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I’m excited to launch Tessl's first products! Introducing the Tessl Framework and Tessl Spec Registry, which integrate into any agent to keep it on rails and well informed using Spec-Driven Development. More details in the launch post: It’s a big milestone in the journey towards AI Native Development🚩 I’m...

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Guy Podjarny

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Agent skills help agents use your products, build in your codebase and enforce your policies. They’re not just words - they are what the unit of software for agentic devs, and need powerful dev tools to match. That is what Tessl offers. Tessl is the package manager and development platform for skills. It offers a full dev lifecycle, helping you generate, evaluate, distribute and observe skills & context, developing them to the professional grade they warrant. Today, I’m excited to announce the general availability of our task evals, which help you understand how good your skills are. Such insight is critical to making your skills great, avoiding regression, and applying learnings from their real world usage. For example: Cisco's software-security skill shows a 1.8X improvement in securing coding in its benchmark, and ElevenLabs's agents skill boosts success by almost 3X! However, not to name names, we often see skills that provide minimal uplift while consuming context window space, or even degrade functionality. As Spencer Kimball, CEO of Cockroach Labs, put it when we shared early versions of this: evaluation is what makes agentic coding outcomes converge instead of drifting. Task evals are joining a long list of powerful context development tools, such as: * Review skills against quality best practices * Generate and maintain skills and docs for using your libraries & platform * Distribute versioned skills to your dev team and ecosystem * Consume skills easily and safely, and keep them up-to-date Skills are a central part of software development. If you’re serious about making agentic dev successful in your org, or helping your customers’s agents use your products, you need to invest in them. We hope Tessl can help. Check out links in the thread to get started!
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Agent skills help agents use your products, build in your codebase and enforce your policies. They’re not just words - they are what the unit of software for agentic devs, and need powerful dev tools to match. That is what Tessl offers. Tessl is the package manager and development platform for skills. It offers a full dev lifecycle, helping you generate, evaluate, distribute and observe skills & context, developing them to the professional grade they warrant. Today, I’m excited to announce the general availability of our task evals, which help you understand how good your skills are. Such insight is critical to making your skills great, avoiding regression, and applying learnings from their real world usage. For example: Cisco's software-security skill shows a 1.8X improvement in securing coding in its benchmark, and ElevenLabs's agents skill boosts success by almost 3X! However, not to name names, we often see skills that provide minimal uplift while consuming context window space, or even degrade functionality. As Spencer Kimball, CEO of Cockroach Labs, put it when we shared early versions of this: evaluation is what makes agentic coding outcomes converge instead of drifting. Task evals are joining a long list of powerful context development tools, such as: * Review skills against quality best practices * Generate and maintain skills and docs for using your libraries & platform * Distribute versioned skills to your dev team and ecosystem * Consume skills easily and safely, and keep them up-to-date Skills are a central part of software development. If you’re serious about making agentic dev successful in your org, or helping your customers’s agents use your products, you need to invest in them. We hope Tessl can help. Check out links in the thread to get started!

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New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @pauleveritt@fosstodon.org. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!
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New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @[email protected]. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

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🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:
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🔗 Announcing LangChain OSS Skills LangChain has the most popular frameworks for building AI agents — and now your coding agent can be an expert in it. We're excited to release the first iteration of LangChain OSS Skills, giving your agent expertise in our open source frameworks. The skills include guidance on how to use langchain, langgraph, and deepagents to effectively build agents. ➡️ Install our OSS skills for your coding agent here: ➡️ Read more:

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We've built 40+ AI agents and internal tools. The hardest part is Context Creation. AI runs playbooks and makes judgment calls for you. But without your company's context, you get slop. Context Creation means extracting the subject matter expertise and playbooks that live in people's heads, not in LLM training data, or even your tools. As forward deployed engineers (FDEs), we create context and turn it into code. We evaluate the business impact, how it aligns with the dev roadmap, and come up with creative solutions. We built The FDE Factory to replace ourselves. It drives AI adoption inside our clients' companies by running discovery sessions using prototypes to create context. Here's how it works: We put a prototype in front of a stakeholder. The stakeholder gives feedback via voice while they're using or reviewing it. Then our FDE Factory Agents builds in their expertise in minutes: > Context Agent reviews the codebase and feedback, extracts the requirements, and creates a spec > Scope Agent checks the spec against the development roadmap, validates it, and hands it off > Engineering Agent builds a new feature and wires the integration > QA Agent runs tests to prove to itself it works > PR merges, feature goes live, product updates itself in real time It's like the nontechnical stakeholder wrote the code without even knowing it. Coding agents are great at turning good development plans into code, and they're getting better at turning context into good development plans in collaboration with professional engineers. But nontechnical people are capped on what they can build without product people and engineers. The bridge that takes nontechnical people from vibe coding basic apps to building production AI tools that run on first party context is FDEs. Our new FDE Factory gives you the system to go from idea to production. Context Creation is the first and most important step in our FDE lifecycle, and we just automated it. Now clients get the right agents and tools built for them, customized to their unique business and encoded with their expertise. PS: If you're building AI agents within your company, reply "Playbook" and I'll DM you the entire FDE playbook we've run with 30+ companies. It covers finding high-impact AI use cases, building them, and deploying them across the org.
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We've built 40+ AI agents and internal tools. The hardest part is Context Creation. AI runs playbooks and makes judgment calls for you. But without your company's context, you get slop. Context Creation means extracting the subject matter expertise and playbooks that live in people's heads, not in LLM training data, or even your tools. As forward deployed engineers (FDEs), we create context and turn it into code. We evaluate the business impact, how it aligns with the dev roadmap, and come up with creative solutions. We built The FDE Factory to replace ourselves. It drives AI adoption inside our clients' companies by running discovery sessions using prototypes to create context. Here's how it works: We put a prototype in front of a stakeholder. The stakeholder gives feedback via voice while they're using or reviewing it. Then our FDE Factory Agents builds in their expertise in minutes: > Context Agent reviews the codebase and feedback, extracts the requirements, and creates a spec > Scope Agent checks the spec against the development roadmap, validates it, and hands it off > Engineering Agent builds a new feature and wires the integration > QA Agent runs tests to prove to itself it works > PR merges, feature goes live, product updates itself in real time It's like the nontechnical stakeholder wrote the code without even knowing it. Coding agents are great at turning good development plans into code, and they're getting better at turning context into good development plans in collaboration with professional engineers. But nontechnical people are capped on what they can build without product people and engineers. The bridge that takes nontechnical people from vibe coding basic apps to building production AI tools that run on first party context is FDEs. Our new FDE Factory gives you the system to go from idea to production. Context Creation is the first and most important step in our FDE lifecycle, and we just automated it. Now clients get the right agents and tools built for them, customized to their unique business and encoded with their expertise. PS: If you're building AI agents within your company, reply "Playbook" and I'll DM you the entire FDE playbook we've run with 30+ companies. It covers finding high-impact AI use cases, building them, and deploying them across the org.

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Introducing Theoriq’s AlphaSwarm! ⚡️ We’re thrilled to give developers access to a starter toolkit for building AI-powered trading agents in DeFi (AiFi)! 🦾 AlphaSwarm streamlines agent and swarm development, making it easier to build, execute, and refine collaborative agents that can analyze real-time market signals, and autonomously execute trades across multiple chains. Check out our latest blog for more details! 👇 You can explore the toolkit directly in Theoriq’s GitHub: Or if you’re a developer interested in building the future of AiFi, join our dev community in Discord:

Theoriq

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We just open-sourced Simulang, a JavaScript library that gives you and your coding agents the ability to fully control computers. Simulang is our scripting framework for desktop automation. It allows you to write deterministic computer use code that can be replayed dozens if not hundreds of times. Much faster and cheaper, compared to LLM agents. It ships with a skill out of the box. That means you can turn natural language prompts into Simulang code directly, and your agent can now see the screen, click, type, and navigate. It gives your AI agents eyes and hands to control the computer like humans do. Try these things with Simulang: - upload your pile of invoices to the expense platform - find 50 people with specific criteria on LinkedIn - open your calculator app and do some math - find all buttons on your favorite app using accessibility tree - or draw a bunny with MS paint 🐰 In this demo, we show how Simulang took over when the coding agent couldn’t open and click on the target LinkedIn profile page. Give it a try:

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14,421 Aufrufe • vor 2 Monaten

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Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 Aufrufe • vor 1 Jahr

We are excited to announce a powerful step for the future of FOMO! Taking a page out of Virtuals book on BASE, FOMO will be releasing the ability for future projects to be paired in $FOMO in the coming weeks. This is the biggest release we have ever announced. Launch your AI Agent Token + $FOMO trading pair Every individual agent token is paired with the $FOMO token in its liquidity pool. When launching an agent on you will need $FOMO tokens, which are used to create the liquidity pool. This process creates deflationary pressure for FOMO and the entire agent ecosystem. When creating your agent and token, you will have the option to pair your launch with FOMO or SOL, as our goal is not to alienate any project, but rather invite the best communities, CTO’s and builders to launch with us. If you decide to pair your project with FOMO you in turn get full marketing and dev support, once your project graduates the bonding curve and reaches Raydium. Further, as an added incentive, as our revenue grows we will be using part of the funds to support projects that have paired in FOMO. And Devs who launch tokens paired in FOMO will earn fees from their AI Agent token launch. Building the most robust agents using our framework will catapult us as one of the most prominent standards of the Solana ecosystem. Not only have we developed our own core infrastructure, but we also pull from some of the best repo’s and developer talent in all of AI, not just blockchain. Our team is comprised of 9 world class artificial intelligence engineers, PHDs in mathematics and engineering from the top companies on the cutting edge of AI. The future of AI Agents will be on Solana and we will help lead the way.
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We are excited to announce a powerful step for the future of FOMO! Taking a page out of Virtuals book on BASE, FOMO will be releasing the ability for future projects to be paired in $FOMO in the coming weeks. This is the biggest release we have ever announced. Launch your AI Agent Token + $FOMO trading pair Every individual agent token is paired with the $FOMO token in its liquidity pool. When launching an agent on you will need $FOMO tokens, which are used to create the liquidity pool. This process creates deflationary pressure for FOMO and the entire agent ecosystem. When creating your agent and token, you will have the option to pair your launch with FOMO or SOL, as our goal is not to alienate any project, but rather invite the best communities, CTO’s and builders to launch with us. If you decide to pair your project with FOMO you in turn get full marketing and dev support, once your project graduates the bonding curve and reaches Raydium. Further, as an added incentive, as our revenue grows we will be using part of the funds to support projects that have paired in FOMO. And Devs who launch tokens paired in FOMO will earn fees from their AI Agent token launch. Building the most robust agents using our framework will catapult us as one of the most prominent standards of the Solana ecosystem. Not only have we developed our own core infrastructure, but we also pull from some of the best repo’s and developer talent in all of AI, not just blockchain. Our team is comprised of 9 world class artificial intelligence engineers, PHDs in mathematics and engineering from the top companies on the cutting edge of AI. The future of AI Agents will be on Solana and we will help lead the way.

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Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!
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Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!

Sam Rodriques

725,230 Aufrufe • vor 1 Jahr

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base
1:47

Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base

Malte Ubl

124,713 Aufrufe • vor 7 Monaten

Excited to launch Upstream and announce our $3M pre-seed round AN INBOX DESIGNED FOR HUMANS AND AGENTS Upstream's agents sort the noise, draft replies in your exact voice, follow up at the right time, and do what you ask, like finding receipts, scheduling meetings, or writing personalized messages Thousands of people used it in our closed beta to handle their email. Now available to everyone How it works: 🧵
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Excited to launch Upstream and announce our $3M pre-seed round AN INBOX DESIGNED FOR HUMANS AND AGENTS Upstream's agents sort the noise, draft replies in your exact voice, follow up at the right time, and do what you ask, like finding receipts, scheduling meetings, or writing personalized messages Thousands of people used it in our closed beta to handle their email. Now available to everyone How it works: 🧵

