Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

Most engineering metrics are broken. They count PRs and commits, not real impact. Developer 360 from CodeAnt AI (YC W24) changes that. Built on top of their AI code reviews, it shows what’s actually being built, fixed, or improved— with real visibility into engineering work.

Y Combinator

1,620,464 subscribers

16,430 görüntüleme • 10 ay önce •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Engineering teams have a secret: most still use metrics like lines of code to judge their teams. Weave (YC W25) built a better option: an AI agent that accurately measures engineering output & quality. Congrats on the launch, Adam Cohen + Andrew!

Engineering teams have a secret: most still use metrics like lines of code to judge their teams. Weave (YC W25) built a better option: an AI agent that accurately measures engineering output & quality. Congrats on the launch, Adam Cohen + Andrew!

Y Combinator

25,403 görüntüleme • 1 yıl önce

30% of code at top tech companies is now AI-generated. Most engineering leaders have no idea what that means for speed, quality, or ROI. Nivara ( gives them visibility into how humans and AI build together. The future of engineering is hybrid.

30% of code at top tech companies is now AI-generated. Most engineering leaders have no idea what that means for speed, quality, or ROI. Nivara ( gives them visibility into how humans and AI build together. The future of engineering is hybrid.

Y Combinator

26,681 görüntüleme • 9 ay önce

Traditional coding benchmarks do not reflect how software is actually built and maintained. That's why we built a new benchmark, APEX-SWE, in partnership with Cognition. It measures whether AI models can perform complex, real-world software engineering work to ship systems that work and debug them when they don't. OpenAI GPT 5.3 Codex (High) tops the leaderboard at 41.5% on Pass@1.

Traditional coding benchmarks do not reflect how software is actually built and maintained. That's why we built a new benchmark, APEX-SWE, in partnership with Cognition. It measures whether AI models can perform complex, real-world software engineering work to ship systems that work and debug them when they don't. OpenAI GPT 5.3 Codex (High) tops the leaderboard at 41.5% on Pass@1.

adarsh

216,227 görüntüleme • 4 ay önce

GStack is an open-source toolkit built by YC President & CEO Garry Tan that turns Claude Code into an AI engineering team — with skills for office hours, design, code review, QA, and browser testing. In this video, Garry walks through how GStack works, starting with Office Hours, a skill modeled after real YC partner sessions that pressure-tests your idea before you write a line of code. He demos it live, going from idea through adversarial review, design mockups, and automated QA in a single session.

GStack is an open-source toolkit built by YC President & CEO Garry Tan that turns Claude Code into an AI engineering team — with skills for office hours, design, code review, QA, and browser testing. In this video, Garry walks through how GStack works, starting with Office Hours, a skill modeled after real YC partner sessions that pressure-tests your idea before you write a line of code. He demos it live, going from idea through adversarial review, design mockups, and automated QA in a single session.

Y Combinator

924,363 görüntüleme • 3 ay önce

.InspectMind AI (YC W24)'s AI agent reviews construction drawings, specs, and building codes to catch issues before they turn into rework, delays, or lawsuits. It flags dimension errors, materials mismatches, code violations, and coordination gaps across architectural, structural, civil, and MEP drawings. On one $100M job, it caught a materials mismatch that saved the general contractor $2M.

.InspectMind AI (YC W24)'s AI agent reviews construction drawings, specs, and building codes to catch issues before they turn into rework, delays, or lawsuits. It flags dimension errors, materials mismatches, code violations, and coordination gaps across architectural, structural, civil, and MEP drawings. On one $100M job, it caught a materials mismatch that saved the general contractor $2M.

Y Combinator

19,218 görüntüleme • 8 ay önce

While we are at Prometheus, there are reports that Jeff Bezos is creating an AI startup called ‘Project Prometheus’ that has amassed $6 billion and aims to develop AI capable of engineering, manufacturing, and real-world physical systems, not just chatbots or purely online software. They are building their guards and workers for their doomsday bunkers!

While we are at Prometheus, there are reports that Jeff Bezos is creating an AI startup called ‘Project Prometheus’ that has amassed $6 billion and aims to develop AI capable of engineering, manufacturing, and real-world physical systems, not just chatbots or purely online software. They are building their guards and workers for their doomsday bunkers!

