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Make your CLI 10x more powerful with custom subagents! Mistral Vibe is an open-source coding agent that runs in your terminal. Most terminal agents give you one assistant that does everything. With Vibe, you can build custom subagents for targeted tasks like deploy scripts, PR reviews, and test generation,...

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10,483 просмотров • 7 месяцев назад •via X (Twitter)

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Mistral Vibe 2.0 is now available on Le Chat Pro and Team plans. Build, maintain, and ship code faster with the terminal-native coding agent by Mistral AI. Here’s what’s new 🧵
1:18

Mistral Vibe 2.0 is now available on Le Chat Pro and Team plans. Build, maintain, and ship code faster with the terminal-native coding agent by Mistral AI. Here’s what’s new 🧵

Vibe

392,740 просмотров • 9 месяцев назад

.Postman is now natively available in your favorite coding agent! The new Postman CLI is designed to bring API engineering for agents: 1️⃣ Works in Git and your code repo - Just drop Postman where your agent lives and works. 2️⃣ No GUI - Work in your coding agent. Bring up the Postman UI for review and approval. 3️⃣ No sign-up - Get started right away. Sign-up when you have to save your work and want more. Install once, work in your agent. Run npm install -g postman-cli, then postman init. This loads Postman's skills into your coding agent so it can create collections, write tests, and much more. Available as a plugin for all coding agents! The skills cover the API lifecycle: find APIs your org already has, generate tests that catch regressions, mock an API before it exists, watch live endpoints for downtime and drift, run checks in CI on every commit, and run performance tests. You can also extend the abilities of your agent with the Context Graph. An agent often sees only the code that is accessible to them. The Context Graph API gives it a map of your team's infrastructure, APIs, and services, and how they depend on each other. As your agent works, you stay the reviewer. Your agent does the work from the command line. Open Postman when you want to review or approve it. Check out more at
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.Postman is now natively available in your favorite coding agent! The new Postman CLI is designed to bring API engineering for agents: 1️⃣ Works in Git and your code repo - Just drop Postman where your agent lives and works. 2️⃣ No GUI - Work in your coding agent. Bring up the Postman UI for review and approval. 3️⃣ No sign-up - Get started right away. Sign-up when you have to save your work and want more. Install once, work in your agent. Run npm install -g postman-cli, then postman init. This loads Postman's skills into your coding agent so it can create collections, write tests, and much more. Available as a plugin for all coding agents! The skills cover the API lifecycle: find APIs your org already has, generate tests that catch regressions, mock an API before it exists, watch live endpoints for downtime and drift, run checks in CI on every commit, and run performance tests. You can also extend the abilities of your agent with the Context Graph. An agent often sees only the code that is accessible to them. The Context Graph API gives it a map of your team's infrastructure, APIs, and services, and how they depend on each other. As your agent works, you stay the reviewer. Your agent does the work from the command line. Open Postman when you want to review or approve it. Check out more at

Abhinav Asthana

494,079 просмотров • 1 месяц назад

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣
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Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

rody

18,089 просмотров • 1 месяц назад

Mistral Vibe CLI is an open-source command-line coding assistant powered by Devstral. It explores, modifies, and executes changes across your codebase using natural language. Also under Apache 2.0. Install via: uv tool install mistral-vibe
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Mistral Vibe CLI is an open-source command-line coding assistant powered by Devstral. It explores, modifies, and executes changes across your codebase using natural language. Also under Apache 2.0. Install via: uv tool install mistral-vibe

Mistral AI

145,148 просмотров • 11 месяцев назад

🎄 We've shipped Skills for Vibe CLI: your dev expertise and rules, bundled and reusable across projects. Plus reasoning model support and native terminal themes. Try Vibe CLI now and happy shipping! → uv tool install mistral-vibe
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🎄 We've shipped Skills for Vibe CLI: your dev expertise and rules, bundled and reusable across projects. Plus reasoning model support and native terminal themes. Try Vibe CLI now and happy shipping! → uv tool install mistral-vibe

Mistral AI

91,481 просмотров • 10 месяцев назад

- agent skill for UI direction - 300+ motion effects for vibe coders - 500+ open-source animated React icons - 290+ vibe coding apps, agent skills, subagents and MCPs - 600+ curated website designs
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- agent skill for UI direction - 300+ motion effects for vibe coders - 500+ open-source animated React icons - 290+ vibe coding apps, agent skills, subagents and MCPs - 600+ curated website designs

