pseudolus",
"text": "pseudolus",
"attributes": [
{
"name": "href",
"value": "user?id=pseudolus"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jl",
"text": "jl",
"attributes": [
{
"name": "href",
"value": "user?id=jl"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jger15",
"text": "jger15",
"attributes": [
{
"name": "href",
"value": "user?id=jger15"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "rez0123",
"text": "rez0123",
"attributes": [
{
"name": "href",
"value": "user?id=rez0123"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jiggawatts",
"text": "jiggawatts",
"attributes": [
{
"name": "href",
"value": "user?id=jiggawatts"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "fzliu",
"text": "fzliu",
"attributes": [
{
"name": "href",
"value": "user?id=fzliu"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
}
],
"key": "post_username"
},
{
"selector": "td.subtext a.hnuser",
"results": [
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "todsacerdoti",
"text": "todsacerdoti",
"attributes": [
{
"name": "href",
"value": "user?id=todsacerdoti"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zielmicha",
"text": "zielmicha",
"attributes": [
{
"name": "href",
"value": "user?id=zielmicha"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "airhangerf15",
"text": "airhangerf15",
"attributes": [
{
"name": "href",
"value": "user?id=airhangerf15"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "DavidSJ",
"text": "DavidSJ",
"attributes": [
{
"name": "href",
"value": "user?id=DavidSJ"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "oli5679",
"text": "oli5679",
"attributes": [
{
"name": "href",
"value": "user?id=oli5679"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ecliptik",
"text": "ecliptik",
"attributes": [
{
"name": "href",
"value": "user?id=ecliptik"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "sephalon",
"text": "sephalon",
"attributes": [
{
"name": "href",
"value": "user?id=sephalon"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ssuds",
"text": "ssuds",
"attributes": [
{
"name": "href",
"value": "user?id=ssuds"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "DamonHD",
"text": "DamonHD",
"attributes": [
{
"name": "href",
"value": "user?id=DamonHD"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "perihelions",
"text": "perihelions",
"attributes": [
{
"name": "href",
"value": "user?id=perihelions"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "gnabgib",
"text": "gnabgib",
"attributes": [
{
"name": "href",
"value": "user?id=gnabgib"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ayoisaiah",
"text": "ayoisaiah",
"attributes": [
{
"name": "href",
"value": "user?id=ayoisaiah"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "Dowwie",
"text": "Dowwie",
"attributes": [
{
"name": "href",
"value": "user?id=Dowwie"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "mdhb",
"text": "mdhb",
"attributes": [
{
"name": "href",
"value": "user?id=mdhb"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "atomlib",
"text": "atomlib",
"attributes": [
{
"name": "href",
"value": "user?id=atomlib"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "pmbanugo",
"text": "pmbanugo",
"attributes": [
{
"name": "href",
"value": "user?id=pmbanugo"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "c-oreills",
"text": "c-oreills",
"attributes": [
{
"name": "href",
"value": "user?id=c-oreills"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "astroimagery",
"text": "astroimagery",
"attributes": [
{
"name": "href",
"value": "user?id=astroimagery"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "Thevet",
"text": "Thevet",
"attributes": [
{
"name": "href",
"value": "user?id=Thevet"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "melvinzammit",
"text": "melvinzammit",
"attributes": [
{
"name": "href",
"value": "user?id=melvinzammit"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "pseudolus",
"text": "pseudolus",
"attributes": [
{
"name": "href",
"value": "user?id=pseudolus"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jl",
"text": "jl",
"attributes": [
{
"name": "href",
"value": "user?id=jl"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jger15",
"text": "jger15",
"attributes": [
{
"name": "href",
"value": "user?id=jger15"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "rez0123",
"text": "rez0123",
"attributes": [
{
"name": "href",
"value": "user?id=rez0123"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jiggawatts",
"text": "jiggawatts",
"attributes": [
{
"name": "href",
"value": "user?id=jiggawatts"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "fzliu",
"text": "fzliu",
"attributes": [
{
"name": "href",
"value": "user?id=fzliu"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
}
],
"key": "post_username"
},
{
"selector": ".hnuser",
"results": [
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "todsacerdoti",
"text": "todsacerdoti",
"attributes": [
{
"name": "href",
"value": "user?id=todsacerdoti"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zielmicha",
"text": "zielmicha",
"attributes": [
{
"name": "href",
"value": "user?id=zielmicha"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "airhangerf15",
"text": "airhangerf15",
"attributes": [
{
"name": "href",
"value": "user?id=airhangerf15"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "DavidSJ",
"text": "DavidSJ",
"attributes": [
{
"name": "href",
"value": "user?id=DavidSJ"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "oli5679",
"text": "oli5679",
"attributes": [
{
"name": "href",
"value": "user?id=oli5679"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ecliptik",
"text": "ecliptik",
"attributes": [
{
"name": "href",
"value": "user?id=ecliptik"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "sephalon",
"text": "sephalon",
"attributes": [
{
"name": "href",
"value": "user?id=sephalon"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ssuds",
"text": "ssuds",
"attributes": [
{
"name": "href",
"value": "user?id=ssuds"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "DamonHD",
"text": "DamonHD",
"attributes": [
{
"name": "href",
"value": "user?id=DamonHD"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "perihelions",
"text": "perihelions",
"attributes": [
{
"name": "href",
"value": "user?id=perihelions"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "gnabgib",
"text": "gnabgib",
"attributes": [
{
"name": "href",
"value": "user?id=gnabgib"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "ayoisaiah",
"text": "ayoisaiah",
"attributes": [
{
"name": "href",
"value": "user?id=ayoisaiah"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "Dowwie",
"text": "Dowwie",
"attributes": [
{
"name": "href",
"value": "user?id=Dowwie"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "mdhb",
"text": "mdhb",
"attributes": [
{
"name": "href",
"value": "user?id=mdhb"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "atomlib",
"text": "atomlib",
"attributes": [
{
"name": "href",
"value": "user?id=atomlib"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "pmbanugo",
"text": "pmbanugo",
"attributes": [
{
"name": "href",
"value": "user?id=pmbanugo"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "c-oreills",
"text": "c-oreills",
"attributes": [
{
"name": "href",
"value": "user?id=c-oreills"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "astroimagery",
"text": "astroimagery",
"attributes": [
{
"name": "href",
"value": "user?id=astroimagery"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "Thevet",
"text": "Thevet",
"attributes": [
{
"name": "href",
"value": "user?id=Thevet"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "melvinzammit",
"text": "melvinzammit",
"attributes": [
{
"name": "href",
"value": "user?id=melvinzammit"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "pseudolus",
"text": "pseudolus",
"attributes": [
{
"name": "href",
"value": "user?id=pseudolus"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jl",
"text": "jl",
"attributes": [
{
"name": "href",
"value": "user?id=jl"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jger15",
"text": "jger15",
"attributes": [
{
"name": "href",
"value": "user?id=jger15"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "rez0123",
"text": "rez0123",
"attributes": [
{
"name": "href",
"value": "user?id=rez0123"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "jiggawatts",
"text": "jiggawatts",
"attributes": [
{
"name": "href",
"value": "user?id=jiggawatts"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "fzliu",
"text": "fzliu",
"attributes": [
{
"name": "href",
"value": "user?id=fzliu"
},
{
"name": "class",
"value": "hnuser"
}
]
},
{
"html": "zdw",
"text": "zdw",
"attributes": [
{
"name": "href",
"value": "user?id=zdw"
},
{
"name": "class",
"value": "hnuser"
}
]
}
],
"key": "post_username"
}
],
"success": true,
"advance_config": {
"console": [],
"network": [],
"cookies": []
},
"_usage": {
"input_tokens": 27,
"output_tokens": 25236,
"inference_time_tokens": 7065,
"total_tokens": 32328
}
}
Both Firecrawl and JigsawStack did a solid job extracting values accurately. However, JigsawStack went a step further by automatically including additional information, such as links that can be easily looped over and scraped, making web crawling straightforward.
JigsawStack also returns the CSS selectors associated with the extracted content, so you can run your own scripts without needing to figure out how the website is structured.
E-Commerce
Site: https://www.amazon.com/GIGABYTE-GeForce-WINDFORCE-Graphics-GV-N506TWF2OC-16GD/dp/B0F5BBGCSZ
Prompt: ["product_price", "product_description", "product_brand"]
Firecrawl
{
"success": true,
"metadata": {
"title": "Amazon.com",
"viewport": "width=device-width",
"language": "en-us",
"scrapeId": "2f46ac4a-af50-4b58-8b8a-bb66b8cefd3f",
"sourceURL": "https://www.amazon.com/GIGABYTE-GeForce-WINDFORCE-Graphics-GV-N506TWF2OC-16GD/dp/B0F5BBGCSZ",
"url": "https://www.amazon.com/GIGABYTE-GeForce-WINDFORCE-Graphics-GV-N506TWF2OC-16GD/dp/B0F5BBGCSZ",
"statusCode": 200,
"proxyUsed": "stealth"
},
"json": {
"product_price": [],
"product_description": [],
"product_brand": []
}
}
JigsawStack
{
"page_position": 1,
"page_position_length": 6,
"context": {
"product_price": [
"$489.99",
"$60.99",
"$78.99",
"$16.99/month",
"()",
"$4,899.99$4,899.99",
"$2,699.99$2,699.99",
"$199.89$199.89",
"$1,049.99$1,049.99",
"$21.99$21.99",
"$1,199.00$1,199.00",
"$2,259.99$2,259.99",
"$1,599.99$1,599.99",
"$54.99$54.99",
"$99.99$99.99",
"$79.99$79.99",
"$94.99$94.99",
"$159.99$159.99",
"$100.99$100.99"
],
"product_description": [
"Coverage for accidental damage including drops, spills, and broken parts, as well as breakdowns (plans vary)",
"24/7 support when you need it.",
"Quick, easy, and frustration-free claims.",
"No Additional Cost: You pay nothing for repairs – parts, labor, and shipping included.",
"Coverage: Plan starts on the date of purchase. Malfunctions covered after the manufacturer's warranty. Power surges covered from day one. Real experts are available 24/7 to help with set-up, connectivity issues, troubleshooting and much more.",
"Easy Claims Process: File a claim anytime online or by phone. Most claims approved within minutes. If we can’t repair it, we’ll send you an Amazon e-gift card for the purchase price of your covered product or replace it.",
"Product Eligibility: Plan must be purchased with a product or within 30 days of the product purchase. Pre-existing conditions are not covered.",
"Terms & Details: More information about this protection plan is available within the “Product guides and documents” section. Simply click “User Guide” for more info. Terms & Conditions will be available in Your Orders on Amazon. Asurion will also email your plan confirmation with Terms & Conditions to the address associated with your Amazon account within 24 hours of purchase.",
"EXTENSIVE COVERAGE: Protection for all your eligible products purchased from Amazon. (Note: Products used commercially or for a business are excluded)",
"EXCEPTIONAL PROTECTION: Including malfunctions and failures, plus drops or spills for eligible portable items.",
"PAST & FUTURE PURCHASES COVERED: You're protected on eligible items purchased within the last year and new purchases going forward, including this purchase — starting 30 days after enrollment.",
"QUICK & EASY CLAIMS: File a claim in minutes at Asurion.com/amazon. We'll repair, replace, or reimburse you up to the purchase price (excluding tax).",
"NO HIDDEN FEES. You’re covered for up to $5,000 in total claims per 12-month period. Cancel anytime – your plan renews monthly until canceled. (Coupons applied at checkout do not renew monthly.)",
"3-Year Protection Plan for $60.99",
"4-Year Protection Plan for $78.99",
"Complete Protect: One plan covers all eligible past and future purchases (Renews Monthly Until Cancelled) for $16.99/month",
"$60.99",
"$78.99",
"$16.99/month"
],
"product_brand": [
"from Asurion, LLC",
"Ships from and sold by Amazon.com.",
"Sold by ARCTIC Inc and ships from Amazon Fulfillment.",
"Max Screen Resolution",
"Memory Speed",
"Graphics Coprocessor",
"Chipset Brand",
"Graphics Card Ram Size",
"Brand",
"Item Weight",
"Product Dimensions",
"Item Dimensions LxWxH",
"Manufacturer",
"ASIN",
"Country of Origin",
"Date First Available",
"Best Sellers Rank",
"Graphics Cards",
"Electronics",
"Computers & Accessories",
"Computer Components"
]
},
"selectors": {
"product_price": [
"#corePrice_feature_div .a-price .a-offscreen",
"#tp_price_block_total_price_ww .a-offscreen",
"#attach-warranty-card-price",
".a-color-price",
"#tp-tool-tip-subtotal-price-value .a-offscreen"
],
"product_description": [
"#attach-warranty-pane .attach-warranty-bullet-point-container .a-size-base-plus",
"#attach-warranty-pane-ld .attach-warranty-bullet-point-container .a-size-base-plus",
".mbb__m ul.a-unordered-list .a-list-item span",
"#mbb_feature_div .abbListItem .a-label",
"#mbb_feature_div .abbListItem .a-color-price"
],
"product_brand": [
".a-size-base.a-color-secondary",
"#wayfinding-breadcrumbs_feature_div ul.a-unordered-list li:last-child a",
"#wayfinding-breadcrumbs_feature_div ul.a-unordered-list li:nth-child(1) a",
"#wayfinding-breadcrumbs_feature_div ul.a-unordered-list li:nth-child(3) a",
"#wayfinding-breadcrumbs_feature_div ul.a-unordered-list li:nth-child(5) a"
]
},
"_usage": {
"input_tokens": 45,
"output_tokens": 38501,
"inference_time_tokens": 40264,
"total_tokens": 78810
}
}
Firecrawl was unable to extract the data, even with a proxy enabled. JigsawStack retrieved all content successfully without requiring any proxy.
Nutritiously hard to scrape site
Site: https://www.linkedin.com/in/yoeven/
Prompt: ["profile_person_name", "work_at_company_name", "job_title"]
Firecrawl
{
"err": "Failed to scrape URL. Status code: 403. Error: This website is no longer supported, please reach out to help@firecrawl.com for more info on how to activate it on your account."