Open Minded Approach

29,947 görüntüleme • 9 ay önce

CONTEXT ENGINEERING > PROMPT ENGINEERING Everyone is obsessed with writing better prompts. The next generation of AI builders is focused on context engineering instead. • Prompt engineering shapes the question. Context engineering shapes everything the AI sees. • Great prompts can't save an agent missing critical context, memory, or tools. • AI failures often come from missing information, not weak models. • Context engineering combines prompts, memory, RAG, state management, and tool access into one system. What powers effective AI agents? → Memory: Remembers preferences, past interactions, and ongoing tasks. → State Management: Tracks progress across multi-step workflows. → RAG: Retrieves only the most relevant information when needed. → Tools: Connects AI to APIs, databases, code execution, and real-world actions. → Dynamic Prompts: Enriches instructions with live context at runtime. The key insight: Prompt Engineering = Better Questions Context Engineering = Better Systems The future of AI isn't building smarter prompts. It's building smarter environments for AI to think, remember, retrieve, and act.

CONTEXT ENGINEERING > PROMPT ENGINEERING Everyone is obsessed with writing better prompts. The next generation of AI builders is focused on context engineering instead. • Prompt engineering shapes the question. Context engineering shapes everything the AI sees. • Great prompts can't save an agent missing critical context, memory, or tools. • AI failures often come from missing information, not weak models. • Context engineering combines prompts, memory, RAG, state management, and tool access into one system. What powers effective AI agents? → Memory: Remembers preferences, past interactions, and ongoing tasks. → State Management: Tracks progress across multi-step workflows. → RAG: Retrieves only the most relevant information when needed. → Tools: Connects AI to APIs, databases, code execution, and real-world actions. → Dynamic Prompts: Enriches instructions with live context at runtime. The key insight: Prompt Engineering = Better Questions Context Engineering = Better Systems The future of AI isn't building smarter prompts. It's building smarter environments for AI to think, remember, retrieve, and act.

Dami-Defi

10,127 görüntüleme • 2 ay önce

ANTHROPIC'S HEAD OF ENGINEERING SAYS THEY JUST SHIPPED THE MOST CAPABLE MODELS THEY HAVE EVER BUILT Mythos 5 and Fable 5. Fable 5 can run for days on a single goal and get it right on the first pass, on work that used to need an entire team. Most people use AI to summarize things. The real leverage is the long autonomous task you keep putting off.

ANTHROPIC'S HEAD OF ENGINEERING SAYS THEY JUST SHIPPED THE MOST CAPABLE MODELS THEY HAVE EVER BUILT Mythos 5 and Fable 5. Fable 5 can run for days on a single goal and get it right on the first pass, on work that used to need an entire team. Most people use AI to summarize things. The real leverage is the long autonomous task you keep putting off.

0xMarioNawfal

57,127 görüntüleme • 2 ay önce

We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.

We've built a massive verification bottleneck: • 72% of developers use AI to generate code every day • 96% of them don't fully trust it Writing code is now free. All the work now is verifying that the code does what it's supposed to. According to a new State of Code Survey, almost half of the respondents believe the number one skill that will matter most in the coming years is "reviewing and validating AI-generated code for quality and security". Not prompt engineering or vibe-coding, but checking AI's work.

Santiago

16,299 görüntüleme • 7 ay önce

Users state the goal. xBubble handles the building path. With Bubble Code, xBubble helps users create different kinds of Code AI Agents & AI roducts. The key is not just generating a prototype. Bubble Code is built to turn user goals into ready-to-use products with real interfaces, logic, integrations, and deployment paths. AI products should not stop at a mockup. With xBubble, they can be built, deployed, and used directly.

Users state the goal. xBubble handles the building path. With Bubble Code, xBubble helps users create different kinds of Code AI Agents & AI roducts. The key is not just generating a prototype. Bubble Code is built to turn user goals into ready-to-use products with real interfaces, logic, integrations, and deployment paths. AI products should not stop at a mockup. With xBubble, they can be built, deployed, and used directly.

DAPPOS

96,529 görüntüleme • 1 ay önce

Developers won’t like this…😭 But 90% of “AI agents” we’ve been hyping are basically unstable interns with amnesia. They hallucinate. They loop. They forget instructions. A tiny 11-person team from Sweden just fixed ALL of it. Meet the first AI agent engine that actually works: Link : AI agents just entered their real era.

