Загрузка видео...

Не удалось загрузить видео

На главную

Introducing Coldtea. The ADE for shipping self-driving software. Purpose-built for the entire software lifecycle. Other IDEs optimise for one thing: Build. Run more agents in parallel, ship faster, orchestrate better. But software engineering is not just about building. Coldtea AI brings your coding agents, agentic end-to-end testing, and production...

OhansEmmanuel's profile picture

Ohans Emmanuel

3,713 subscribers

137,236 просмотров • 12 часов назад •via X (Twitter)

Наука и технологииОбразование
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Software isn’t merely technical work anymore. It’s creative. Introducing Replit Agent 4. The first AI built for creative collaboration between humans and agents. Design on an infinite canvas, work with your team, run parallel agents, and ship working apps, sites, slides & more.
8:25

Software isn’t merely technical work anymore. It’s creative. Introducing Replit Agent 4. The first AI built for creative collaboration between humans and agents. Design on an infinite canvas, work with your team, run parallel agents, and ship working apps, sites, slides & more.

Amjad Masad

3,323,961 просмотров • 5 месяцев назад

At DevCon 6, Palantir Software Engineer Ankit Shankar unveils the Agent Stack, a set of products to help you build production agents for the enterprise, all built on the Ontology. ▪️Orchestrator for durable execution ▪️Agent Engine and Agent SDK for building agents of any shape ▪️Agent Manager for actionable telemetry and observability ▪️AIP Evolve for continuous, end-to-end optimization
2:08

At DevCon 6, Palantir Software Engineer Ankit Shankar unveils the Agent Stack, a set of products to help you build production agents for the enterprise, all built on the Ontology. ▪️Orchestrator for durable execution ▪️Agent Engine and Agent SDK for building agents of any shape ▪️Agent Manager for actionable telemetry and observability ▪️AIP Evolve for continuous, end-to-end optimization

Palantir

40,626 просмотров • 27 дней назад

🧲 Meet Magnet — the AI workspace for agentic coding. Build software with Claude Code, Cursor, Codex & co. → Write a ticket → Magnet assembles context → Fires to Claude Code, Deep Research, and other agent sessions in parallel Git worktree sandboxes → PRs appear → Use agents to help you spec, research, and decompose tasks Let your agents cook!
2:12

🧲 Meet Magnet — the AI workspace for agentic coding. Build software with Claude Code, Cursor, Codex & co. → Write a ticket → Magnet assembles context → Fires to Claude Code, Deep Research, and other agent sessions in parallel Git worktree sandboxes → PRs appear → Use agents to help you spec, research, and decompose tasks Let your agents cook!

Nicolae Rusan

16,608 просмотров • 1 год назад

Agents can negotiate, pay, and execute - but none of it holds together. Today we are introducing Internet Court, which is the open skill that connects the entire agentic commerce stack into one flow, so any two agents can run a deal end to end. →
1:01

Agents can negotiate, pay, and execute - but none of it holds together. Today we are introducing Internet Court, which is the open skill that connects the entire agentic commerce stack into one flow, so any two agents can run a deal end to end. →

Internet Court

424,256 просмотров • 1 месяц назад

Amjad Masad (Amjad Masad), co-founder & CEO of Replit, has spent nearly a decade making programming accessible to everyone. With AI, that vision is closer than ever. In his AI Startup School talk, Amjad traces computing’s arc from mainframes to PCs to a future where AI agents generate software on demand—driving the value of traditional software toward zero and reshaping how companies are built. 00:22 - Evolution of Computing 01:27 - The Rise of Software Engineering 02:16 - Replit's Vision: Making Programming Accessible 02:42 - The Role of AI in Software Development 04:32 - Challenges and Infrastructure for AI Agents 05:03 - Building a Scalable and Secure Environment 06:08 - Future of Software Engineering Agents 09:25 - Autonomy Levels in AI Agents 15:56 - Predictions for the Software Market 18:31 - Impact on Business and Employment 19:58 - The Role of Generalist Employees 26:00 - Audience Q&A
42:01

Amjad Masad (Amjad Masad), co-founder & CEO of Replit, has spent nearly a decade making programming accessible to everyone. With AI, that vision is closer than ever. In his AI Startup School talk, Amjad traces computing’s arc from mainframes to PCs to a future where AI agents generate software on demand—driving the value of traditional software toward zero and reshaping how companies are built. 00:22 - Evolution of Computing 01:27 - The Rise of Software Engineering 02:16 - Replit's Vision: Making Programming Accessible 02:42 - The Role of AI in Software Development 04:32 - Challenges and Infrastructure for AI Agents 05:03 - Building a Scalable and Secure Environment 06:08 - Future of Software Engineering Agents 09:25 - Autonomy Levels in AI Agents 15:56 - Predictions for the Software Market 18:31 - Impact on Business and Employment 19:58 - The Role of Generalist Employees 26:00 - Audience Q&A