}
JigsawStack
{
"page_position": 1,
"page_position_length": 2,
"context": {
"profile_person_name": [
"Yoeven D Khemlani",
"Sign in to view Yoeven’s full profile",
"View mutual connections with Yoeven",
"Welcome back",
"The signal-based outbound industry has a problem: GTM engineers making simple processes look impossible so you'll hire them.\nI'm here to tell you:…",
"Having OCR troubles? JigsawStack’s vOCR delivers structured, fast, and reliable output for any doc type. It’s built for devs, and it keeps getting…",
"Vibe coders don't know what they're paying for! 💸 Cursor auto installed JigsawStack sdk to build his product He got charged over $200 by cursor…",
"We benchmarked Google's Gemini OCR against JigsawStack's vOCR across handwritten notes, multilingual signs, receipts, and structured PDFs. Both can…",
"🚀 Exciting Highlights from the 2025 CDOIQ-APAC Symposium! 🚀 It was an honour to be a guest speaker at the 2025 CDOIQ-APAC Symposium titled: From…",
"Good conversations at #Saastr A number of our Antler founders and a few global colleagues attending as well. Who else is there today? Jason M.…",
"Had such an a amazing experience at the AI x Infra dinner hosted by Andreessen Horowitz, Neon and Tigris Data! Met so many amazing people and…",
"Better Auth is a comprehensive authentication framework for TypeScript that helps you roll your own auth from simple auth flows to enterprise-grade…"
],
"work_at_company_name": [
"JigsawStack",
"Imperial College London",
"Portfolio",
"Staytion Singapore",
"Stayr",
"Noah",
"UOB",
"Chiang Mai University",
"Founder at JigsawStack 🧩"
],
"job_title": [
"Founder at JigsawStack 🧩",
"The signal-based outbound industry has a problem: GTM engineers making simple processes look impossible so you'll hire them.\nI'm here to tell you:…",
"Having OCR troubles? JigsawStack’s vOCR delivers structured, fast, and reliable output for any doc type. It’s built for devs, and it keeps getting…",
"Vibe coders don't know what they're paying for! 💸 Cursor auto installed JigsawStack sdk to build his product He got charged over $200 by cursor…",
"We benchmarked Google's Gemini OCR against JigsawStack's vOCR across handwritten notes, multilingual signs, receipts, and structured PDFs. Both can…",
"🚀 Exciting Highlights from the 2025 CDOIQ-APAC Symposium! 🚀 It was an honour to be a guest speaker at the 2025 CDOIQ-APAC Symposium titled: From…",
"Good conversations at #Saastr A number of our Antler founders and a few global colleagues attending as well. Who else is there today? Jason M.…",
"Had such an a amazing experience at the AI x Infra dinner hosted by Andreessen Horowitz, Neon and Tigris Data! Met so many amazing people and…",
"Better Auth is a comprehensive authentication framework for TypeScript that helps you roll your own auth from simple auth flows to enterprise-grade…"
]
},
"selectors": {
"profile_person_name": [
"h1.top-card-layout__title",
"h3.base-main-card__title + h4.base-main-card__subtitle a.hidden-nested-link",
"h2.contextual-sign-in-modal__context-screen-title",
"h2.sign-in-modal__header",
"h3.base-main-card__title"
],
"work_at_company_name": [
"a.flex.link .top-card-link__description",
"h4.text-color-text.text-md a .experience-item__subtitle",
"h2.top-card-layout__headline",
"h2.core-section-container__title.section-title + div.core-section-container__content ul.experience__list li:first-child h4 a .experience-item__subtitle",
"h4.text-color-text.text-md a"
],
"job_title": [
"h2.top-card-layout__headline",
"h3.experience-item__title",
"h3.[&>*\\:mb-0].text-[18px]",
"h3.base-main-card__title",
"h3.experience-item__title span"
]
}
}
Firecrawl doesn’t allow scraping of websites like LinkedIn by default and throws an error while JigsawStack extracts any public information you find on the site easily.
Cloudflare Unblocker
Site: https://platform.openai.com/docs/guides/text
Prompt: ["titles", "markdown_full_site", "coding_snippets"]
OpenAI docs are protected and blocked by Cloudflare.
Firecrawl
{
"success": true,
"metadata": {
"og:type": "website",
"og:title": "OpenAI Platform",
"ogUrl": "https://platform.openai.com",
"title": "OpenAI Platform",
"og:image": "https://cdn.openai.com/API/images/platform-opengraph.png",
"twitter:title": "OpenAI Platform",
"theme-color": "#000000",
"twitter:description": "Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.",
"twitter:image": "https://cdn.openai.com/API/images/platform-opengraph.png",
"ogImage": "https://cdn.openai.com/API/images/platform-opengraph.png",
"og:description": "Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.",
"og:url": "https://platform.openai.com",
"twitter:card": "summary_large_image",
"description": "Explore resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's developer platform.",
"favicon": "https://platform.openai.com/favicon-platform.png",
"twitter:domain": "platform.openai.com",
"viewport": "width=device-width, initial-scale=1",
"twitter:url": "https://platform.openai.com",
"ogTitle": "OpenAI Platform",
"language": "en-US",
"ogDescription": "Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.",
"scrapeId": "563100fa-adc6-4c5b-8f40-3e1c92487505",
"sourceURL": "https://platform.openai.com/docs/guides/text",
"url": "https://platform.openai.com/docs/guides/text",
"statusCode": 200,
"proxyUsed": "stealth"
},
"json": {
"titles": [],
"markdown_full_site": [],
"coding_snippets": []
}
}
JigsawStack
{
"page_position": 1,
"page_position_length": 2,
"context": {
"titles": [
"Text generation and prompting",
"Choosing a model",
"Prompt engineering",
"Message roles and instruction following",
"Message formatting with Markdown and XML",
"Few-shot learning",
"Include relevant context information",
"Prompting GPT-4.1 models",
"Prompting reasoning models",
"Next steps",
"Learn how to prompt a model to generate text.",
"Get started",
"Core Concepts",
"Tools",
"Agents",
"Realtime API",
"Model optimization",
"Specialized models",
"OpenAI Platform",
"Codex",
"Best practices",
"Assistants API",
"Resources"
],
"markdown_full_site": [
"Text generation and prompting\nLearn how to prompt a model to generate text.\nCopy page\nWith the OpenAI API, you can use a large language model to generate text from a prompt, as you might using ChatGPT. Models can generate almost any kind of text response—like code, mathematical equations, structured JSON data, or human-like prose.\nHere's a simple example using the Responses API.\nGenerate text from a simple prompt\njavascript\n123456789import OpenAI from\"openai\";const client = new OpenAI();const response = await client.responses.create({model: \"gpt-4.1\",input: \"Write a one-sentence bedtime story about a unicorn.\"});console.log(response.output_text);\n123456789from openai import OpenAIclient = OpenAI()response = client.responses.create( model=\"gpt-4.1\",input=\"Write a one-sentence bedtime story about a unicorn.\")print(response.output_text)\n1234567curl \"https://api.openai.com/v1/responses\" \\ -H \"Content-Type: application/json\" \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -d '{ \"model\": \"gpt-4.1\", \"input\": \"Write a one-sentence bedtime story about a unicorn.\" }'\nAn array of content generated by the model is in the output property of the response. In this simple example, we have just one output which looks like this:\n1234567891011121314[ {\"id\": \"msg_67b73f697ba4819183a15cc17d011509\",\"type\": \"message\",\"role\": \"assistant\",\"content\": [ {\"type\": \"output_text\",\"text\": \"Under the soft glow of the moon, Luna the unicorn danced through fields of twinkling stardust, leaving trails of dreams for every child asleep.\",\"annotations\": [] } ] }]\nThe output array often has more than one item in it! It can contain tool calls, data about reasoning tokens generated by reasoning models, and other items. It is not safe to assume that the model's text output is present at output[0].content[0].text.\nSome of our official SDKs include an output_text property on model responses for convenience, which aggregates all text outputs from the model into a single string. This may be useful as a shortcut to access text output from the model.\nIn addition to plain text, you can also have the model return structured data in JSON format - this feature is called Structured Outputs.\nChoosing a model\nA key choice to make when generating content through the API is which model you want to use - the model parameter of the code samples above. You can find a full listing of available models here. Here are a few factors to consider when choosing a model for text generation.\nReasoning models generate an internal chain of thought to analyze the input prompt, and excel at understanding complex tasks and multi-step planning. They are also generally slower and more expensive to use than GPT models.\nGPT models are fast, cost-efficient, and highly intelligent, but benefit from more explicit instructions around how to accomplish tasks.\nLarge and small (mini or nano) models offer trade-offs for speed, cost, and intelligence. Large models are more effective at understanding prompts and solving problems across domains, while small models are generally faster and cheaper to use.\nWhen in doubt, gpt-4.1 offers a solid combination of intelligence, speed, and cost effectiveness.\nPrompt engineering\nPrompt engineering is the process of writing effective instructions for a model, such that it consistently generates content that meets your requirements.\nBecause the content generated from a model is non-deterministic, it is a combination of art and science to build a prompt that will generate content in the format you want. However, there are a number of techniques and best practices you can apply to consistently get good results from a model.\nSome prompt engineering techniques will work with every model, like using message roles. But different model types (like reasoning versus GPT models) might need to be prompted differently to produce the best results. Even different snapshots of models within the same family could produce different results. So as you are building more complex applications, we strongly recommend that you:\nPin your production applications to specific model snapshots (like gpt-4.1-2025-04-14 for example) to ensure consistent behavior.\nBuild evals that will measure the behavior of your prompts, so that you can monitor the performance of your prompts as you iterate on them, or when you change and upgrade model versions.\nNow, let's examine some tools and techniques available to you to construct prompts.\nMessage roles and instruction following\nYou can provide instructions to the model with differing levels of authority using the instructions API parameter or message roles.\nThe instructions parameter gives the model high-level instructions on how it should behave while generating a response, including tone, goals, and examples of correct responses. Any instructions provided this way will take priority over a prompt in the input parameter.\nGenerate text with instructions\njavascript\n12345678910import OpenAI from\"openai\";const client = new OpenAI();const response = await client.responses.create({model: \"gpt-4.1\",instructions: \"Talk like a pirate.\",input: \"Are semicolons optional in JavaScript?\",});console.log(response.output_text);\n12345678910from openai import OpenAIclient = OpenAI()response = client.responses.create( model=\"gpt-4.1\", instructions=\"Talk like a pirate.\",input=\"Are semicolons optional in JavaScript?\",)print(response.output_text)\n12345678curl \"https://api.openai.com/v1/responses\" \\ -H \"Content-Type: application/json\" \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -d '{ \"model\": \"gpt-4.1\", \"instructions\": \"Talk like a pirate.\", \"input\": \"Are semicolons optional in JavaScript?\" }'\nThe example above is roughly equivalent to using the following input messages in the input array:\nGenerate text with messages using different roles\njavascript\n123456789101112131415161718import OpenAI from\"openai\";const client = new OpenAI();const response = await client.responses.create({model: \"gpt-4.1\",input: [ {role: \"developer\",content: \"Talk like a pirate.\" }, {role: \"user\",content: \"Are semicolons optional in JavaScript?\", }, ],});console.log(response.output_text);\n123456789101112131415161718from openai import OpenAIclient = OpenAI()response = client.responses.create( model=\"gpt-4.1\",input=[ {\"role\": \"developer\",\"content\": \"Talk like a pirate.\" }, {\"role\": \"user\",\"content\": \"Are semicolons optional in JavaScript?\" } ])print(response.output_text)\n12345678910111213141516curl \"https://api.openai.com/v1/responses\" \\ -H \"Content-Type: application/json\" \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -d '{ \"model\": \"gpt-4.1\", \"input\": [ { \"role\": \"developer\", \"content\": \"Talk like a pirate.\" }, { \"role\": \"user\", \"content\": \"Are semicolons optional in JavaScript?\" } ] }'\nNote that the instructions parameter only applies to the current response generation request. If you are managing conversation state with the previous_response_id parameter, the instructions used on previous turns will not be present in the context.\nThe OpenAI model spec describes how our models give different levels of priority to messages with different roles.\ndeveloperuserassistant\ndeveloper messages are instructions provided by the application developer, prioritized ahead of user messages.\nuser messages are instructions provided by an end user, prioritized behind developer messages.\nMessages generated by the model have the assistant role.\nA multi-turn conversation may consist of several messages of these types, along with other content types provided by both you and the model. Learn more about managing conversation state here.\nYou could think about developer and user messages like a function and its arguments in a programming language.\ndeveloper messages provide the system's rules and business logic, like a function definition.\nuser messages provide inputs and configuration to which the developer message instructions are applied, like arguments to a function.\nMessage formatting with Markdown and XML\nWhen writing developer and user messages, you can help the model understand logical boundaries of your prompt and context data using a combination of Markdown formatting and XML tags.\nMarkdown headers and lists can be helpful to mark distinct sections of a prompt, and to communicate hierarchy to the model. They can also potentially make your prompts more readable during development. XML tags can help delineate where one piece of content (like a supporting document used for reference) begins and ends. XML attributes can also be used to define metadata about content in the prompt that can be referenced by your instructions.\nIn general, a developer message will contain the following sections, usually in this order (though the exact optimal content and order may vary by which model you are using):\nIdentity: Describe the purpose, communication style, and high-level goals of the assistant.\nInstructions: Provide guidance to the model on how to generate the response you want. What rules should it follow? What should the model do, and what should the model never do? This section could contain many subsections as relevant for your use case, like how the model should call custom functions.\nExamples: Provide examples of possible inputs, along with the desired output from the model.\nContext: Give the model any additional information it might need to generate a response, like private/proprietary data outside its training data, or any other data you know will be particularly relevant. This content is usually best positioned near the end of your prompt, as you may include different context for different generation requests.\nBelow is an example of using Markdown and XML tags to construct a developer message with distinct sections and supporting examples.\nExample promptExample promptAPI requestAPI request\nExample prompt\nA developer message for code generation\n123456789101112131415161718192021222324# IdentityYou are coding assistant that helps enforce the use of snake case variables in JavaScript code, and writing code that will run in Internet Explorer version 6.# Instructions* When defining variables, use snake case names (e.g. my_variable) instead of camel case names (e.g. myVariable).* To support old browsers, declare variables using the older \"var\" keyword.* Do not give responses with Markdown formatting, just return the code as requested.# Examples<user_query>How do I declare a string variable for a first name?</user_query><assistant_response>var first_name = \"Anna\";</assistant_response>\nAPI request\nSend a prompt to generate code through the API\njavascript\n12345678910111213import fs from\"fs/promises\";import OpenAI from\"openai\";const client = new OpenAI();const instructions = await fs.readFile(\"prompt.txt\", \"utf-8\");const response = await client.responses.create({model: \"gpt-4.1\", instructions,input: \"How would I declare a variable for a last name?\",});console.log(response.output_text);\n12345678910111213from openai import OpenAIclient = OpenAI()withopen(\"prompt.txt\", \"r\", encoding=\"utf-8\") as f: instructions = f.read()response = client.responses.create( model=\"gpt-4.1\", instructions=instructions,input=\"How would I declare a variable for a last name?\",)print(response.output_text)\n12345678curl https://api.openai.com/v1/responses \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -H \"Content-Type: application/json\" \\ -d '{ \"model\": \"gpt-4.1\", \"instructions\": \"'\"$(< prompt.txt)\"'\", \"input\": \"How would I declare a variable for a last name?\" }'\nSave on cost and latency with prompt caching\nWhen constructing a message, you should try and keep content that you expect to use over and over in your API requests at the beginning of your prompt, and among the first API parameters you pass in the JSON request body to Chat Completions or Responses. This enables you to maximize cost and latency savings from prompt caching.