Louis Lecat

36,417 Aufrufe • vor 2 Monaten

Today we open the Zapier SDK to everyone. If you're building with AI agents, this is for you. I've been using this for 2 months. It's totally changed how I do my job. You install it in your coding agent. Cursor, Claude Code, Codex, whatever you use. Now that agent has access to 8,000+ apps through Zapier and can do anything those APIs can do. I think it’s the most powerful thing we’ve launched in years. Now in open beta. Just give this link right to your agent:
2:47

Today we open the Zapier SDK to everyone. If you're building with AI agents, this is for you. I've been using this for 2 months. It's totally changed how I do my job. You install it in your coding agent. Cursor, Claude Code, Codex, whatever you use. Now that agent has access to 8,000+ apps through Zapier and can do anything those APIs can do. I think it’s the most powerful thing we’ve launched in years. Now in open beta. Just give this link right to your agent:

Wade Foster

174,868 Aufrufe • vor 3 Monaten

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!
2:59

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

Milind S

11,917 Aufrufe • vor 2 Monaten

🟦 SUMEX BETA TEST - LIVE NOW Our beta test just opened - and it’s happening right now during the community call in Discord. here: The CEO is walking everyone through: • how to claim beta access • how to navigate the platform • how to secure your Beta Tester achievement (rewarded after TGE) ⚠️ Access is extremely limited: only 500 slots. And the counter is dropping every minute since this announcement. If you want to be among the first to touch SUMEX before launch - this is your moment. ...tick tock⌚ The doors are open… and they won’t stay open long. 👉 Join the SUMEX Discord and get in.
0:37

🟦 SUMEX BETA TEST - LIVE NOW Our beta test just opened - and it’s happening right now during the community call in Discord. here: The CEO is walking everyone through: • how to claim beta access • how to navigate the platform • how to secure your Beta Tester achievement (rewarded after TGE) ⚠️ Access is extremely limited: only 500 slots. And the counter is dropping every minute since this announcement. If you want to be among the first to touch SUMEX before launch - this is your moment. ...tick tock⌚ The doors are open… and they won’t stay open long. 👉 Join the SUMEX Discord and get in.

SUMEX | Web3 SuperApp

101,091 Aufrufe • vor 6 Monaten

New course to bring you up to state-of-the-art at using AI to help you code: Build Apps with Windsurf's AI Coding Agents, built in partnership with WIndsurf (Codeium) and taught by Anshul Ramachandran! AI-assisted IDEs (Integrated Development Environments) make developers’ workflows faster, more efficient, and much more fun. Agentic tools like Windsurf are more than just code autocomplete—they are collaborative coding agents that help you break down complex applications, iterate efficiently, and generate code that spans multiple files. Although a lot of coding assistants share the same underlying large language models for planning and reasoning, a major point of distinction is how they handle tools, keep track of context, and stay aligned with your intent as a developer. For instance, if you make modifications to a class definition in your code and make the same modifications to other classes in the same directory, you might tell the AI agent "Do the same thing in similar places in this directory." Here, tracking your intent means understanding that “the same thing" refers to that recent edit you just made, which must be followed by appropriate search and tool-calling to implement the changes. In this course, you'll learn the inner workings of coding agents, their strengths and limitations, and how to use Windsurf to quickly build several applications. In detail, you'll: - Build a mental model of how agents work by combining human-action tracking, tool integration, and context awareness to carry out an agentic coding workflow. - Learn the challenges of code search and discovery and how a multi-step retrieval approach helps coding agents address them. - Use Windsurf to analyze and understand a large, old codebase and update it to the latest versions of the frameworks and packages it uses. - Build a Wikipedia data analysis app that retrieves, parses, and analyzes word frequencies. - Enhance the performance of your Wikipedia analysis app by adding caching, and through this, also learn how to course-correct when the AI agent produces unexpected results. - Learn tips and tricks such as keyboard shortcuts, autocomplete, and @ mentions to quickly call on agentic capabilities. - Use image/multimodal capabilities of the AI agent to increase your development velocity; you'll see an example of uploading a mockup with sketched-out UI features, and ask the agent to use that to build new functionality to an app. By the end of this course, you’ll understand agentic coding in-depth and know how to use it to make your development process much faster, more efficient, and enjoyable. Please sign up here!
4:01