Y Combinator

224,320 просмотров • 11 месяцев назад

We raised $8m to build self-healing software. In 2026, software moves fast. But monitoring and observability are still manual and slow. Sazabi is a next-generation observability platform for fast-moving engineering teams. Not another AI SRE. Not another LLM observability tool. A new, general solution to observability that works for any workload (including agents) and leverages AI for maximum speed and automation. Time to suit up.
1:44

We raised $8m to build self-healing software. In 2026, software moves fast. But monitoring and observability are still manual and slow. Sazabi is a next-generation observability platform for fast-moving engineering teams. Not another AI SRE. Not another LLM observability tool. A new, general solution to observability that works for any workload (including agents) and leverages AI for maximum speed and automation. Time to suit up.

Sherwood

1,305,338 просмотров • 1 месяц назад

The trades can build anything... except the software they run on. That changes today. We've raised $9.2M to build Dalton Mills. Software has spent its whole history getting closer to the people who do the work. First, the system of record. Software you stored your business in. Then, the agentic era. Software that did the work for you. Now, the bespoke era. Agentic software you build yourself, without code. Each era closed the gap and this one closes it for good. Software can finally work around your business, instead of you bending your business to make it fit. You ran on software made for everyone… never for you. That's over. Welcome to Dalton Mills. Let the builders build!
2:14

The trades can build anything... except the software they run on. That changes today. We've raised $9.2M to build Dalton Mills. Software has spent its whole history getting closer to the people who do the work. First, the system of record. Software you stored your business in. Then, the agentic era. Software that did the work for you. Now, the bespoke era. Agentic software you build yourself, without code. Each era closed the gap and this one closes it for good. Software can finally work around your business, instead of you bending your business to make it fit. You ran on software made for everyone… never for you. That's over. Welcome to Dalton Mills. Let the builders build!

Todd Saunders

92,793 просмотров • 2 месяцев назад

🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️
2:02

🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️

LangChain

30,744 просмотров • 5 месяцев назад

Introducing: AI agents that ship product videos whenever you ship features. Engineering teams today are releasing product updates faster than ever before. But creating videos for every new release still takes weeks. Now, whenever you ship a feature to your software, Clueso deploys a team of AI agents to create launch videos, product demos, help tutorials, and more. Content can finally ship as quickly as code. Get access at:
2:05

Introducing: AI agents that ship product videos whenever you ship features. Engineering teams today are releasing product updates faster than ever before. But creating videos for every new release still takes weeks. Now, whenever you ship a feature to your software, Clueso deploys a team of AI agents to create launch videos, product demos, help tutorials, and more. Content can finally ship as quickly as code. Get access at:

Akash Anand

44,337 просмотров • 20 дней назад

I built 3 functional web apps in 4min… on my phone! Replit ⠕ Agent don’t just review and write code, their AI agents plan the functions, create development environment, install dependencies, write the code, configure databases and deploy. Is this the beginning of the end of paying for software? What’d you create?
1:29

I built 3 functional web apps in 4min… on my phone! Replit ⠕ Agent don’t just review and write code, their AI agents plan the functions, create development environment, install dependencies, write the code, configure databases and deploy. Is this the beginning of the end of paying for software? What’d you create?

Sander Saar

86,072 просмотров • 1 год назад

The ceo of Box says if you're not building for agents, you won't exist as a software company in 2-3 years. Aaron Levie recalled how in the 90s, it was mainframes built for institutions. If you didn't build for the CIO or IT org, you didn't exist. You could build software for users, but no one cared. Similarly, in the mid 2000s, it was software built for end users. If you didn't take that route, you got completely trounced. The likes of Yammer, Slack, Zoom, etc., ripped through enterprises with viral adoption. Bottom-up and completely user driven. And now it's software built for agents. We're going to have trillions of agent runs. The systems that optimize for agents the most will win. - lower latency - better API exposure - better system intelligence - serves the right information when called Agents will eventually choose their own tools on the fly and make purchasing decisions at runtime. All based on past experiences/online reviews/performance, sans any procurement process. The more pragmatic version is companies swapping out bad tools / tech that don't work well with agents. - crm doesn't expose the right APIs - auth can't handle agent scale requests - database has too much latency for agent workloads Being good enough for humans won't work because they have to pass the litmus test for agents to make the cut.
2:15