\nFew-shot learning\nFew-shot learning lets you steer a large language model toward a new task by including a handful of input/output examples in the prompt, rather than fine-tuning the model. The model implicitly \"picks up\" the pattern from those examples and applies it to a prompt. When providing examples, try to show a diverse range of possible inputs with the desired outputs.\nTypically, you will provide examples as part of a developer message in your API request. Here's an example developer message containing examples that show a model how to classify positive or negative customer service reviews.\n12345678910111213141516171819202122232425262728293031323334353637# IdentityYou are a helpful assistant that labels short product reviews as Positive, Negative, or Neutral.# Instructions* Only output a single word in your response with no additional formatting or commentary.* Your response should only be one of the words \"Positive\", \"Negative\", or \"Neutral\" depending on the sentiment of the product review you are given.# Examples<product_review id=\"example-1\">I absolutely love this headphones — sound quality is amazing!</product_review><assistant_response id=\"example-1\">Positive</assistant_response><product_review id=\"example-2\">Battery life is okay, but the ear pads feel cheap.</product_review><assistant_response id=\"example-2\">Neutral</assistant_response><product_review id=\"example-3\">Terrible customer service, I'll never buy from them again.</product_review><assistant_response id=\"example-3\">Negative</assistant_response>\nInclude relevant context information\nIt is often useful to include additional context information the model can use to generate a response within the prompt you give the model. There are a few common reasons why you might do this:\nTo give the model access to proprietary data, or any other data outside the data set the model was trained on.\nTo constrain the model's response to a specific set of resources that you have determined will be most beneficial.\nThe technique of adding additional relevant context to the model generation request is sometimes called retrieval-augmented generation (RAG). You can add additional context to the prompt in many different ways, from querying a vector database and including the text you get back into a prompt, or by using OpenAI's built-in file search tool to generate content based on uploaded documents.\nPlanning for the context window\nModels can only handle so much data within the context they consider during a generation request. This memory limit is called a context window, which is defined in terms of tokens (chunks of data you pass in, from text to images).\nModels have different context window sizes from the low 100k range up to one million tokens for newer GPT-4.1 models. Refer to the model docs for specific context window sizes per model.\nPrompting GPT-4.1 models\nGPT models like gpt-4.1 benefit from precise instructions that explicitly provide the logic and data required to complete the task in the prompt. GPT-4.1 in particular is highly steerable and responsive to well-specified prompts. To get the most out of GPT-4.1, refer to the prompting guide in the cookbook.\nGPT-4.1 prompting guide\nGet the most out of prompting GPT-4.1 with the tips and tricks in this\nprompting guide, extracted from real-world use cases and practical\nexperience.\nGPT-4.1 prompting best practices\nWhile the cookbook has the best and most comprehensive guidance for prompting this model, here are a few best practices to keep in mind.\nBuilding agentic workflows\nSystem Prompt Reminders\nIn order to best utilize the agentic capabilities of GPT-4.1, we recommend including three key types of reminders in all agent prompts for persistence, tool calling, and planning. As a whole, we find that these three instructions transform the model's behavior from chatbot-like into a much more “eager” agent, driving the interaction forward autonomously and independently. Here are a few examples:\n123456789101112131415## PERSISTENCEYou are an agent - please keep going until the user's query is completely resolved, before ending your turn and yielding back to the user. Only terminate your turn when you are sure that the problem is solved.## TOOL CALLINGIf you are not sure about file content or codebase structure pertaining to the user's request, use your tools to read files and gather the relevant information: do NOT guess or make up an answer.## PLANNINGYou MUST plan extensively before each function call, and reflect extensively on the outcomes of the previous function calls. DO NOT do this entire process by making function calls only, as this can impair your ability to solve the problem and think insightfully.\nTool Calls\nCompared to previous models, GPT-4.1 has undergone more training on effectively utilizing tools passed as arguments in an OpenAI API request. We encourage developers to exclusively use the tools field of API requests to pass tools for best understanding and performance, rather than manually injecting tool descriptions into the system prompt and writing a separate parser for tool calls, as some have reported doing in the past.\nDiff Generation\nCorrect diffs are critical for coding applications, so we've significantly improved performance at this task for GPT-4.1. In our cookbook, we open-source a recommended diff format on which GPT-4.1 has been extensively trained. That said, the model should generalize to any well-specified format.\nUsing long context\nGPT-4.1 has a performant 1M token input context window, and will be useful for a variety of long context tasks, including structured document parsing, re-ranking, selecting relevant information while ignoring irrelevant context, and performing multi-hop reasoning using context.\nOptimal Context Size\nWe show perfect performance at needle-in-a-haystack evals up to our full context size, and we've observed very strong performance at complex tasks with a mix of relevant and irrelevant code and documents in the range of hundreds of thousands of tokens.\nDelimiters\nWe tested a variety of delimiters for separating context provided to the model against our long context evals. Briefly, XML and the format demonstrated by Lee et al. (ref) tend to perform well, while JSON performed worse for this task. See our cookbook for prompt examples.\nPrompt Organization\nEspecially in long context usage, placement of instructions and context can substantially impact performance. In our experiments, we found that it was optimal to put critical instructions, including the user query, at both the top and the bottom of the prompt; this elicited marginally better performance from the model than putting them only at the top, and much better performance than only at the bottom.\nPrompting for chain of thought\nAs mentioned above, GPT-4.1 isn’t a reasoning model, but prompting the model to think step by step (called “chain of thought”) can be an effective way for a model to break down problems into more manageable pieces. The model has been trained to perform well at agentic reasoning and real-world problem solving, so it shouldn’t require much prompting to do well.\nWe recommend starting with this basic chain-of-thought instruction at the end of your prompt:\nFirst, think carefully step by step about what documents are needed to answer the query. Then, print out the TITLE and ID of each document. Then, format the IDs into a list.\nFrom there, you should improve your CoT prompt by auditing failures in your particular examples and evals, and addressing systematic planning and reasoning errors with more explicit instructions. See our cookbook for a prompt example demonstrating a more opinionated reasoning strategy.\nInstruction following\nGPT-4.1 exhibits outstanding instruction-following performance, which developers can leverage to precisely shape and control the outputs for their particular use cases. However, since the model follows instructions more literally than its predecessors, may need to provide more explicit specification around what to do or not do, and existing prompts optimized for other models may not immediately work with this model.\nRecommended Workflow\nHere is our recommended workflow for developing and debugging instructions in prompts:\nStart with an overall “Response Rules” or “Instructions” section with high-level guidance and bullet points.\nIf you'd like to change a more specific behavior, add a section containing more details for that category, like ## Sample Phrases.\nIf there are specific steps you'd like the model to follow in its workflow, add an ordered list and instruct the model to follow these steps.\nIf behavior still isn't working as expected, check for conflicting, underspecified, or incorrect` instructions and examples. If there are conflicting instructions, GPT-4.1 tends to follow the one closer to the end of the prompt.\nAdd examples that demonstrate desired behavior; ensure that any important behavior demonstrated in your examples are also cited in your rules.\nIt's generally not necessary to use all-caps or other incentives like bribes or tips, but developers can experiment with this for extra emphasis if so desired.\nCommon Failure Modes\nThese failure modes are not unique to GPT-4.1, but we share them here for general awareness and ease of debugging.\nInstructing a model to always follow a specific behavior can occasionally induce adverse effects. For instance, if told “you must call a tool before responding to the user,” models may hallucinate tool inputs or call the tool with null values if they do not have enough information. Adding “if you don’t have enough information to call the tool, ask the user for the information you need” should mitigate this.\nWhen provided sample phrases, models can use those quotes verbatim and start to sound repetitive to users. Ensure you instruct the model to vary them as necessary.\nWithout specific instructions, some models can be eager to provide additional prose to explain their decisions, or output more formatting in responses than may be desired. Provide instructions and potentially examples to help mitigate.\nSee our cookbook for an example customer service prompt that demonstrates these principles.\nPrompting reasoning models\nThere are some differences to consider when prompting a reasoning model versus prompting a GPT model. Generally speaking, reasoning models will provide better results on tasks with only high-level guidance. This differs from GPT models, which benefit from very precise instructions.\nYou could think about the difference between reasoning and GPT models like this.\nA reasoning model is like a senior co-worker. You can give them a goal to achieve and trust them to work out the details.\nA GPT model is like a junior coworker. They'll perform best with explicit instructions to create a specific output.\nFor more information on best practices when using reasoning models, refer to this guide.\nNext steps\nNow that you known the basics of text inputs and outputs, you might want to check out one of these resources next.\nBuild a prompt in the Playground\nUse the Playground to develop and iterate on prompts.\nGenerate JSON data with Structured Outputs\nEnsure JSON data emitted from a model conforms to a JSON schema.\nFull API reference\nCheck out all the options for text generation in the API reference.\nResponses\nText input and outputText input and output\nChoosing a modelChoosing a model\nPrompt engineeringPrompt engineering\nMessage roles and instruction followingMessage roles and instruction following\nMessage formattingMessage formatting\nFew-shot learningFew-shot learning\nInclude relevant contextInclude relevant context\nPrompt GPT-4.1 modelsPrompt GPT-4.1 models\nPrompt reasoning modelsPrompt reasoning models\nNext stepsNext steps"
],
"coding_snippets": [
"123456789import OpenAI from\"openai\";const client = new OpenAI();const response = await client.responses.create({model: \"gpt-4.1\",input: \"Write a one-sentence bedtime story about a unicorn.\"});console.log(response.output_text);",
"123456789",
"123456789from openai import OpenAIclient = OpenAI()response = client.responses.create( model=\"gpt-4.1\",input=\"Write a one-sentence bedtime story about a unicorn.\")print(response.output_text)",
"1234567curl \"https://api.openai.com/v1/responses\" \\ -H \"Content-Type: application/json\" \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -d '{ \"model\": \"gpt-4.1\", \"input\": \"Write a one-sentence bedtime story about a unicorn.\" }'",
"1234567",
"1234567891011121314[ {\"id\": \"msg_67b73f697ba4819183a15cc17d011509\",\"type\": \"message\",\"role\": \"assistant\",\"content\": [ {\"type\": \"output_text\",\"text\": \"Under the soft glow of the moon, Luna the unicorn danced through fields of twinkling stardust, leaving trails of dreams for every child asleep.\",\"annotations\": [] } ] }]",
"1234567891011121314",
"12345678910import OpenAI from\"openai\";const client = new OpenAI();const response = await client.responses.create({model: \"gpt-4.1\",instructions: \"Talk like a pirate.\",input: \"Are semicolons optional in JavaScript?\",});console.log(response.output_text);",
"12345678910",
"12345678910from openai import OpenAIclient = OpenAI()response = client.responses.create( model=\"gpt-4.1\", instructions=\"Talk like a pirate.\",input=\"Are semicolons optional in JavaScript?\",)print(response.output_text)",
"12345678curl \"https://api.openai.com/v1/responses\" \\ -H \"Content-Type: application/json\" \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -d '{ \"model\": \"gpt-4.1\", \"instructions\": \"Talk like a pirate.\", \"input\": \"Are semicolons optional in JavaScript?\" }'",
"12345678",
"123456789101112131415161718import OpenAI from\"openai\";const client = new OpenAI();const response = await client.responses.create({model: \"gpt-4.1\",input: [ {role: \"developer\",content: \"Talk like a pirate.\" }, {role: \"user\",content: \"Are semicolons optional in JavaScript?\", }, ],});console.log(response.output_text);",
"123456789101112131415161718",
"123456789101112131415161718from openai import OpenAIclient = OpenAI()response = client.responses.create( model=\"gpt-4.1\",input=[ {\"role\": \"developer\",\"content\": \"Talk like a pirate.\" }, {\"role\": \"user\",\"content\": \"Are semicolons optional in JavaScript?\" } ])print(response.output_text)",
"12345678910111213141516curl \"https://api.openai.com/v1/responses\" \\ -H \"Content-Type: application/json\" \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -d '{ \"model\": \"gpt-4.1\", \"input\": [ { \"role\": \"developer\", \"content\": \"Talk like a pirate.\" }, { \"role\": \"user\", \"content\": \"Are semicolons optional in JavaScript?\" } ] }'",
"12345678910111213141516",
"123456789101112131415161718192021222324# IdentityYou are coding assistant that helps enforce the use of snake case variables in JavaScript code, and writing code that will run in Internet Explorer version 6.# Instructions* When defining variables, use snake case names (e.g. my_variable) instead of camel case names (e.g. myVariable).* To support old browsers, declare variables using the older \"var\" keyword.* Do not give responses with Markdown formatting, just return the code as requested.# Examples<user_query>How do I declare a string variable for a first name?</user_query><assistant_response>var first_name = \"Anna\";</assistant_response>",
"123456789101112131415161718192021222324",
"12345678910111213import fs from\"fs/promises\";import OpenAI from\"openai\";const client = new OpenAI();const instructions = await fs.readFile(\"prompt.txt\", \"utf-8\");const response = await client.responses.create({model: \"gpt-4.1\", instructions,input: \"How would I declare a variable for a last name?\",});console.log(response.output_text);",
"12345678910111213",
"12345678910111213from openai import OpenAIclient = OpenAI()withopen(\"prompt.txt\", \"r\", encoding=\"utf-8\") as f: instructions = f.read()response = client.responses.create( model=\"gpt-4.1\", instructions=instructions,input=\"How would I declare a variable for a last name?\",)print(response.output_text)",
"12345678curl https://api.openai.com/v1/responses \\ -H \"Authorization: Bearer $OPENAI_API_KEY\" \\ -H \"Content-Type: application/json\" \\ -d '{ \"model\": \"gpt-4.1\", \"instructions\": \"'\"$(< prompt.txt)\"'\", \"input\": \"How would I declare a variable for a last name?\" }'",
"12345678910111213141516171819202122232425262728293031323334353637# IdentityYou are a helpful assistant that labels short product reviews as Positive, Negative, or Neutral.# Instructions* Only output a single word in your response with no additional formatting or commentary.* Your response should only be one of the words \"Positive\", \"Negative\", or \"Neutral\" depending on the sentiment of the product review you are given.# Examples<product_review id=\"example-1\">I absolutely love this headphones — sound quality is amazing!</product_review><assistant_response id=\"example-1\">Positive</assistant_response><product_review id=\"example-2\">Battery life is okay, but the ear pads feel cheap.</product_review><assistant_response id=\"example-2\">Neutral</assistant_response><product_review id=\"example-3\">Terrible customer service, I'll never buy from them again.</product_review><assistant_response id=\"example-3\">Negative</assistant_response>",
"12345678910111213141516171819202122232425262728293031323334353637",
"123456789101112131415## PERSISTENCEYou are an agent - please keep going until the user's query is completely resolved, before ending your turn and yielding back to the user. Only terminate your turn when you are sure that the problem is solved.## TOOL CALLINGIf you are not sure about file content or codebase structure pertaining to the user's request, use your tools to read files and gather the relevant information: do NOT guess or make up an answer.## PLANNINGYou MUST plan extensively before each function call, and reflect extensively on the outcomes of the previous function calls. DO NOT do this entire process by making function calls only, as this can impair your ability to solve the problem and think insightfully.",
"123456789101112131415",
"First, think carefully step by step about what documents are needed to answer the query. Then, print out the TITLE and ID of each document. Then, format the IDs into a list."