Developers won’t like this…😭 But 90% of “AI agents” we’ve been hyping are basically unstable interns with amnesia. They hallucinate. They loop. They forget instructions. A tiny 11-person team from Sweden just fixed ALL of it. Meet the first AI agent engine that actually works: Link : AI agents just entered their real era.

Shruti Codes

41,182 görüntüleme • 8 ay önce

Nobody cares that you process 2B tokens. That’s not a flex, it’s a bill. Introducing Entelligence AI Agent Insights - Track not just dollars spent but actual ROI We built Agent Insights to map AI spend straight to engineering outcomes: features, fixes, and PRs Manage your budget based on actual company priorities Cut your spend in half with the Entelligence model router See what your AI spend actually shipped:

Nobody cares that you process 2B tokens. That’s not a flex, it’s a bill. Introducing Entelligence AI Agent Insights - Track not just dollars spent but actual ROI We built Agent Insights to map AI spend straight to engineering outcomes: features, fixes, and PRs Manage your budget based on actual company priorities Cut your spend in half with the Entelligence model router See what your AI spend actually shipped:

Aiswarya Sankar

65,185 görüntüleme • 27 gün önce

Most companies don't know what their customers are actually frustrated about. So I built an AI agent called **Customer Pain Point Miner**. Type a company name, and it automatically finds: • Top customer complaints • Features users keep requesting • Recurring frustrations • Product improvement opportunities It scans reviews, Reddit threads, forums, and blogs, then turns thousands of discussions into a sourced report. No surveys. No guessing. Just real customer feedback from across the web. Built it with Nimble Their APIs made it surprisingly easy to search, extract, and structure live web data into something an AI agent can actually reason about. The best roadmap isn't hidden in another brainstorming session. It's already sitting in your customers' conversations.

Most companies don't know what their customers are actually frustrated about. So I built an AI agent called Customer Pain Point Miner. Type a company name, and it automatically finds: • Top customer complaints • Features users keep requesting • Recurring frustrations • Product improvement opportunities It scans reviews, Reddit threads, forums, and blogs, then turns thousands of discussions into a sourced report. No surveys. No guessing. Just real customer feedback from across the web. Built it with Nimble Their APIs made it surprisingly easy to search, extract, and structure live web data into something an AI agent can actually reason about. The best roadmap isn't hidden in another brainstorming session. It's already sitting in your customers' conversations.

Vipin Gautam (Viipin I Gautam)

96,002 görüntüleme • 2 ay önce

Congrats to Eloquent AI on their $7.4M seed! Traditional agentic systems require engineering teams to build APIs—work that sits in long IT backlogs. Eloquent's AI operators learn from screen recordings and then execute complex financial workflows without APIs or engineering lift, resulting in 96% automation of regulated workflows, 5x lower cost, and minutes instead of hours for multi-party processes.

Congrats to Eloquent AI on their $7.4M seed! Traditional agentic systems require engineering teams to build APIs—work that sits in long IT backlogs. Eloquent's AI operators learn from screen recordings and then execute complex financial workflows without APIs or engineering lift, resulting in 96% automation of regulated workflows, 5x lower cost, and minutes instead of hours for multi-party processes.

Y Combinator

18,835 görüntüleme • 8 ay önce

Always wondered where we actually use these formulas in real life? A mechanical engineer, sajjan_purushh on IG, is answering exactly that by breaking down cos ø (power factor) in workshops, showing how it quietly works behind the machines we see every day. By breaking it down into everyday examples, he shows that engineering is not just theory in books. It is already shaping how our world runs, quietly and constantly. Credits : sajjan_purushh on IG #Engineering #Physics #STEM #EngineeringLife #RealWorldLearning [Power Factor Explained, Cos Phi In Real Life, Mechanical Engineering Concepts, Practical Engineering Examples, How Machines Work]

Always wondered where we actually use these formulas in real life? A mechanical engineer, sajjan_purushh on IG, is answering exactly that by breaking down cos ø (power factor) in workshops, showing how it quietly works behind the machines we see every day. By breaking it down into everyday examples, he shows that engineering is not just theory in books. It is already shaping how our world runs, quietly and constantly. Credits : sajjan_purushh on IG #Engineering #Physics #STEM #EngineeringLife #RealWorldLearning [Power Factor Explained, Cos Phi In Real Life, Mechanical Engineering Concepts, Practical Engineering Examples, How Machines Work]

The Better India

25,335 görüntüleme • 4 ay önce

Can AI actually automate jobs? Scale AI and are launching the Remote Labor Index (RLI), the first benchmark and public leaderboard that test how well AI agents can complete real, paid freelance work in domains like software engineering, design, architecture, data analysis, and more. Early results show the limits of today’s models. The top AI agent completed just 2.5% of real freelance jobs better than humans. AI is powerful, but not yet reliable enough to replace skilled labor. RLI gives us a transparent way to track progress over time and bring clarity to the future of work.