The ceo of Box says if you're not building for agents, you won't exist as a software company in 2-3 years. Aaron Levie recalled how in the 90s, it was mainframes built for institutions. If you didn't build for the CIO or IT org, you didn't exist. You could build software for users, but no one cared. Similarly, in the mid 2000s, it was software built for end users. If you didn't take that route, you got completely trounced. The likes of Yammer, Slack, Zoom, etc., ripped through enterprises with viral adoption. Bottom-up and completely user driven. And now it's software built for agents. We're going to have trillions of agent runs. The systems that optimize for agents the most will win. - lower latency - better API exposure - better system intelligence - serves the right information when called Agents will eventually choose their own tools on the fly and make purchasing decisions at runtime. All based on past experiences/online reviews/performance, sans any procurement process. The more pragmatic version is companies swapping out bad tools / tech that don't work well with agents. - crm doesn't expose the right APIs - auth can't handle agent scale requests - database has too much latency for agent workloads Being good enough for humans won't work because they have to pass the litmus test for agents to make the cut.

Ivan Burazin

22,655 просмотров • 3 месяцев назад

"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!
14:13

"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 просмотров • 18 дней назад

📊 Learn how to observe & evaluate agents on LangChain Academy 📊 Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling agents, and testing agents becomes even more complex than traditional software testing 😵‍💫 To address this challenge, LangSmith provides a comprehensive platform for agent engineering that helps teams use live production data for continuous testing and improvement 🚀 In our quickstart course, LangSmith Essentials, you’ll learn how to observe, evaluate, and deploy your agent in less than 30 minutes. Enroll for free ➡️
1:44

📊 Learn how to observe & evaluate agents on LangChain Academy 📊 Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling agents, and testing agents becomes even more complex than traditional software testing 😵‍💫 To address this challenge, LangSmith provides a comprehensive platform for agent engineering that helps teams use live production data for continuous testing and improvement 🚀 In our quickstart course, LangSmith Essentials, you’ll learn how to observe, evaluate, and deploy your agent in less than 30 minutes. Enroll for free ➡️

LangChain

13,518 просмотров • 7 месяцев назад

Agents now Run Revenue, End-to-End. Rox Autopilot is here 🚀 The world’s largest enterprises now run their critical revenue systems on Autopilot. Coding and support agents had their moment. Now it’s time for Revenue Agents No SaaS. No enrichment. No CRM. Just an Agent. We’re offering 2× free agent actions for the next 30 days. Start Autopilot at Thank you to Sequoia Capital, General Catalyst, @GoogleVentures, Marc Bhargava, Vedant Suri, Dave Munichiello 🇺🇸, MongoDB, Cloud Software Group, Together AI, Microsoft, Databricks, and all of our other customers & partners!
2:07

Agents now Run Revenue, End-to-End. Rox Autopilot is here 🚀 The world’s largest enterprises now run their critical revenue systems on Autopilot. Coding and support agents had their moment. Now it’s time for Revenue Agents No SaaS. No enrichment. No CRM. Just an Agent. We’re offering 2× free agent actions for the next 30 days. Start Autopilot at Thank you to Sequoia Capital, General Catalyst, @GoogleVentures, Marc Bhargava, Vedant Suri, Dave Munichiello 🇺🇸, MongoDB, Cloud Software Group, Together AI, Microsoft, Databricks, and all of our other customers & partners!

Rox

72,939 просмотров • 4 месяцев назад

Today, Sierra is releasing Ghostwriter, our agent for building agents. With Ghostwriter, you can create an AI agent for your customer experience — one that can chat, pick up the phone, speak dozens of languages, take action on your systems of record, and be protected with industry-leading guardrails — simply by having a conversation. No clicking, no forms, no menus. Codex and Claude Code have transformed how we build software, making it possible for software engineers to orchestrate and review the work rather than doing all the work themselves. We think the same transformation will happen for all software. Rather than every enterprise app having a web app for humans and an API for automation, every software platform’s UI will be an agent that can do the work on your behalf. I recorded a demo of my building and optimizing an agent with Ghostwriter so you can see how powerful and easy it is to use. It’s completely changed the way our early adopters build agents, and it’s changed the way I think about the software industry. Let me know what you think, and, if you’re interested in trying it out at your business, please reach out directly.
10:43