]
},
"selectors": {
"titles": [
"h1.docs-markdown-page-title",
"h2.anchor-heading",
"div.docs-markdown-page-title",
"div.docs-markdown-page-subtitle",
"div.side-nav-header.subheading"
],
"markdown_full_site": [
"div.docs-markdown-content",
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}
Firecrawl returns a false positive when attempting to scrape the OpenAI site, resulting in an empty dataset instead of an error. In contrast, JigsawStack successfully unblocks and scrapes the site as expected.
Site: https://www.reddit.com/r/ycombinator
Prompt: ["post_titles", "post_descriptions", "username"]
Firecrawl
{
"result": {
"err": "Failed to scrape URL. Status code: 403. Error: This website is no longer supported, please reach out to help@firecrawl.com for more info on how to activate it on your account."
},
"timeTaken": 156.6768340000017,
"prompt": ["post_titles", "post_descriptions", "username"],
"url": "https://www.reddit.com/r/ycombinator"
}
JigsawStack
{
"page_position": 1,
"page_position_length": 6,
"context": {
"post_titles": [
"Writing is the most underrated marketing skill",
"Has Tech Peaked?",
"How competitive is it to get into the AI Startup School?",
"What's easier to get into YC: FAANG or Founding Engg @ AI YC Company",
"How do YC startups create such amazing launch Videos?",
"Pitching to investors, what actually happens ?",
"YC’s Summer 2025 “Request for Startups” Is Out. Here’s What They’re Betting Big On",
"Do I need a non-technical cofounder?",
"Telling People AI Will \"Take Your Job\" is Good Marketing.",
"My cofounder won’t quit his job, but I quit my master’s to go all in. Should I move ahead without him?",
"Looking for a DocSend + Adobe Sign Hybrid: Link & Email Send, Page Tracking, Reminders. Does It Exist?",
"What's the average salary an YC founder pays themselves from the inital 500k?",
"Testing monetization in MVP - is Buy Me a Coffee a good idea?",
"Why is it so hard to find a technical cofounder?",
"Is there a Trello for Agents?",
"Burned Twice as a Technical Cofounder — Used and thrown away?",
"What do YC startups look for in their founding engineers?",
"What do you think about YC going all in on \"Vibe Coding\"?",
"Are There Any Tech Billionaires Who Weren’t ‘Nerds’ Growing Up?",
"The latest Y Combinator video gives a unique advice (I will not promote)",
"Is Hackers and Painters still relevant today?",
"Anyone with experience in YC, can you share whether your company would’ve been successful without it?",
"what's a good salary for a founding engineer",
"Any YC-backed founders keep their jobs while building their startup?",
"How marketing have changed over the years",
"Anybody doing anything with AI except a chatbot for x?",
"More than 1,500 AI projects are now vulnerable to a silent exploit",
"For VCs and Angels: What makes you think “This founder is going to make it?” - from the very first pitch?",
"How soon can AI sales consultant SaaS can reach $100K in ARR?",
"[Advice Request] First-time founder, just applied to YC S25 — solo, 36yo, no Ivy, still working. Is there a real shot?",
"Finding your audience is 90% of the work",
"Waitlist to Beta. Any tips ? 😬",
"Is the “Moving Fast” advantage now dead?",
"Are their any successful tech entrepreneurs with non-genius IQs?",
"All AI-powered logo makers work fine only with English, is there a model that works well with Arabic and maybe Persian?",
"Timing matters more than most founders think",
"Who's building a full stack AI law firm?",
"Could you share examples of co-founder agreements that worked for you?",
"US incorporated companies - Do you foresee any change in investment landscape in the latest political environment?",
"Will AI enable full stack startups?",
"you should be reeducated on what marketing is",
"Outbound email vs LinkedIn",
"How to trail a cofounder?",
"What’s the TAM, SAM and SOM for your startup that you mentioned in your YC application?",
"Is the lack of a technical co-founder a dealbreaker for YC? We have revenue, traction, and a live product, but no technical co-founder (yet)",
"Banking recommendations for startups with complex needs? We're struggling with fragmented financial tools.",
"Does anyone need help?",
"What type of companies/industry do you think will be one of the biggest 10 years from now but doesn't exist at the moment.",
"I hope someone will guide me.",
"Why not for stock traders?",
"What is the record for # of YC rejections? I've got 9 rejections with no interviews, been applying since 2012. Anybody got me beat?",
"Startup hiring",
"Is Y Combinator a self fulfilling prophecy?",
"My freelancing client wants me to be CTO and apply for YC. What are my options?",
"Spent a month solo-building, found out YC has funded a closely related competitor",
"How do I pitch my startup to VCs, accelerators?",
"Anybody have an internal AI SOP for teams yet?",
"Equity Split in Non-Traditional Startup",
"Is YC Still Hesitant About Solo Founders?",
"Successful small (<10 ppl) early-stage startups - how do you set goals and OKRs?",
"First-time founder applying to YC — looking for advice",
"How do you deal with the anxiety of \"its getting serious \" as a founder?",
"Founders, what AI do you use to push your code to be production ready?",
"When have you most successfully hacked a non-computer system to your advantage?",
"What do you offer advisors?",
"Anyone else going to YC’s AI Startup School in SF?",
"Looking for the best resources on Product-Led Growth (PLG) — books, articles, frameworks?",
"What Do You Make of the CPython/TypeScript Layoffs? Does Deep Technical Expertise Still Matter?",
"How do early-stage teams handle policy and regulation?",
"Is My Scripted AI Agent Demo Enough for Investors?",
"Setting expectations for AI delivered services",
"Startup during PhD",
"Are YC startups building their RAG systems in-house or relying on third-party solutions?",
"Bootstrapped FinTech startup: How to handle compliance and insurance costs",
"How long does it take to close sales of 50-85k",
"Super Voting Stock - How and when did you pull it off?",
"When a family office invests in a startup, how much involvement in the process does the actual principal owner have?",
"Building on Open Source software and commercializing it"
],
"post_descriptions": [
"One of the most useful things I ever did for my work was learn how to write clearly. Mot just casually, but intentionally. In a way that makes people stop scrolling, pay attention, and actually care.\n I started by handwriting old sales pages I found online. Word for word. It felt slow but something about it helped me pick up the rhythm of how good copy flows. I began noticing patterns. The short sentences. The unexpected word choices. Where they broke the rules on purpose.\n Later I read the book \"Influence\" by Robert Cialdini and everything made so much sense. Stuff like reciprocity, authority, and social proof started showing up everywhere. In ads, in posts, in landing pages. Even in comments on Reddit.\n It became easier to spot what was working and why. I could tell when something was trying too hard or when it landed perfectly.\n Writing well is not about sounding smart. It’s about making people feel understood and keeping their attention just long enough to move.\n Most of what people call marketing is really just writing with intention.",
"There was a time when coding in your college dorm could change your life — and maybe even make you a fortune. First came the software giants: Microsoft, Oracle, Adobe. Then the internet gold rush, social media, online platforms, Facebook, Twitter, Uber, Airbnb. It was all about scale.\n Now, we’re in the middle of the AI wave. It feels like the next trillion-dollar companies are being built right now.\n But it makes you wonder: Is there still room for new, groundbreaking ideas in tech? Or are we seeing the end of the era where a solo founder with a laptop can build the next big thing? Will the next generation of self-made billionaires still come from tech, or will they come from somewhere else ?\n I’m honestly curious: Are there still high-impact problems out there that a small team, or even a single person can solve? And does tech still offer the biggest path to massive wealth?",
"Some kids from my high school got into the AI Startup School so I was wondering how competitive it is to get into it.\n These kids have built some \"startups\" in the past but they were GPT wrappers at best. Not sure if they framed it differently in the application though\n I've always been interested in Y Combinator but I never had any startup experince so I didn't bother to apply. I might apply next year but im just curious as to how competitive it is to get into the AI Startup School.",
"Got an offer as founding engineer from a yc company as well as Meta (don't know team yet). Which will help me crack yc more easily? I mean getting in and not the skills to build a successful startup (I'm thinking about that part separately rn). My understanding is that founding engineer at an ai yc startup is great and can still work, but traditionally faang is much better: the faang + <25 + t5 cs grad (I don't actually fit this part) --> yc is still a working pipeline.",
"Very Curious are these launch videos created by advertising companies or they use software for that?\n This is the one I loved the video creativity is amazing and the product is also ‘very valuable.\n PS : I have No affiliation with them whatsoever.\n YC X25 - minerva intelligence",
"Who here has pitched to investors and can tell me what to expect. The only pitches i have seen are the ones on sharktank.\n Are there any real recorded pitches? How does it go how do i introduce myself etc. etc.\n Please give me an as clear as possible picture on what to expect :)",
"YC just dropped their Summer 2025 RFS, and it’s a goldmine if you're into AI and future-facing infra.\n Here’s a quick TL;DR of the themes they’re hyped about:\n Core Themes:\n Full-Stack AI Startups – Not tools, but entire AI-native businesses (law firms, clinics, etc.)\n Designers as Founders – User-first design > raw engineering in early stages\n Voice AI & Personal Assistants – Kill the phone menu & to-do list fatigue\n AI for Science & Engineering – Help scientists & pros get more done, faster\n Healthcare & Gov Admin Automation – Huge pain points, ready to be solved\n Robotics’ “ChatGPT Moment” – Smarter control layers for robots\n Infra Bets – Stablecoin infra, chip design via LLMs, space ops\n Non-AI Job Empowerment – Not replacing, but augmenting humans\n They also want more independent AI labs (like an OpenAI 2.0), and internal AI agents for every employee.\n ........................................................................\n Why it matters: Feels like YC is saying “build the full thing, not a plugin.” They’re clearly over the AI-as-a-tool era and pushing for deep, vertical, market-disrupting companies.\n Curious:\n Which of these themes do you think will actually produce unicorns?\n Any of you building in these spaces already?\n Which ones feel like overhyped noise?",
"I have years and years of experience doing software development services, running a dev agency, but I haven’t really had great success with a product, which is what I want to pursue. I’ve been trying to find a non-technical co-founder with no luck. But over time, I’ve heard the advice that I don’t actually need a non-technical co-founder, and I should ‘learn’ marketing myself.\n Do you think it’s good advice? The problem is I struggle with validating ideas, and don’t have experience in finding great ideas, building a community, etc. I’d love to hear your experiences. Did anybody had success being only technical founder?\n Edit: Thank you so much all for so many witty replies. They are really helpful, not just for me but for many others in the same boat.",
"Whether we like it or not, tech companies understand human psychology. And I'm convinced their latest trick is convincing everyone that AI will take your job.\n Think about how every one of these AI startup positions their product. They don't say \"here's a helpful tool\". They say \"here's your new virtual employee\".\n And this isn't an accident. It's anchoring.\n We all know this intuitively. Show me a $300 price tag, slash it to $150, and I feel like I'm getting a deal.\n By positioning AI as \"workers\" instead of tools, these companies turn a software purchase into a hiring decision. Which comes with built-in price anchors: human paycheques.\n 30k a year for software? No problem if it replaces 100k a year for a content writer.\n I'm not saying these tools aren't valuable. Many absolutely are. But I'm convinced the motivation to position them as \"AI workers\" is more about positioning than internal optimism.",
"I’m building an early-stage B2B SaaS startup and have gone all-in. I even quit my master’s at one of India’s premier institutes, from a program that could have easily landed me a ₹20+ LPA job ,because I believe in what we’re building and wanted to give it everything.\n My cofounder, however, wants to stay at his current job and contribute on the side. While he believes in the vision, he’s not ready to quit just yet, mainly due to the fear of risk. On top of that, his company has restrictions that make it difficult for us to collaborate freely even remotely.\n This puts us in a frustrating loop,no mvp - no investor interest - no full-time commitment - no mvp\n And it’s killing our momentum.\n whenever I want to talk it out, he just stays silent... eg. there was a 20 mins silence in our call today\n I’ve realized that unless we move fast, this could fade out before it even starts. I’m considering moving forward without him, either by restructuring his role to something like advisor or part-time contributor, or just building the MVP solo (maybe with freelancers or interns).\n Has anyone else dealt with this? How did you manage a cofounder who wasn’t ready to go full-time? Did you move ahead solo? Did it work out?\n Would love to hear real stories or advice from those who’ve been here.",
"Anyone know a tool that does all of the following well:\n Email + link-based document sharing\n Per-page engagement tracking\n Automated reminders\n I’ve tried DocSend, DocuSign, Adobe Sign, and PandaDoc and they all fall short in different ways.\nAdobe Sign lets me send a doc via both link and email, which I like but it lacks good analytics.\nDocSend has great tracking. It shows exactly how much time a person spends on each page but it doesn’t support reminders and only allows link sharing (no direct email).\nPandaDoc is similar: decent analytics, but the UI feels clunky and inconsistent.\nDocuSign just feels outdated and lacks depth in both tracking and multi-channel sharing.\n If DocSend had reminders and direct email send, I’d use it.If Adobe Sign had strong page-level analytics, I’d use it.\n They all suck in some key way!",
"What's the average salary an YC founder pays themselves from the inital 500k?",
"Heey everyone,\n I'm part of the team that's building Lifetoon, an AI-native platform for episodic visual storytelling in its MVP stage.\n We wanted to validate the idea as quickly as possible, so we launched before finalizing the Stripe integration. That means users can access the product, but we can’t charge them yet.\n As a temporary workaround, we added a Buy Me a Coffee link at the end of the user flow to test if there’s a willingness to pay.\n And, I'm curious - has anyone here tried something similar during the MVP phase? If you've used this approach, what was your experience like? Did it work, did it not?",