Can AI actually automate jobs? Scale AI and are launching the Remote Labor Index (RLI), the first benchmark and public leaderboard that test how well AI agents can complete real, paid freelance work in domains like software engineering, design, architecture, data analysis, and more. Early results show the limits of today’s models. The top AI agent completed just 2.5% of real freelance jobs better than humans. AI is powerful, but not yet reliable enough to replace skilled labor. RLI gives us a transparent way to track progress over time and bring clarity to the future of work.

Bing Liu

424,454 görüntüleme • 9 ay önce

"Intelligence isn't the boundary anymore. Safety is what's actually constraining agents." I had a great conversation with tusharjain, Head of Engineering at Docker, at our AI Engineer booth. Tushar leads engineering at Docker, the containerization platform millions of developers use to package and ship software, and his team is now rebuilding that engine into a runtime for AI agents with safety built in. Fresh off his talk, we got into: 00:57 - Why safety, not intelligence, is the real constraint on agents 02:00 - The three pillars: contain agents, scope their tools, layer on policy 04:04 - Background agents and the "laptops half open so the agent doesn't die" problem 08:13 - Going 100% agents on Docker's own engineering team 11:28 - Agent identity: you can fire a human, but not their agent Thanks for coming to the Browserbase booth!

"Intelligence isn't the boundary anymore. Safety is what's actually constraining agents." I had a great conversation with tusharjain, Head of Engineering at Docker, at our AI Engineer booth. Tushar leads engineering at Docker, the containerization platform millions of developers use to package and ship software, and his team is now rebuilding that engine into a runtime for AI agents with safety built in. Fresh off his talk, we got into: 00:57 - Why safety, not intelligence, is the real constraint on agents 02:00 - The three pillars: contain agents, scope their tools, layer on policy 04:04 - Background agents and the "laptops half open so the agent doesn't die" problem 08:13 - Going 100% agents on Docker's own engineering team 11:28 - Agent identity: you can fire a human, but not their agent Thanks for coming to the Browserbase booth!

Shubhankar

20,947 görüntüleme • 27 gün önce

Nvidia put $420M into $TAO with 77% of it staked. Polychain added $200M on top of that. Grayscale and Bitwise both filed for spot TAO ETFs in the same quarter. The network generated $43M in real AI revenue last quarter from actual usage, not speculation. Most people are still treating this like a small cap gamble while institutions are treating it like infrastructure. The people who understand what is being built here will not need anyone to explain the price later.

Nvidia put $420M into $TAO with 77% of it staked. Polychain added $200M on top of that. Grayscale and Bitwise both filed for spot TAO ETFs in the same quarter. The network generated $43M in real AI revenue last quarter from actual usage, not speculation. Most people are still treating this like a small cap gamble while institutions are treating it like infrastructure. The people who understand what is being built here will not need anyone to explain the price later.

2xnmore

42,811 görüntüleme • 3 ay önce

They told you, NFTs were over But creators just got their most powerful tool Watch out LaunchMyNFT Built for speed Built for ownership Built for anyone LaunchMyNFT lets you go from idea to live collection in minutes No code Multi chain Real traction already happening This is where the next wave is being built You are not late You are just early enough to see it Watch the video Then go explore it yourself

They told you, NFTs were over But creators just got their most powerful tool Watch out LaunchMyNFT Built for speed Built for ownership Built for anyone LaunchMyNFT lets you go from idea to live collection in minutes No code Multi chain Real traction already happening This is where the next wave is being built You are not late You are just early enough to see it Watch the video Then go explore it yourself

Rakesh Kumar (𝕮𝖆𝖕𝖙𝖆𝖎𝖓)

27,960 görüntüleme • 3 ay önce