New course to bring you up to state-of-the-art at using AI to help you code: Build Apps with Windsurf's AI Coding Agents, built in partnership with WIndsurf (Codeium) and taught by Anshul Ramachandran! AI-assisted IDEs (Integrated Development Environments) make developers’ workflows faster, more efficient, and much more fun. Agentic tools like Windsurf are more than just code autocomplete—they are collaborative coding agents that help you break down complex applications, iterate efficiently, and generate code that spans multiple files. Although a lot of coding assistants share the same underlying large language models for planning and reasoning, a major point of distinction is how they handle tools, keep track of context, and stay aligned with your intent as a developer. For instance, if you make modifications to a class definition in your code and make the same modifications to other classes in the same directory, you might tell the AI agent "Do the same thing in similar places in this directory." Here, tracking your intent means understanding that “the same thing" refers to that recent edit you just made, which must be followed by appropriate search and tool-calling to implement the changes. In this course, you'll learn the inner workings of coding agents, their strengths and limitations, and how to use Windsurf to quickly build several applications. In detail, you'll: - Build a mental model of how agents work by combining human-action tracking, tool integration, and context awareness to carry out an agentic coding workflow. - Learn the challenges of code search and discovery and how a multi-step retrieval approach helps coding agents address them. - Use Windsurf to analyze and understand a large, old codebase and update it to the latest versions of the frameworks and packages it uses. - Build a Wikipedia data analysis app that retrieves, parses, and analyzes word frequencies. - Enhance the performance of your Wikipedia analysis app by adding caching, and through this, also learn how to course-correct when the AI agent produces unexpected results. - Learn tips and tricks such as keyboard shortcuts, autocomplete, and @ mentions to quickly call on agentic capabilities. - Use image/multimodal capabilities of the AI agent to increase your development velocity; you'll see an example of uploading a mockup with sketched-out UI features, and ask the agent to use that to build new functionality to an app. By the end of this course, you’ll understand agentic coding in-depth and know how to use it to make your development process much faster, more efficient, and enjoyable. Please sign up here!

Andrew Ng

139,858 Aufrufe • vor 1 Jahr

1M users joined our community! Thanks for your love! Now we are excited to announce that AI Terminal is ready to launch. Here is a 5 minutes live demo without any edit. AI Terminal is the early version of Agent browser (you can also call it Agent OS). It's backed by our agent network routing and orchestration technologies. Chainopera AI is built by crypto, for crypto! We are looking forwards to see great agents and AI models contributed by the community. We will officially release it to our early community remembers starting from ETH Denver. See you in our booth!
4:59

1M users joined our community! Thanks for your love! Now we are excited to announce that AI Terminal is ready to launch. Here is a 5 minutes live demo without any edit. AI Terminal is the early version of Agent browser (you can also call it Agent OS). It's backed by our agent network routing and orchestration technologies. Chainopera AI is built by crypto, for crypto! We are looking forwards to see great agents and AI models contributed by the community. We will officially release it to our early community remembers starting from ETH Denver. See you in our booth!

ChainOpera AI

550,871 Aufrufe • vor 1 Jahr

Introducing Clips - 100% free, open source, agent-native alternative to Loom Unlike Loom, agent's can fully understand Clips just from a URL. Every Clip comes with APIs and metadata for agents to explore their contents. Agents can "see and hear" anything in a Clip - not just transcripts, but everything visually in the video at any timestamp. Easily share bug reports, feedback, analyses, or anything else in a way that you can easily pass to agents to use to improve products, reports, or more. Also unlike Loom, you own the software, so no one can jack up prices on you suddenly like Loom did to us. Clips is made to be customized. The built-in agent can customize its own code, so you can personalize the app to your needs and workflows. This, in my opinion, is the future of software. Open-source, forkable, customizable with agents, to make your own personal version of anything. You can also import Looms just from a URL and upload videos as well. I got so sick of telling people "don't send me feedback as looms, I can't pass those to agents, I need text and images" that I had to just solve this once and for all. There's a free hosted version you can use too, or fork and self host yourself. Will link to both in the replies.
0:35