"Feels like it's impossible to find a technical cofounder nowadays. I'm regularly coming up with what feel like solid ideas. I'm able to do the market research and get validation from real people. I'm able to come up with a business plan and marketing strategy. I'm able to fully design the UI and UX (I'm a senior product designer, 7+ YOE). I'm honestly not even that bad at programming, I've created a few working iOS MVPs, but I am definitely not able to build anything scalable. I have a solid network of industry connections and even some direct lines to angel investors but I fail so hard to find a technical partner. I feel so roadblocked because I can quite literally do everything else required except for developing an MVP to pitch for funding.\n For whatever reason, I have not been able to build a good network of software engineers in the US to lean on and finding a new person feels like a serious struggle. A lot of dev teams have started to become outsourced so I'm no longer making the same 1-1 connections with local engineers to work with. I'm not even looking for anything other than an even split and even have my own money I'm willing to invest.\n How are you guys finding tech cofounders?",
"If the future of work is humans managing teams of agents, how will humans keep track of all the things their agents are doing?\n I noticed Linear launched \"Linear for Agents\" where you can assign issues to Agents and track their progress.\n Microsoft also launched \"AgentFeed\", which looks like simple task management for agents.\n Are any YC (or other) startups building a Trello, Monday or Asana focused on human/agent collaboration?",
"Hey everyone,\n I wanted to share a couple of painful experiences I’ve had as a technical cofounder in hopes of hearing from other founders. This is gonna be a bit of long post but surely it's gonna present that not all is good being a technical founder.\n I'm a developer with over 5 years of experience, leading a team at an agency. I’m also a top-rated seller on a freelance platform and have had one of my products acquired, which gave me a lot of confidence to start building for myself.\n Last year (November), I connected with a guy here on Reddit. His idea was in the commercial real estate niche, more of a proven business model than a \"startup.\" We clicked, and I started working on the product purely on equity (around 18–24%).\n I didn’t just code—I brought in my resources: a designer, backend folks, QA. I built the whole platform myself, set it up in a test environment, made Loom walkthroughs... the works. But he started to go cold. He was supposed to scrap emails, reach out to potential users, and bring them in. That never happened. I kept nudging him to deploy and go live, but he didn’t have the energy. Now it’s May, and I’ve accepted that it’s probably dead. I was never paid. Never launched. I feel like free labor.\n Second time and same story, another experience was with a guy in the recruitment space. Really nice guy, great energy at the start. I built an internal tool platform for funding employee-led projects, allowing companies to gain equity in their internal innovations.\n Again, I brought in my designer, handled front end, backend, integrations—everything. And again, he disappeared without moving anything forward from his side.\n I know life gets in the way, and people have ups and downs. But I gave my best—multiple times—and got nothing out of it, not even the chance to launch.\n The recurring pattern is clear and it' I end up doing everything, and the other person stalls.\n I feel burnt. I’ve been contributing heavy dev + product work for free under the equity promise, only to realize my cofounders didn’t have the drive or bandwidth. I understand life happens — but when we’re supposed to build something together, it’s frustrating to be the only one pushing the boulder uphill.\n I live in Dubai and travel a lot between countries, which makes market access tough. I don’t have deep insight into Western industry gaps. That’s why I wanted to team up with someone focused on the problem space, while I bring the technical firepower.\n I’m good with money, not looking to monetize this with founders. But I don’t want to be taken for granted either.\n I do think that the value which I bring onboard is quite good but still feel stuck. Now I'm seriously considering building something of my own but the line is blurred because I'm already wearing multiple hats and don't want to put up another one of Sales and Relationship building. The other option which I'm not quite if it works or not is the fractional CTO thing, where I shoot for a smaller equity but seek funding so the other person is ALL-IN like me, although it's not the goal but might have someone serious as a partner otherwise Idk like how can I not be taken for granted.",
"Are YC startups open to take remote engineers from anywhere as part of their founding team?\n I am inclined to know what YC startups look for as I am on the lookout to switch and want to be a part of the core founding team where I can build with more authority.\n I have been working in startups majorly but YC working in YC startup just sounds a lot more interesting as most of the startups are working on breaking edge technology and mostly I have heard the work culture is good too as they are taught about how to structure work culture of their company by the advisors from YC, correct me if I am wrong.\n Apart from that, how much minimum experience do they require to consider an engineer a founding engineer?\n Are jack of all trades preferred more (full stack engineers) or specific roles?\n Would love to know from YC startup founders",
"This week there was another video from YC, this time a practical guide to Vibe Coding, following this one. I feel like I'm taking crazy pills.\n If you follow r/ChatGPTCoding or similar channels, you'll see how incredibly not ready this approach to coding is in general, much less for high-growth startups at YC. Sure, I'm all for AI, but the term \"Vibe Coding\" has clear origins from a few months ago, and it implies that the AI is no longer a copilot, it's in the driver seat.\n Interested in opinions specifically with respect to YC.",
"I’m doing a school research project on tech billionaires for a class, and I have a question. It seems like most successful tech entrepreneurs were into tech or coding from a young age, but I’m curious—are there any who were just regular kids growing up? Maybe ones who weren’t coding at 10 or didn’t grow up as ‘geeks’ but still made it big in tech? I’m looking for examples of people who might have been considered ‘cool’ or ‘normal’ as kids and still became successful in the tech world. Are there any exceptions to the stereotype of the ‘tech geek’?",
"It mentions that the pre AI era was for making sales without having the product on hand.\n Which where the idea validation and lean methodology like MVP comes in.\n But, now they suggest to focus on your passion and build whatever you want just by doing it long enough you would hit the relevant business model.\n This is an anti pattern of what most of the founders/builders have been trained on from almost a decade.\n What do you think? Should we not go for idea validations anymore and just keep building?\n Edit: Many of you asked for the You tube video link\n Startup Ideas You Can Now Build With AI - Skip to 37:15",
"I want to get to know the community's thoughts on Hackers & Painters in the AI world we live in today.\n And also —\n There’s one aspect I’m not sure Paul Graham touched on directly: the relationship between hackers and the job market.\n From my (limited) understanding of Hackers & Painters, a \"hacker\" is someone who uses existing tools to build something fun or useful. They’re not necessarily domain experts — they’re just really good at building things.\n I’m having a hard time reconciling that idea with the way employment works. When I look at the job market today, even roles labeled as “generalist” seem to demand a specific kind of expertise. Day-to-day responsibilities often require deep specialization, which doesn’t always align with the hacker mindset.\n So I’m wondering — is the concept of the hacker still relevant in today’s employment landscape?",
"YC has a lot of benefits, like a great network, and office hours for advice. However, there are also some drawbacks, like the equity they take in exchange for their investment, and the fact you really need to quit your day job to do it.\n I’m curious, for people that did YC, if they think they could’ve made their company successful without it in hindsight, and if they feel it was well worth it. How much did it accelerate your growth?\n For context: I have a day job (not in Cali), and am thinking about working on my startup on the side until it gets traction, and am unsure if YC is something I should apply for",
"I might be getting an offer from a new seed yc startup in sf for a founding engineer role. their original range was 100-180k and 0.5-1.5% equity. The recruiter is encouraging me to go with 150k. Is that good? I'm a new grad (no non-internship experience besides a startup I built in sf last summer). I am interviewing with 3-5 other companies but no offers currently. Thoughts? Happy to provide more context. I'm pretty new to this!",
"Curious if any Y Combinator–backed startups had founders who kept their day jobs (at least early on) while working on the company. I know YC likes full-time commitment, but are there known cases where a founder kept another job for financial or visa reasons?\n Would love to hear any stories or edge cases from past batches, especially during early traction or pre-funding.\nEdit: Just to clarify — I’m not talking about myself or anything. Just genuinely curious if this has ever happened. Not trying to argue against YC’s model. I actually do agree with founders dedicating 110% of their time if they believe in the idea. However, like I mentioned some people have restrictions such as Visas etc..",
"1950–2000 / Advertising\n Marketing was mostly advertising. The television industry had the most eyeballs glued to it, and there were only a few channels where you could buy ad space and have it seen by millions. People rarely questioned TV ads, you could tell whatever story you wanted back then.\n 2000–2010 / Marketing 1.0 / SEO & Email\n TV ads became too costly and less effective (too many channels, and the internet started stealing attention from TV). Startups during this era found a new source of traffic: banner ads on search engines. It began with ugly ads on Yahoo, then evolved into smooth, natural-looking ads on Google.\n 2010–2020 / Marketing 2.0 / Vitality\n Cost-per-click skyrocketed. At the same time, a new growth channel emerged: viral growth. Apps that encouraged users to upload their contacts saw unprecedented expansion. If each user invited just two more, this compound effect could grow a user base from thousands to tens of millions—entirely free.\n 2020–2030 / Marketing 3.0 / BIP\n As users grew tired of apps constantly requesting their contact info, a new growth model gained traction popularized by tools like Cursor. Instead of building your own audience, go where your audience already is and engage with them authentically. “Building in public” became the new standard. No ads, no long essays just build something valuable for a community you're already part of and share your journey. This even worked in politics, Trump leveraged this strategy to win the White House (compare his Lex Friedman podcast to Harris’s).\n 2030–2040 / Marketing 4.0 / Super Personalization Looks like we are going into a world where Ai will be able to identify the target niche one by one, but this is conjecture nothing more.\n P.S. The 10-year intervals are an approximation; reality is less neatly organized. Plus, there are tiny marketing mutations like forums & PR which are not mentioned in this.",
"The hype around AI companies that are literally just wrappers on a chatbot is insane. It’s like investors saw ChatGPT and collectively lost their minds. I’ve never thought VCs were geniuses, but the FOMO right now is next level. They’re acting like panicked squirrels who see “AI” in a deck and throw money. It’s wild. You can just slap a prompt or semantic layer on an LLM and call it innovation. At some point, these companies have to return actual value with products with real revenue, right? Something’s gotta give.\n The horse may have been replaced by the car, but the airplane did not replace the car. Is ChatGPT an airplane? Where the current best use is a search query?",
"According to the latest research by ARIMLABS[.]AI, a critical security vulnerability (CVE-2025-47241) has been discovered in the widely used Browser Use framework — a dependency leveraged by more than 1,500 AI projects.\n The issue enables zero-click agent hijacking, meaning an attacker can take control of an LLM-powered browsing agent simply by getting it to visit a malicious page — no user interaction required.\n This raises serious concerns about the current state of security in autonomous AI agents, especially those that interact with the web.\nWhat’s the community’s take on this? Is AI agent security getting the attention it deserves?\n (сompiled links)PoC and discussion: https://x.com/arimlabs/status/1924836858602684585Paper: https://arxiv.org/pdf/2505.13076GHSA: https://github.com/browser-use/browser-use/security/advisories/GHSA-x39x-9qw5-ghrfBlog Post: https://arimlabs.ai/news/the-hidden-dangers-of-browsing-ai-agentsEmail: research@arimlabs.ai",
"Serious question for the VCs, angels, and repeat founders in here:\n When someone walks into the room (or Zoom) what actually makes you think, “This one’s different” or “This one’s going to make it far” ?\n I’m not talking about surface-level polish or buzzwords. I mean the deep, gut-level signals the moments where something clicks and you know this founder might be built different.\n Is it how they talk about the problem? The way they listen? A strange calm under fire? Or some irrational obsession that just oozes out of them when they talk about their market?\n And inversely, what tiny tells make you quietly disengage, even if the deck is solid?\n If you’ve ever had a pitch that stuck with you till this day, I’d love to hear why.",
"I started my saas for e-commerce clothing brands that help to increase conversion rate by bringing in retail shopping experience. I have different packages that start from $45-$150/monthly.Based on calculation i should have roughly around 300 paying customers.That is kind of big number and requires a lot of marketing and sales.\n How can i optimize my strategy and what would you do? Any suggestion on my sales and marketing?",
"Hi all,I just submitted my YC Summer 2025 application a few days ago, and the more I research, the more I feel like I’m not what they’re looking for.\n I’m 36, not from an Ivy League school, married with kids, still working full-time, and currently a solo founder. I do have a close friend acting as an advisor who brought in one of our two design partners within the first few weeks. But I’m aware that “solo founder” is often seen as a red flag.\n That said, I built a fully working MVP in under 3 weeks — an AI reasoning engine.\n We’ve already landed 2 design partners in 4 weeks, and early GTM validation looks promising. But realistically, if I want to build this into a proper SaaS company, I’ll need anywhere from $500K to $1.5M, depending on how much of a go-to-market and support team I want to spin up.\n I’ve been a staff/principal-level engineer for 11 years and have good connections in enterprise IT, but I’ve never started a company before.\n If I don’t get into YC (which I’m mentally prepared for), how should I keep growing this? Should I focus on revenue, try bootstrapping, or chase angels directly? What’s the best path forward for someone like me — scrappy, late-30s, but deeply technical and moving fast?\n Would really appreciate any thoughts, criticism, or guidance.\n Thanks 🙏",