Csaba Kissi

11,864 просмотров • 1 месяц назад

THIS FREE OPEN-SOURCE REPO GIVES YOU A SELF-HOSTED PERSONAL AI AGENT WITH MEMORY, WEB SEARCH, SUBAGENTS AND SCHEDULED AUTOMATIONS. NANOBOT RUNS WITH YOUR OWN API OR LOCAL MODEL AND CAN EVEN USE YOUR TERMINAL TO GET REAL WORK DONE.
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THIS FREE OPEN-SOURCE REPO GIVES YOU A SELF-HOSTED PERSONAL AI AGENT WITH MEMORY, WEB SEARCH, SUBAGENTS AND SCHEDULED AUTOMATIONS. NANOBOT RUNS WITH YOUR OWN API OR LOCAL MODEL AND CAN EVEN USE YOUR TERMINAL TO GET REAL WORK DONE.

0xMarioNawfal

42,564 просмотров • 1 месяц назад

My TRAE Agent is cuter and smarter than yours… 😎 With TRAE 2.0, you can now: 🛠 Define custom roles, tasks, and tools for each agent 🤝 Combine agents to co-build in the same project 🎨 (NEW) Pick from 100+ pixel-style avatars to match their vibe 🧵Thread below for example agents to start building your dream AI team
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My TRAE Agent is cuter and smarter than yours… 😎 With TRAE 2.0, you can now: 🛠 Define custom roles, tasks, and tools for each agent 🤝 Combine agents to co-build in the same project 🎨 (NEW) Pick from 100+ pixel-style avatars to match their vibe 🧵Thread below for example agents to start building your dream AI team

TRAE

22,029 просмотров • 1 год назад

Most AI coding setups right now look something like this: one agent in a terminal, another in a browser tab, a chat window somewhere else, and you in the middle copy-pasting diffs like a very tired air traffic controller. JetBrains just launched something aimed right at that mess. It's called JetBrains Air, and it lives inside their IDEs. The short version: Air lets you direct multiple coding agents, run their tasks in parallel, and review their work without ever leaving your IDE. Here's what stood out to me: 👇 1. You pick the agents. Air isn't tied to a single agent or provider. You can use the ones you already like. That matters more than it sounds, because the "best" coding agent changes every few months, and nobody wants to rebuild their whole workflow each time. 2. Parallel work without losing track. You can run several agent sessions at once, even across different projects. Air shows you where your attention is needed, so you're not hopping between tabs to find out which agent is stuck. 3. You stay in control. You can follow what each agent is doing, give it input, inspect the changes, and review the output before accepting anything. Nothing lands in your codebase just because an agent felt confident. 4. The agents get IDE smarts too. This is the part I find most interesting. JetBrains IDEs already have great code navigation, refactoring, testing, and debugging. With Air, both you and your agents work with that context. So the agents aren't guessing blind inside a chat box, and when something needs a human, the real tools are right there. The bigger idea here is that agents become part of your development workflow instead of a separate chat you keep switching to. There's also a nice bonus. For a limited time, JetBrains is offering Junie Lite for free (fair use applies). It's their own coding agent paired with a highly efficient model. It isn't pitched as a frontier-level agent. Think of it as a solid, free baseline for trying out Air and running everyday tasks. Air works in any JetBrains IDE and is in early access right now. If you write code with agents, give it a try: #ad
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Most AI coding setups right now look something like this: one agent in a terminal, another in a browser tab, a chat window somewhere else, and you in the middle copy-pasting diffs like a very tired air traffic controller. JetBrains just launched something aimed right at that mess. It's called JetBrains Air, and it lives inside their IDEs. The short version: Air lets you direct multiple coding agents, run their tasks in parallel, and review their work without ever leaving your IDE. Here's what stood out to me: 👇 1. You pick the agents. Air isn't tied to a single agent or provider. You can use the ones you already like. That matters more than it sounds, because the "best" coding agent changes every few months, and nobody wants to rebuild their whole workflow each time. 2. Parallel work without losing track. You can run several agent sessions at once, even across different projects. Air shows you where your attention is needed, so you're not hopping between tabs to find out which agent is stuck. 3. You stay in control. You can follow what each agent is doing, give it input, inspect the changes, and review the output before accepting anything. Nothing lands in your codebase just because an agent felt confident. 4. The agents get IDE smarts too. This is the part I find most interesting. JetBrains IDEs already have great code navigation, refactoring, testing, and debugging. With Air, both you and your agents work with that context. So the agents aren't guessing blind inside a chat box, and when something needs a human, the real tools are right there. The bigger idea here is that agents become part of your development workflow instead of a separate chat you keep switching to. There's also a nice bonus. For a limited time, JetBrains is offering Junie Lite for free (fair use applies). It's their own coding agent paired with a highly efficient model. It isn't pitched as a frontier-level agent. Think of it as a solid, free baseline for trying out Air and running everyday tasks. Air works in any JetBrains IDE and is in early access right now. If you write code with agents, give it a try: #ad