Today, Sierra is releasing Ghostwriter, our agent for building agents. With Ghostwriter, you can create an AI agent for your customer experience — one that can chat, pick up the phone, speak dozens of languages, take action on your systems of record, and be protected with industry-leading guardrails — simply by having a conversation. No clicking, no forms, no menus. Codex and Claude Code have transformed how we build software, making it possible for software engineers to orchestrate and review the work rather than doing all the work themselves. We think the same transformation will happen for all software. Rather than every enterprise app having a web app for humans and an API for automation, every software platform’s UI will be an agent that can do the work on your behalf. I recorded a demo of my building and optimizing an agent with Ghostwriter so you can see how powerful and easy it is to use. It’s completely changed the way our early adopters build agents, and it’s changed the way I think about the software industry. Let me know what you think, and, if you’re interested in trying it out at your business, please reach out directly.

Bret Taylor

1,062,187 просмотров • 4 месяцев назад

Introducing Giga's browser agent. Giga can now log in and completes tasks end-to-end, just like your human agents. It used to take months to get support APIs deployed for AI agents in the enterprise. Now these integrations can be built instantly.
1:16

Introducing Giga's browser agent. Giga can now log in and completes tasks end-to-end, just like your human agents. It used to take months to get support APIs deployed for AI agents in the enterprise. Now these integrations can be built instantly.

Esha

1,481,739 просмотров • 6 месяцев назад

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓
2:05:53

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Lunar

390,986 просмотров • 5 дней назад

Everyone is trying to build a support agent. Now you can build one in your CLI that resolves 90% of your support tickets. Today we're launching the Giga CLI. pip install giga-sdk Build, test, deploy, and roll back your AI agents like production software. This is the workflow our customers use to operate AI agents resolving 100,000+ support tickets every day. → CI-gated deployments → GitHub-powered knowledge base syncs → Bulk conversation analysis → Integrating Coding Agents directly into Giga Available now on PyPI.
1:08

Everyone is trying to build a support agent. Now you can build one in your CLI that resolves 90% of your support tickets. Today we're launching the Giga CLI. pip install giga-sdk Build, test, deploy, and roll back your AI agents like production software. This is the workflow our customers use to operate AI agents resolving 100,000+ support tickets every day. → CI-gated deployments → GitHub-powered knowledge base syncs → Bulk conversation analysis → Integrating Coding Agents directly into Giga Available now on PyPI.

Giga

211,994 просмотров • 28 дней назад

I built dev tools at GitHub for 7 years before AI coding became the default. AI made code gen fast, but software still depends on the human mind knowing which details matter. AI only made that harder. That's why I built Nuanced, the AI coding app I want. Nuanced is a macOS app for building software with agents around a living spec, keeping intent and implementation connected as the agent builds. Try it:
1:52

I built dev tools at GitHub for 7 years before AI coding became the default. AI made code gen fast, but software still depends on the human mind knowing which details matter. AI only made that harder. That's why I built Nuanced, the AI coding app I want. Nuanced is a macOS app for building software with agents around a living spec, keeping intent and implementation connected as the agent builds. Try it:

ayman nadeem

12,822 просмотров • 1 месяц назад

An engineer at Anthropic wrote a spec, pointed Claude at an Asana board, and went home. Claude broke the spec into tickets, spawned agents for each one, and they started building independently. When the agent is confused it runs git-blame and messages the right engineers in Slack. By Monday the agents finished the plugin feature. That's one example of how the best engineers are shipping software right now. Developers will soon orchestrate 50 AI agents in parallel and the difference between a good engineer & a great one would come down to specs. You can't write a spec that holds up at that scale without genuinely understanding what you're building at a deeper level. The next-gen developer who understands the fundamentals, can architect well and orchestrate agent is going to be a 1000x developer!
1:08

An engineer at Anthropic wrote a spec, pointed Claude at an Asana board, and went home. Claude broke the spec into tickets, spawned agents for each one, and they started building independently. When the agent is confused it runs git-blame and messages the right engineers in Slack. By Monday the agents finished the plugin feature. That's one example of how the best engineers are shipping software right now. Developers will soon orchestrate 50 AI agents in parallel and the difference between a good engineer & a great one would come down to specs. You can't write a spec that holds up at that scale without genuinely understanding what you're building at a deeper level. The next-gen developer who understands the fundamentals, can architect well and orchestrate agent is going to be a 1000x developer!

rvivek

1,242,662 просмотров • 5 месяцев назад