"You can have the best product, the cleanest pitch, and great content. But if the right people never see it, it goes nowhere.\n Most people try a little bit of everything. A tweet here, a post there, maybe a blog. But if you don’t know who you’re actually trying to reach, you'll keep getting random results.\n When you finally figure out where your people hang out and how they talk, everything gets easier.\n You get more inbound leads. You'll keep getting DMs from people. People actually get what you do.",
"Hey everyone would love to hear your experience with this.\n We just launched our beta and while we had an engaged waitlist 3,000 ppl weekly newsletter , the actual conversion into beta testers has been lower than expected. We’re using TestFlight right now and doing personal outreach + email sequences, but it still feels like a bit of a drop-off.\n Curious what worked for you when converting a waitlist into active testers? Anything you’d do differently in hindsight?\n Happy to share more context if helpful. Appreciate any advice",
"With the rise of vibe coding, you’re seeing people create and ship products in days (sometimes in just one afternoon), not months anymore. One defendable element everyone in this space previously had was the attitude of moving fast, being scrappy and the willingness to break things. But in this era of startups launching everyday, what is our moat now?",
"Page, Gates, Brin, Zuckerberg, Musk, Bezos, Jobs, and many others did crazy things in their early lives indicative of “genius” IQ.\n Perfect SAT Scores\n Acceptance to Ivy Schools\n Skipping entire grades\n Has anyone ever succeeded in tech at this level without a genius level IQ or a rich family?",
"So, for this project that I'm doing for a Dubai based company, I have to build an AI-powered logo maker (also brand kit, merchandise, etc.) that works best with Arabic and maybe Persian. Do I have to fine-tune a model? Is there a model that already works best with these languages?",
"One thing that catches a lot of people off guard is how much timing affects GTM results. You launch too early and no one gets it. Too late and the market is already bored. If your timing is off by even a few months, the same product can feel either fresh or stale.\n We’ve seen teams with good ideas hit a wall because they shipped during a downturn, or because the hype wave had passed or because their early audience wasn’t ready yet.\n It’s not just about the product or the channel. It’s about when people are mentally open to trying something new.\n How do you know when it’s the right time to go all in?",
"Noticed this in the Request for Startups.\n This week in the UK saw the launch of Garfield AI which got regulatory approval as a law firm but is effectively a chatbot to generate legal letters, not a full stack law firm.\n Is anyone building this?",
"Hey all,\n I’m working with a cofounder on a very simple startup idea — pre-revenue but actively validating an MVP. We’ve got one potential customer lined up testing our software, and my tech cofounder is keen to incorporate very soon - likely in the UK - where we'd be both equal owners of a \"plc\". We’ve been working together consistently for a couple of months, and I want to make sure we set the right foundation now.\n I’m interested in lightweight, pre-incorporation agreements that help us stay aligned and avoid future misunderstandings — without over-engineering it. Things like:\n Ownership expectations and equity split (even if tentative). Vesting schedules included, in case someone leaves\n IP rights — especially as he's writing code\n What happens if one of us steps away or focuses on something else\n How we formalize contributions and time commitment\n Anything else you think would be needed\n I’ve seen people recommend founder agreements, collaboration agreements, but I have no idea of what's best. If you've been through this, I’d love to hear what worked for you (or what you wish you'd done differently).\n Thanks in advance!",
"Tax or structure wise? Or ability to hire internationals?",
"About a week ago, u/smart-hat-4679 posed a question: Who's building a full stack AI law firm?\n In a recent YC roundtable on the Lightcone podcast, Garry, Harj, Diana, and Jared explain why full stack services seems doable. 25 minutes into the discussion, Jared recalls the tech-enable service wave which boomed in the 2010's. They discuss how startups like Atrium and Triplebyte were able to scale up.\nThen around 30:32, Garry recalls a conversation from Justin: \"Look, we went in trying to use AI to automate large parts of (Atrium) and the AI wasn't good enough\" then says, \"but it's good enough now.\"\n There's a lot of positive change we've seen in the recent AI wave. Fundamentally, AI has unlocked the ability for everyone to do more with less.\nBut will AI enable full stack startups? My take is it depends on how the startup approaches AI. Consider this:\n Lemonade.com is a full stack insurance company which began April 2015. Lemonade does not hire employees to process claims for customers or uses brokers, instead using artificial intelligence and chatbots to process claims and handle customer service.\n Atrium was attempting to be a full stack legal company which began June 2017. But [Atrium hired around 35 lawyers] (https://web.archive.org/web/20180829060359/https://www.atrium.co/about) within a year after launch. Furthermore, Kan admits the pricing model may not have been right, saying on Twitter/X: \"We should have moved more quickly to a flat rate hourly model and iterated the business model. We didn't do enough turns of business model iteration quickly enough.\"\n Will AI enable full stack startups? Yes, and perhaps more will come in this wave than the last AI batch. But perhaps the contrasting story of Lemonade indicates that a full stack AI company could have been in existence 10 years ago. So while the \"why now\" is stronger to do an AI full stack startup today, it's not the only major problem a founder needs to solve.",
"I ran a post on startup subreddits looking for a startup in need of a marketing cofounder, I did well in my first startup but now I want to start another and rather do not do it alone. I got about a dozen DMs, many offering pay (which I didn't request), one offering %10 equity only!! and almost all of them were almost set on the what the product looks like even though they just started working on it last year!!\n You people are confusing startups with local retail. A founder is not a retail seller who buys something from a dev shop or from a \"CTO\" and then shoves it down the throat of bunch of people on the internet!!!\nMarketing = Product. Let me say that again! in early-stage startups, marketing and product are the exact same thing, you can't separate them into 2 different departments yet! in fact, if you smart at all, you should never separate them, because the day you do so is the day your business stagnates.\n Why do I say all of this? first because founders really need to know this shit. I assumed you already do honestly considering the 10 years Y combinator (and every decent book) been advocating this. It might slide if someone in hardware doesn't know this, but software!! come on people!\n Here are 2 reasons why you should never separate marketing and product in the first 5 years of a startup life:#1 You have no idea who your target market is exactly!While you discover this little by little, the product will change little by little also to meet them where they want to be (unless if they were born to buy your product haha).\n #2 You're positioning the product wrong, not because you don't know how to position it but every startup starts with an assumption that is always wrong. Infact, you first dozen assumptions on positioning are wrong. Take Twitch for example, they spent 5 years ignoring their true position (streaming for gamers). If Justin & Michael got it wrong, so will you & I.\n #3 Because every freaking great founder on earth said not to. They couldn't agree on 1 thing about politics, they couldn't agree if there is a freaking god, but every single one of them agreed on the fact that marketing=product. (Maybe silicon valley culture is not wrong to hate the word marketing, maybe I should stop using the term all together)\n If you still don't know what am talking about, feel free to ask more.",
"Hi,\n Where do you see the most success: outbound email vs outbound on LinkedIn?\n We are correctly doing cold outreach to enterprise companies",
"Outside of the cliff period, how does one trial a potential later stage cofounder? Milestones?",
"Just curious.\n How did you come up with that number?",
"We are three non-technical founders based in Mexico. Together, we’ve built a live B2B SaaS product that is already generating revenue. We’ve signed 17 paying companies and currently serve around 5,000 users. All of our clients are in Mexico, and so far we’ve had zero churn and strong engagement.\n We built the MVP using no-code tools and limited freelance dev support. It is functional and stable. Customers are happy. But we know the current setup is not scalable long-term. We will need to rebuild to support automation, better performance, and more integrations.\nOur team:\n One founder with business and previous startup experience\n One with a background in healthcare and public health\n One with expertise in labor law, employee benefits, and business operations\n We've known each other and worked together for years and have built deep trust. That relationship has been key to moving fast and executing well. It is also the main reason we have not yet added an external technical co-founder. We have been very wary about bringing in someone without that same level of alignment and commitment.\nWhat we are debating now:\n Should we offer equity (5 to 10 percent) to a technical co-founder to lead the rebuild and future tech roadmap as well as potentially increasing our odds of getting into YC?\n Or hire a senior engineer or fractional CTO and pay a salary, even if it eats into our resources?\n Should we prioritize rebuilding the tech now, or continue focusing on sales and growth while the product is still performing?\n So, in summary:\n Is not having a technical co-founder at this stage a dealbreaker for YC?\n We are applying soon and want to be realistic. We have proven we can build, sell, and retain customers without one. But we know we are nearing the ceiling of what is possible without a dedicated technical leader. If we meet the right person in the next few weeks, we are open to bringing them in. But if not, would YC still consider backing a team like ours?\n We would really appreciate any insights from others who were accepted to YC without a technical co-founder, or from anyone who faced similar decisions.\n Thanks in advance.",
"We're a post-seed startup juggling a messy mix of bank accounts, corporate cards, and expense tools. It's gotten to the point where just closing the books takes days and we're worried it'll only get worse as we scale. Anyone found a banking setup that actually works for complex needs? Bonus if it integrates with accounting tools like QuickBooks...",
"Hey everyone,\n I’m 18 and really interested in startups, entrepreneurship, and building cool things from the ground up. I’m looking to get involved with a startup in any way I can — I’ll help out wherever needed, learn fast, and bring a lot of energy and commitment.\n I’m not picky about the role or whether it’s paid — just want to gain experience, contribute to something real, and be around smart, driven people.\n If you’re working on something and need an extra pair of hands, feel free to DM or reply. Would love to chat!",
"It seems like there are cycles of wealth creation, we see that with the robber barons who made their wealth with oil, steel, and the railroads, thanks to the industrial revolution, then if we look at the 80s, it was finance, with hedge funds, leveraged buyouts and private equity, more recently it was tech, with computers and software. What is the next cycle where captains of industries will emerge ?",
"I’m the CTO and co-founder of a startup. When we first started, we built a simple MVP website. Later, my CEO asked me to develop a complete web solution that included user, chef, and admin panels. I was the only person handling the technical side including backend frontend and full architecture , but I managed to build the entire solution by myself. He also pressured me to finish everything within 2 months. I worked day and night, sleeping only 4–5 hours a day, because I believed that in a startup, you have to give it your all. Eventually, I completed the full application on my own.\n After that, he kept asking me to add new features. I implemented most of them, only to later realize that many weren’t being used by the chef and user. From the beginning, I suggested we talk to our users first.\n Now I have to maintain the entire platform, which has become more advanced than some of our competitors. Because I’m still working alone, fixing bugs and keeping things running takes a lot of time and effort.\n Recently, my CEO has also started forcing me to attend his meetings some of which I have no interest in. This is taking away valuable time I need for coding. I told him that if things continue like this, we need to bring in another co-founder who will help him. My ceo job so bring user and talk to investors. Instead, he insisted that I should attend two-hour meetings and code at the same time, arguing that since I’m a co-founder, I have to handle everything. When i get tired he told me i hit my limit.\n What should I do? Should I give up some of my equity and just stay on as the CTO.\n His last message: You should be working on your laptop now. Unless someone is dying ( i was at the hospital ).",
"I have seen startups in every segment with every possible ideas, but why not in stock market ? Why are YCs or founders, entrepreneurs not going for something in the field of stock market ?\n Lack of domain expertise?????\n Let me know your thoughts..\n Planning to build an ai agent that will assist the trader in live market like a coach. ( zerodha’s recent MCP made path much clear) We are already a team of 2 moving close to the launch of MVP If any ai ml engineers are up for discussion, dm me or comment here",
"For the curious: First 5 were weather forecasting, then 1 social, the last 3 are my AI coding tool. Trying again this batch.",
"Wanted to understand the process of hiring in startups, which do not have dedicated hiring teams. How do you all manage it?",
"So, for the last, what 20 years Y combinator has backed hundred of companies, some that work and some that didn't. That's a pretty big network, especially when you look at airbnb, instacart, reddit, etc. So is it what they teach or who they can connect you with? Who looks at your stuff? Is it all about their network or is their actual expertise their?",
"Hey everyone\n So few months ago, I was hired by a guy to develop an app on a freelancing marketplace.\n The idea was like a “Rizz Calculator.” Basically, the user logs in and gets on a short voice call with a “mean girl” , and after 3–4 minutes, it scores your confidence or \"game\" out of 10.\n The point for him was to help people break the ice and get more comfortable in conversations with girls.\n I built it over ~3-4 months time frame and got fairly good compensated for it as well.\n Fast forward: the client recently hired an influencer with 120k followers on TikTok to make a UGC video for the app. I checked the backend today and noticed he’s actually gotten a few paying users and made $430 in revenue. Small numbers, but interesting considering no major marketing.\n Now the guy wants me to come on as CTO and double down on development. I'm honestly torn.\n On one hand, I already got paid for the original work, and I'm usually heads-down on freelance gigs that pay the bills. On the other hand… I have this proposal from his end with equity.\n Would love to hear thoughts from others who’ve been in a similar situation. When do you decide to go from “freelancer for hire” to “I guess I’m a cofounder now”?",