Introducing Clips - 100% free, open source, agent-native alternative to Loom Unlike Loom, agent's can fully understand Clips just from a URL. Every Clip comes with APIs and metadata for agents to explore their contents. Agents can "see and hear" anything in a Clip - not just transcripts, but everything visually in the video at any timestamp. Easily share bug reports, feedback, analyses, or anything else in a way that you can easily pass to agents to use to improve products, reports, or more. Also unlike Loom, you own the software, so no one can jack up prices on you suddenly like Loom did to us. Clips is made to be customized. The built-in agent can customize its own code, so you can personalize the app to your needs and workflows. This, in my opinion, is the future of software. Open-source, forkable, customizable with agents, to make your own personal version of anything. You can also import Looms just from a URL and upload videos as well. I got so sick of telling people "don't send me feedback as looms, I can't pass those to agents, I need text and images" that I had to just solve this once and for all. There's a free hosted version you can use too, or fork and self host yourself. Will link to both in the replies.

Steve (Builder.io)

230,407 Aufrufe • vor 1 Monat

Introducing the Clips chrome extension - the easiest way to send bug reports to agents with video, transcript, and browser debug info captured automatically. 100% free and open source. If you are like me and get tired of manually typing instructions to agents, attaching screenshots, pasting debug logs, and all of that, this might be your new favorite tool. With the Clips chrome extension, you can just click the Clips icon, hit record, and start talking. Visually demonstrate your issue, go through the flow, point out what’s broken. Clips will capture everything on your screen, plus network requests, browser logs, client errors, and all the details around them. And it redacts sensitive information. Then it gives you a link you can send to humans so they can play it and take a look. Or, more importantly, just give it to your agents by just pasting the URL to them. The link has special metadata for agents so just from the URL, the agent can pull all information from the clip automatically. No plugin or MCP server required. That means it can "see and hear" what’s in the video - read the transcript, grab snapshots at any timestamp, and inspect the logs and network requests that were shared with it. So whether you want to quickly demo an issue and send all that context to an agent, or get better bug reports from teammates, recording and sending Clips makes that super easy. Unlike expensive apps like Loom, this is all 100% free and open source. The framework that powers this, plus a bunch of other free applications, is open source too. You can just sign up and use it, or fork it and customize it to your needs. This, in my opinion, is the future of software. Rather than bloated SaaS that charges you a ton of money and still doesn’t even have the things you need, we get free open source canonical apps that you can fork and customize in any way you want. I'll link to all this stuff in the replies. If you try it, let me know your feedback.
1:27

Introducing the Clips chrome extension - the easiest way to send bug reports to agents with video, transcript, and browser debug info captured automatically. 100% free and open source. If you are like me and get tired of manually typing instructions to agents, attaching screenshots, pasting debug logs, and all of that, this might be your new favorite tool. With the Clips chrome extension, you can just click the Clips icon, hit record, and start talking. Visually demonstrate your issue, go through the flow, point out what’s broken. Clips will capture everything on your screen, plus network requests, browser logs, client errors, and all the details around them. And it redacts sensitive information. Then it gives you a link you can send to humans so they can play it and take a look. Or, more importantly, just give it to your agents by just pasting the URL to them. The link has special metadata for agents so just from the URL, the agent can pull all information from the clip automatically. No plugin or MCP server required. That means it can "see and hear" what’s in the video - read the transcript, grab snapshots at any timestamp, and inspect the logs and network requests that were shared with it. So whether you want to quickly demo an issue and send all that context to an agent, or get better bug reports from teammates, recording and sending Clips makes that super easy. Unlike expensive apps like Loom, this is all 100% free and open source. The framework that powers this, plus a bunch of other free applications, is open source too. You can just sign up and use it, or fork it and customize it to your needs. This, in my opinion, is the future of software. Rather than bloated SaaS that charges you a ton of money and still doesn’t even have the things you need, we get free open source canonical apps that you can fork and customize in any way you want. I'll link to all this stuff in the replies. If you try it, let me know your feedback.

Steve (Builder.io)

60,399 Aufrufe • vor 1 Monat