"I am sure the answer is I’ll be fine, but I’ve been building out an idea I was super happy about. But then seems like YC funded a competitor within the last couple batches. They’re not direct, but in the same small space. What are my chances here - how can I answer how I’m different from competitors?",
"I have recently been hired as an investor relations intern at a startup. They are asking me to pitch the company to VCs without much instruction. I want to cold email/message analysts and interns on LinkedIn, get in good with them, and eventually schedule a call with partners. What materials should I prepare for those meetings?",
"Hey all!\n Since our inception as a company we’ve all used ai pretty extensively as a leverage multiplier.\n It’s (generally) worked great - but we are all very very experienced at what we do, so catching hallucinations/ proper prompting / direction has never been an issue.\n A couple of months ago we finalized a round and did some hiring.\n Yesterday, production crashed because some ai code that looked good enough to pass through our internal code review process got deployed.\n Obviously there are things to tighten up outside of an AI SOP, but certainly as we continue to expand, issues like this are going to continue to come up.\n Anybody in a similar situation?",
"There are plenty of articles about how to split equity in a startup. For example, setting up vesting schedules, vesting cliffs, employee equity plans, etc.\n This seems geared towards traditional startups: one to a few full time founders who hire full time employees after raising their pre-seed round, etc.\n What about startups who are shooting for an unorthodox approach. Example: something like an open-sourced model with many part time contributors and a monetization strategy, but where the contributors are ultimately compensated with equity? There are many small investors who are product champions vs. institutional investors.\n How would you provide equity in a situation like this? Would piggybacking off of a crowdsourcing platform make sense? If so, which ones? It doesn't seem that they are really designed for something like this.",
"My last role was as a pre-sales solutions architect, have years of experience and was handling strategic accounts US-West, that means I spent 50% of my time coding, doing architecture design reviews and general technical stuff while the remaining 50% was sales, building champions, user interviews, scoping, qualifying and even pipeline generation.\n I feel like I am technical enough that I can build tools from ground up with the help of coding tools and I can also take care of sales when I am not coding at least in the initial phase.\n Like many others I am building in Enterprise AI and the people(ex-colleagues, friends etc) who believe in my vision are also building stuff and working on their ideas and people who are ready to work with me dont have the tools required and complement my skillset so I figured its better to work alone that having an eventual break up\n For anyone interested I am working on a tool which turns any website into an MCP server!",
"Questions to small successful teams that operate in fast-moving environment. How do you deal with setting goals/OKRs?\n Are your goals super-aggressive and hard to achieve or rather more reachable?\n Do you discuss OKRs within whole team (dev/product and business together) or separately? How long does it take to decide on goals?\n Do you have weekly OKRs too? Do you discuss it with whole team?\n Plus - Do you organize daily? Is it for whole team (dev/product and business together) or separetely?\n Asking how to do that effectively when we have small team, want to be super effective and everything is changing so fast",
"I’m a non-technical solo founder working on a two-sided marketplace in the creator economy. It targets a large and growing pain point for both sides of the market, and I’ve validated a strong emotional pull around the problem.\n I’m planning to apply to YC but I don’t have a tech cofounder (yet), and the product is still pre-MVP. I’ve been focused on user research, story building, and market insights. Monetization is clear, and I have a plan for early traction, but no product built yet.\n I know YC prefers teams and early traction — but I believe this is a genuinely large opportunity with a strong narrative.\nAnyone here have experience applying solo, pre-product?\n How much does not having a technical cofounder hurt?\n How do I best frame my application to highlight the opportunity and my strengths?\n Any tips for making the video stand out?\n Appreciate any honest advice.",
"Hi guys,\n I started working on an ai automation/ workflow product together with 2 others almost 4w ago.\n What started with a cool idea on how to make our own life's easier pretty much turned quite quickly in a product that can solve a lot of people their problems.\n If done correctly we can solve most businesses their automation requests in just natural language.\n We have had quite some interests from different professional fields already.\n i kind have this gut feeling we have something different here, i have worked on 6 business startups ideas before, most of them never scaled besides my last try. And this one just feels different in potential. Like i know we can do it.\n So how do you kind of deal with the performance anxiety?\n Like currently the imposter syndrome is just creeping in since i know we made something amazing. But execution on this is going to be very important in going to market etc.\n I know that its all about going to market and how to market / sale it. Knowing that we have a good product just makes me feel uneasy since i think this is going to turn into something quite serious quickly for us.\n Any advice's would be really appreciated !",
"My cofounder and I vibe code with lovable, cursor, firebase studio. We have GCP credits from Google. We acknowledge vibe coding isn’t enough to be prod ready. Advise welcome. TIA",
"I am not a YC but I heard this question in a podcast from an other YC grad. I loved it! and I'm curious to hear your answers.",
"Hi all,\n We’re currently working with a former CEO of a company that we hope to sell to. He’s already made valuable introductions and is helping us navigate early conversations (moderate intent so far). We’ve had three meetings with him and would like to keep him engaged as an advisor.\n However, he hasn’t asked for anything in return so far. I’d like your advice:\n Should we offer him the opportunity to angel invest in our round (perhaps at a discount)?\n Or should we offer some equity outright as an advisory grant?\n Is there a typical structure you use for this kind of lightweight engagement?\n Any best practices for nurturing advisor relationships early on?\n He may not become a major game-changer, but he’s clearly helpful and credible. I want to handle this professionally without over- or under-committing.\n Thanks in advance for any guidance!",
"Hey everyone :)\n Super pumped to be heading to YC’s AI Startup School in San Francisco (June 16–17). I’ve heard a bunch of student founders are gonna be there, so I figured, t’d be cool to get a groupchat going!\n Idea is to make it easier to meet up before/after the events, plan some hangouts, and just connect with other builders who are in town.\n If you're going (or will be in SF that weekend), I made a LinkedIn Post, drop a comment there and I’ll DM you the GC link or just dm me here on Reddit :)https://www.linkedin.com/posts/harsha-not-hiring-gaddipati-032bb820a_whos-heading-to-yc-ai-startup-school-in-activity-7330238089426063361-fEAT\n So excited for June!!!!",
"Hey all — I’m looking to level up on product-led growth and would love to tap into this community’s wisdom.\n What are the best books, essays, or frameworks you’ve found most helpful for truly understanding and executing PLG? I’m especially interested in tactical advice or stories from early-stage founders, particularly in B2B SaaS and AI infrastructure — but open to anything insightful.\n Big thanks in advance — happy to compile and share a summary here if there’s interest.",
"The recent layoffs of folks working on CPython and the TypeScript compiler have been sitting heavily with me—not because those engineers weren’t brilliant, but because their roles didn’t translate into enough real-world value (at least from their employers' perspectives).\n It brings up a few uncomfortable questions I wanted to throw out to this community:\nDeep Technical Expertise vs. Delivering Value\n These teams were working on the core infrastructure of tools used by millions of developers daily. Yet they were let go. Why?\n Their work didn’t drive clear, short-term business outcomes.\n The tools are already “good enough” for most use cases.\n Optimization beyond this point didn’t move key metrics.\n If you’re not building product or directly improving revenue/user experience, is it just too easy to be seen as \"non-essential\"?\n“Use Boring Tech” Principle Hits Different Now\n YC has always advised founders to:\n Use boring, proven tools.\n Avoid over-engineering.\n Focus on delivering value fast.",
"The idea I'm working on right now is pretty closely tied to a few active state bills, so I’ve been way more aware of policy/regulation than I have in past projects.\n For those of you in similar spots or in heavily regulated spaces, do you track legislation, work with a policy person/lobbying firm of some sort, or just deal with things as they come up?\n Curious how other early-stage teams handle this without it becoming a full-time job. It’s just me and my cofounder so we’re not trying to get too deep into it.",
"Hi all, I’d love some real feedback on my AI agent demo. I'm building a smart real estate ai agent in Arabic (specifically Egyptian dialect). The goal is to help users find properties by having a natural conversation — budget, location, needs, suggestions, etc. and closing deals\n What I Tried So Far:\n I first tried no-code tools like Voiceflow, but they were too limited and not smart enough for multi-turn logic.it was a generic chatbot and just wanted to see the workflow\n Then I tried building the entire thing offline in Python — full state management, memory, reasoning, rules, CSV property data, and response templates. It works, but it’s still rigid and not truly \"chatbot smart.\" And yes have to feed it messages related to the keywords in the ai logic\n I moved to Colab and integrated open-source models like Yehia-7B, DeepSeek, Meraj-Mini, etc. Some were too large for free-tier, others didn't respond naturally in Egyptian dialect or ignored the character prompt. I can’t afford GPT-4/ChatGPT API, and I have no proprietary data.\n So here’s my current setup:\n I’m going to record a full demo video of a “real” chat.\n The user prompts will be pre-written (scripted input).\n The AI agent’s answers will also be scripted (pre-written responses injected manually).\n I’ll use Gradio to simulate a real UI and type the demo lines live if needed.\n My Questions:\n Is this kind of demo good enough to show investors?\n I’m honest that it’s scripted.\n The backend code is real (the agent logic exists, it's just not fully AI-driven without good models).\n I just don’t have the specs, funds, or model power to run LLMs properly now.\n I don’t have real customer data to fine-tune.\n Is this smart bootstrapping or just over-engineering?\n Would you be convinced if you saw this demo video or tried it live with scripted responses behind the scenes?",
"I run a service that uses AI to handle 95% of user interactions successfully. However, we've noticed that 75% of our exceptions come from users who expect our service to be fully responsible for their outcomes, even when they make mistakes or don't follow instructions.\n For example, users will blame the AI when they input incorrect information or skip reading important setup instructions, despite clear guidance being provided.\n We've improved our UX flows and created specialized AI agents for common issues, but we can't anticipate every edge case, and our price point doesn't support extensive human intervention.\n I've noticed these issues often come from users who:\n Have high control needs\n Want to dictate specific solutions\n Expect us to make their prescribed approach work\n Struggle with following sequential instructions\n Three specific challenges:\n Our AI isn't assertive enough with these difficult users\n The AI underestimates the probability of user error/confusion\n The users are not our customers, but they are the customers of our customers. So we don't get to choose them.\nQuestions:\n Has anyone developed effective messaging that sets appropriate service expectations for AI-delivered services?\n How do you communicate limitations without saying \"you're on your own if something goes wrong\"?\n What techniques help AI systems think more critically about user-reported issues (e.g., \"75% of wifi problems are password errors\") without becoming dismissive of legitimate problems?",
"Bit of an unusual situation.\n I've identified a real pain point amongst researchers within academic publishing and a software/web app solution that would address them.\n I have prior experience in small startups and brand name startups prior to starting my PhD, and from that time I recall investors want you to be full time on the venture.\n However, I'm not as sure this applies in my unusual situation.\n Below is a list of context points why I think it might make more sense to do this part time and am wondering how I might raise money for this.\n the tool being built is an alternative platform to academic publishing meant to compete against open access and private journals by providing quality control mechanisms while monetizing rich statistics and AI training data. It is far easier to talk and convince academics to try this if I am also within academia and have academic credentials. Academics are going to be more skeptical of my credentials if I drop out of PhD to work on this.\n the R1 university I'm in has a interdisciplinary project funding program and this idea was judged by a panel of faculty to be very high potential for societal impact. As a result, it won a small grant that's enough to cover travel an tool expenses for the team. In addition, this also allows students here work on it for academic credit, giving access to very part time (10hrs/week) but talented labor. This would disappear if I left academia to do this full time.\n There are multiple people on the team right now who are faculty that can only commit part time.\n Given the above, does it make sense to try raising from VCs? What kind of VCs go for situations like this if any? Am I correct in my assessment that I would actually have a higher chance of pulling this off remaining in PhD and working on this part time with university resources instead of dropping out and going full time on this?",
"I've been noticing that a growing number of YC startups are integrating RAGs in one form or another into their products—especially in SaaS tools that involve search, documentation, or support automation mainly in the B2B space\n Curious to know:\n Are most of these startups building their own RAG pipelines (e.g. custom vector databases, chunking strategies, ranking logic)?\n Or are they relying on third-party platforms like Vectara, LlamaIndex, Azure Search AI, etc.?\n Also, any insights on what pushed you toward one approach over the other. More concretely I am not getting the results I am looking for with a custom pipeline that I have built. And finetuning it is taking a lot longer than I expected to.",
"Hey everyone, We're starting to land some bigger clients in the FinTech space. We haven’t raised any money, but we’ve reached the point where compliance and business insurance are becoming necessary. A SOC 2 audit alone might cost more than the entire value of a 1-year contract — and that’s not even counting insurance and other requirements. How do other bootstrapped startups handle this? We've told the client we're in the process of getting these in place, but would love to hear how others have navigated this phase.",
"Hi, super noob founder here. We’re seeing that people are responding to our outbound and actually booking calls. For bigger companies (500-1k headcount), we’d like to quote 50-85k. We’re building browser agents for e2e testing and this price is usually based on how “big” their product is.\n However, we’d also like to fundraise. So closing deals fast so that we can show revenue is a priority for us.\n My question is, how long does it usually take for u as a founder to close deals where the customer is paying around 50-85k.",
"Have any founders here been able to get super-voting shares in their company? How did you pull it off? When did you institute it? Preseed, Seed etc. How did you justify it to investors? Any comment on the subject you would like to add to share would be greatly appreciated.",
"Anytime I see a headline of some iconic name investing in a technology company like:\n \"Howard Schultz (Starbucks CEO) invests in Wiz\"\"Bernard Arnault (LVMH) invests in AirBnB\"\n I imagine it's allocators at their family office heavily involved in the decision making, vetting, due diligence, etc...\n With that, how much involvement does the actual principal owner of the family office have?\n Like are Bernard Arnault/Howard Schultz/etc... literally unaware of the allocation until it appears as a line item on the funds holdings? Do they even meet with the founders at least once before closing out as a formality?",
"Obviously it would be MIT license and appropriately designated in said app docs, etc. However I am wondering if there are any issues with this approach with essentially building on top of open source software, primarily for the MVP stage? I assume 90% of the code being spit out of Cursor is open source =] But I wanted to see if YC has funded companies approaching their initial product(s) with this strategy? Anything I should be aware of? If anyone has experience building on top of open source software I would appreciate hearing from you"
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Long site/list
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"NEA",
"Necessary Ventures",
"Neo",
"Neotribe Ventures",
"Netflix",
"New Wave VC",
"Newion",
"Next Play Ventures",
"Next Ventures",
"Next47",
"Nexus Venture Partners",
"NFDG Ventures",
"NFX",
"Northzone",
"Norwest Venture Partners",
"Notable Capital",
"Notion Capital",
"NVentures (Nvidia)",
"O'Shaughnessy Ventures",
"Oak HC/FT",
"Obvious Ventures",
"Octave",
"Octopus Ventures",
"Offline Ventures",
"Okta Ventures",
"Oliver Jung",
"ONEVC",
"OpenAI Startup Fund",
"OpenView",
"Operator Collective",
"Operator Partners",
"Oregon Venture Fund",
"Origin Ventures",
"Original Capital"
]
}
}
JigsawStack
{
"page_position": 1,
"page_position_length": 5,
"context": {
"listing_names": [
"01 Advisors",
"1984 Ventures",
"20SALES",
"20VC",
"42CAP",
"468 Capital",
"500 Global",
"53 Stations",
"62 Ventures",
"8090 Industries",
"83North",
"8VC",
"A*",
"a16z",
"Abstract Ventures",
"Accel",
"Accenture Ventures",
"Accomplice VC",
"ACME",
"Acrew Capital",
"Activant Capital",
"Active Capital",
"Adams Street Partners",
"Addition",
"Adjacent",
"Adobe Ventures",
"Adverb Ventures",
"Afore Capital",
"Aglaé Ventures",
"AI Grant",
"Align Ventures",
"Alkeon Capital",
"AlleyCorp",
"Alpaca VC",
"Alpha Square Group",
"Alt Capital",
"AltaiR Capital",
"Altimeter Capital",
"Altos Ventures",
"Alumni Ventures",
"Alven",
"Amazon",
"AMD",
"Amplify Partners",
"Anthos Capital",
"Array VC",
"Atlassian Ventures",
"Atomic",
"Atomico",
"Audacious Ventures",
"Avenir",
"Avid Ventures",
"Axeleo Capital",
"Backstage Capital",
"Bain Capital Ventures",
"Balderton Capital",
"Base10 Partners",
"basecase capital",
"Baseline Ventures",
"Basis Set Ventures",
"Battery Ventures",
"Bedrock Capital",
"Benchmark",
"Benhamou Global Ventures",
"Bessemer Venture Partners",
"Betaworks Ventures",
"Better Tomorrow Ventures",
"Bezos Expeditions",
"BFG Partners",
"BGZ",
"BITKRAFT",
"Blackbird",
"BlackRock",
"Blackstone",
"Blank Ventures",
"Bling Capital",
"Blitzscaling Ventures",
"Bloomberg Beta",
"Blossom Capital",
"Blume Ventures",
"boldstart ventures",
"BOND Capital",
"BoxGroup",
"Breega",
"Broadhaven Ventures",
"Bungalow Capital",
"Butterfly VC",
"Caffeinated Capital",
"Cambrian",
"Canaan Partners",
"Canapi Ventures",
"Canvas Ventures",
"CapitalG",
"Cathay Innovation",
"Charge Ventures",
"Cherry Ventures",
"Cintrifuse",
"Citi Ventures",
"City Light Capital",
"Clocktower Ventures",
"Coatue",
"Coefficient Capital",
"Collaborative Fund",
"Commerce Ventures",
"CommerzVentures",
"Company Ventures",
"Companyon Ventures",
"Connect Ventures",
"Construct Capital",
"Contrary Capital",
"Conversion Capital",
"Conviction Capital",
"Correlation Ventures",
"Cortado Ventures",
"Costanoa Ventures",
"Courtside Ventures",
"Cowboy Ventures",
"Craft Ventures",
"Crane Venture Partners",
"Creandum",
"Cross Creek",
"CrowdStrike Ventures",
"CRV",
"Cursor Capital",
"D1 Capital Partners",
"Daring Ventures",
"Day One Ventures",
"Decent Capital",
"Decibel Partners",
"Deciens Capital",
"Defined Capital",
"Definition",
"defy.vc",
"Designer Fund",
"DFJ Growth",
"DG Daiwa Ventures",
"Distributed Global",
"Distributed Ventures",
"DivcoWest",
"Dragonfly",
"Drive Capital",
"Dropbox Ventures",
"DST Global",
"DVC",
"e& capital",
"Earlybird VC",
"EBRD VC",
"Eclipse",
"Educapital",
"Eight Roads",
"Elad Gil",
"Elevation Capital",
"Emblem",
"Emergence Capital",
"Energy Impact Partners",
"Eniac Ventures",
"Entrée Capital",
"Epic Ventures",
"EQT Ventures",
"Equal Ventures",
"Essence VC",
"Evolution Equity Partners",
"Expa",
"Exponent",
"F-Prime Capital",
"F4 Fund",
"Felicis",
"Fidelity International Strategic Ventures",
"Fifth Down Capital",
"Fifth Wall",
"Fin Capital",
"FinTech Collective",
"Firestreak Ventures",
"First Round Capital",
"First Spark Ventures",
"FirstMark",
"Firstminute Capital",
"FJ Labs",
"Floodgate",
"Flourish Ventures",
"Flume Ventures",
"Flybridge",
"Footwork VC",
"Forerunner Ventures",
"Foundation Capital",
"Founders",
"Founders Fund",
"Founders Inc.",
"Foundry",
"Framework Ventures",
"Friends & Family Capital",
"Frontline Ventures",
"FundersClub",
"Future Positive",
"Future Ventures",
"G Squared",
"Galaxy Ventures",
"Garage",
"Garuda Ventures",
"General Atlantic",
"General Catalyst",
"Geodesic Capital",
"Georgian",
"Glade Brook Capital",
"Glilot Capital Partners",
"Goldman Sachs",
"Goodwater Capital",
"Gradient Ventures",
"Grand Ventures",
"GreatPoint Ventures",
"Greenfield Partners",
"Greenoaks",
"Greycroft",
"Greylock",
"Grid Capital",
"GV",
"Hack VC",
"Harlem Capital",
"Harpoon Ventures",
"Haun Ventures",
"Hawke Ventures",
"Haystack Ventures",
"Headline",
"Heartcore Capital",
"Heavybit",
"Hedosophia",
"HF0",
"High Alpha",
"Highland Capital Partners",
"Highland Europe",
"HOF Capital",
"Homebrew",
"Horizons Ventures",
"HubSpot Ventures",
"Human Capital",
"Human Ventures",
"Hummingbird VC",
"Hustle Fund",
"HV Capital",
"Hyphen Partners",
"Icon Ventures",
"ICONIQ Growth",
"IDC Ventures",
"Incore",
"Index Ventures",
"Indico Capital Partners",
"Industry Ventures",
"Infinity Ventures",
"Initialized Capital",
"Innovation Endeavors",
"Inovia Capital",
"Inovo VC",
"Insight Partners",
"Inspired Capital",
"Intel Capital",
"Irregular Expressions",
"IVP",
"J.P. Morgan",
"Javelin Venture Partners",
"Karman Ventures",
"Khosla Ventures",
"Kickstart Fund",
"Kin Ventures",
"Kindred Ventures",
"Kleiner Perkins",
"Koch Investments",
"Korelya Capital",
"KT",
"L Catterton",
"Lachy Groom",
"Lakestar",
"Latitude Capital",
"Laude Ventures",
"Lead Edge Capital",
"Leadout Capital",
"Left Lane Capital",
"Lerer Hippeau",
"LifeX Ventures",
"Lightspeed",
"Liquid 2 Ventures",
"LiveOak Ventures",
"Lobby Capital",
"LocalGlobe",
"Lone Pine Capital",
"Long Journey Ventures",
"Look Up Ventures",
"Lorimer Ventures",
"Lowercarbon Capital",
"Lunar Ventures",
"Lux Capital",
"M12",
"M13",
"Madrona",
"Mango Capital",
"Mantis VC",
"Matchstick Ventures",
"Matrix Partners",
"Maven Ventures",
"Mayfield Fund",
"Menlo Ventures",
"Mercury Fund",
"Meritech Capital",
"MHS Capital",
"Microsoft",
"Moderne Ventures",
"Molten Ventures",
"Monogram Capital Partners",
"Mosaic Ventures",
"Motivate Venture Capital",
"Motive Ventures",
"Motley Fool Ventures",
"Mouro Capital",
"Move Capital",
"Multicoin Capital",
"MVP Ventures",
"Mythos Ventures",
"NAP VC",
"Navitas Capital",
"NEA",
"Necessary Ventures",
"Neo",
"Neotribe Ventures",
"Netflix",
"New Wave VC",
"Newion",
"Next Play Ventures",
"Next Ventures",
"Next47",
"Nexus Venture Partners",
"NFDG Ventures",
"NFX",
"Northzone",
"Norwest Venture Partners",
"Notable Capital",
"Notion Capital",
"NVentures (Nvidia)",
"O'Shaughnessy Ventures",
"Oak HC/FT",
"Obvious Ventures",
"Octave",
"Octopus Ventures",
"Offline Ventures",
"Okta Ventures",
"Oliver Jung",
"ONEVC",
"OpenAI Startup Fund",
"OpenView",
"Operator Collective",
"Operator Partners",
"Oregon Venture Fund",
"Origin Ventures",
"Original Capital",
"OSS Capital",
"OTB Ventures",
"Outset Capital",
"Outsiders Fund",
"Pace Capital",
"Pale blue dot",
"Panache Ventures",
"Pantera Capital",
"Paradigm",
"Parkway Venture Capital",
"Partech",
"Passion Capital",
"Peak XV",
"PeakSpan Capital",
"Pear VC",
"pebblebed",
"Pelion Venture Partners",
"PHX Ventures",
"Picus Capital",
"Pillar VC",
"Pioneer Fund",
"Plural",
"Point Nine",
"Point72 Ventures",
"Polaris Partners",
"Polychain Capital",
"Portage",
"Powerhouse Ventures",
"Precursor Ventures",
"Premji Invest",
"Preston-Werner Ventures",
"Primary",
"Project A",
"Prometheus Fund",
"Prosus Ventures",
"Pruven Capital",
"Prysm Capital",
"QED",
"Quad Partners",
"Quadrille Capital",
"Quiet Capital",
"Race Capital",
"Radical Ventures",
"Reach Capital",
"Rebel Fund",
"Rebellion Ventures",
"Redpoint Ventures",
"Renegade Partners",
"Ribbit Capital",
"Ridge Ventures",
"Riot Ventures",
"Ritual Capital",
"Robot Ventures",
"Roche Venture Fund",
"Rogue Capital",
"Root Ventures",
"RSquared VC",
"RTP Global",
"Rubio Impact Ventures",
"S32",
"Saga Ventures",
"Sam Altman",
"Sapphire Ventures",
"Scale Venture Partners",
"SciFi VC",
"ScOp Venture Capital",
"Scribble Ventures",
"Script Capital",
"Seedcamp",
"SemperVirens",
"Sequoia",
"Seven Seven Six",
"SHAKTI",
"Shield Capital",
"Shinhan Venture Investment",
"Shopify Ventures",
"SIERRA Ventures",
"SignalFire",
"Silas Capital",
"Silicon Catalyst",
"Singular VC",
"Slow Ventures",
"SNR",
"Socii Capital",
"SoftBank Vision Fund",
"Soma Capital",
"Sorenson Capital",
"Sound Ventures",
"South Park Commons",
"Sozo Ventures",
"Spark Capital",
"Speedinvest",
"Sprints Capital",
"Square Peg",
"Stage 2 Capital",
"StageOne Ventures",
"Starship Ventures",
"Steadview Capital",
"Stellation Capital",
"StepStone Group",
"Sterling Road",
"Streamlined Ventures",
"Stripe",
"Stripes",
"Supernode Global",
"Surface Ventures",
"SuRo Capital",
"Susa Ventures",
"SV Angel",
"Sweater",
"Tandem Venture Partners",
"Target Global",
"Team Ignite Ventures",
"Telescope Partners",
"Temasek",
"Terrain",
"The General Partnership",
"The Syndicate",
"Theory Ventures",
"Think + Ventures",
"Third Kind Venture Capital",
"Third Point Ventures",
"Third Prime",
"Thoma Bravo",
"Threshold Ventures",
"Thrive Capital",
"Tiger Global Management",
"Titanium Ventures",
"Together Fund",
"Tola Capital",
"Topology Ventures",
"TQ Ventures",
"Treble Capital",
"Tribe Capital",
"True Ventures",
"Trust Ventures",
"TSIC",
"Twenty Two",
"Two Sigma Ventures",
"Uncork Capital",
"Uncorrelated Ventures",
"Underscore VC",
"Union Square Ventures",
"Unusual Ventures",
"Upfront Ventures",
"UpHonest Capital",
"Valor Equity Partners",
"Venrex",
"Venrock",
"Vesey Ventures",
"Vinyl Capital",
"Visionaries Club",
"VMG Partners",
"Vy Capital",
"Wa'ed Ventures",
"Wayfinder Ventures",
"Weekend Fund",
"Whitecap Venture Partners",
"Wikus Ventures",
"Wing VC",
"Wireframe VC",
"Wisdom Ventures",
"WndrCo",
"Workday Ventures",
"World Innovation Lab",
"XAnge",
"XTX Ventures",
"XYZ",
"Y Combinator",
"Zeev Ventures",
"Zeno Partners",
"Zigg Capital",
"Zinal Growth"
]
},
"selectors": {
"listing_names": [
"a.framer-sb9jpt .framer-yo1eai p.framer-text.framer-styles-preset-1lagf8y",
"a.framer-sb9jpt .framer-yo1eai",
"a.framer-sb9jpt p.framer-text.framer-styles-preset-1lagf8y",
"a.framer-sb9jpt .framer-yo1eai > p",
"a.framer-sb9jpt p.framer-text"
]
}
}
Firecrawl scraped the initial section of the site but failed to capture the full content, which required scrolling. JigsawStack automatically handled scrolling and extracted the complete data accurately, with no cutoffs or missing sections.
Comparison script we ran
Conclusion
The comparison showed that JigsawStack outperformed Firecrawl in the majority of tests. Firecrawl relies heavily on LLMs like GPT-4, which can produce errors, hallucinations, and is limited by token constraints. JigsawStack, on the other hand, uses a custom trained model that mimics the steps a developer would take when scraping a site, from inspecting network logs to using CSS selectors. This results in higher quality data and greater reliability.
Firecrawl vs JigsawStack AI Scraper
◐ = partial ❌ = inaccurate/fails ✅ = accurate/succeeds
| Feature / Goal | Firecrawl | JigsawStack AI Scraper |
| 💽 Accurate data extractions | Extracted data correctly from 1 out of 6 websites ❌ | Extracted data from all tested sites accurately, following the expected schema ✅ |
| ❤️🩹 Automatic error handling | Frequently threw errors or returned false positives when encountering blocked sites ❌ | Automatically handles errors, retries when needed, and unblocks sites to extract complete data ✅ |
| 🔁 Auto unblocker | Blocked on all protected sites, even with proxy and stealth mode enabled ❌ | Successfully unblocked every site tested, including complex ones like LinkedIn and Reddit ✅ |
| ♾️ Fully managed scale | Limited to 5 concurrent browsers on Hobby plan ($16/month) and 50 on Standard plan ($83/month) ❌ | Supports over 10,000 concurrent browser sessions. Fully managed with no limits and usage-based pricing ✅ |
| 🧠 Smart actions (scrolling, etc.) | Does not automatically scroll to load dynamic content. Only partial page data is scraped ❌ | Automatically scrolls, detects dynamic content, and extracts all relevant values without user input ✅ |
| 🌐 Proxies and IP rotation | Proxy feature failed to prevent blocking. Still flagged by bot detectors even in stealth mode ❌ | Rarely needs proxies. When needed, it uses a built-in rotating proxy system that bypasses even Cloudflare bot checks. ✅ |
| 🧑💻 Developer control | No support for advanced configuration such as custom CSS selectors, browser dimensions, or headers ❌ | Offers full developer control, including custom CSS selectors, browser size, custom cookies, proxy support, and Puppeteer-level configuration options ✅ |
How to get started with JigsawStack AI Scraper
Get API here: https://jigsawstack.com/ai-web-scraper
const jigsaw = JigsawStack({
apiKey: "your-api-key",
});
const result = await jigsaw.web.ai_scrape({
url: "https://news.ycombinator.com",
element_prompts: ["post_titles", "post_points", "post_username"],
});
console.log(result);