Mushfiq Sajib

40,728 просмотров • 1 месяц назад

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:
2:50

New course: Gemini CLI: Code & Create with an Open-Source Agent, built with Google Cloud Tech/Gemini CLI and taught by Jack Wotherspoon. Agentic coding assistants like Gemini CLI are transforming how developers work. This short course teaches you to use Google's open-source agent to coordinate local tools and cloud services for coding and non-coding workflows. Gemini CLI works from your terminal, so it works with your local files and development tools. You can also connect it to services through MCP. Then provide high-level instructions, and it autonomously plans and executes complex workflows. Skills you'll gain: - Build website features and automate code reviews with GitHub ActionsCreate data dashboards that combine local files with cloud data sources - Use MCP servers and extensions to orchestrate workflows across GitHub, Canva, and Google Workspace - Generate social media content from multimedia files like conference recordings I particularly appreciate that Gemini CLI is open-source. You can see exactly how it works, read the prompts it uses, and understand its architecture. The community has contributed thousands of pull requests. Since Gemini 3’s release I've found Gemini CLI highly capable - this is a tool worth having in your toolbox! Whether you're prototyping applications, automating workflows, or working with multimedia content, join to learn to delegate complex tasks and build faster:

Andrew Ng

126,315 просмотров • 9 месяцев назад

Important new course: Agent Skills with Anthropic, built with Anthropic and taught by Elie Schoppik! Skills are constructed as folders of instructions that equip agents with on-demand knowledge and workflows. This short course teaches you how to create them following best practices. Because skills follow an open standard format, you can build them once and deploy across any skills-compatible agent, like Claude Code. What you'll learn: - Create custom skills for code generation and review, data analysis, and research - Build complex workflows using Anthropic's pre-built skills (Excel, PowerPoint, skill creation) and custom skills - Combine skills with MCP and subagents to create agentic systems with specialized knowledge - Deploy the same skills across Claude Code, the Claude API, and the Claude Agent SDK Join and learn to equip agents with the specialized knowledge they need for reliable, repeatable workflows.
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Important new course: Agent Skills with Anthropic, built with Anthropic and taught by Elie Schoppik! Skills are constructed as folders of instructions that equip agents with on-demand knowledge and workflows. This short course teaches you how to create them following best practices. Because skills follow an open standard format, you can build them once and deploy across any skills-compatible agent, like Claude Code. What you'll learn: - Create custom skills for code generation and review, data analysis, and research - Build complex workflows using Anthropic's pre-built skills (Excel, PowerPoint, skill creation) and custom skills - Combine skills with MCP and subagents to create agentic systems with specialized knowledge - Deploy the same skills across Claude Code, the Claude API, and the Claude Agent SDK Join and learn to equip agents with the specialized knowledge they need for reliable, repeatable workflows.

Andrew Ng

891,429 просмотров • 9 месяцев назад

🇺🇸 xAI launched Grok Build, a coding agent that runs directly from your terminal, now in early beta for SuperGrok and X Premium Plus subscribers. It lets you plan and approve changes before anything runs, works with tools you already use like MCP servers and plugins, and can spin up multiple subagents working in parallel on larger tasks. Some users say it's already competing with Claude Code and GitHub Copilot Workspace. Source: xAI
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🇺🇸 xAI launched Grok Build, a coding agent that runs directly from your terminal, now in early beta for SuperGrok and X Premium Plus subscribers. It lets you plan and approve changes before anything runs, works with tools you already use like MCP servers and plugins, and can spin up multiple subagents working in parallel on larger tasks. Some users say it's already competing with Claude Code and GitHub Copilot Workspace. Source: xAI

Mario Nawfal

99,324 просмотров • 5 месяцев назад

holy f*ck, you WILL lose your job in 2027 if you don't learn this. not to AI. to the person next to you who runs 5 agents while you're still clicking through 1 app. one person with the right agent stack now does modeling, materials, design, video and research before your first meeting ends. 10 repos to learn before it's too late: 1. dream-loop - YOUR AI 3D ART DIRECTOR the agent imagines the final scene, builds it in Blender, and a critic agent checks it until it matches. 2. Blender Skills - PRO BLENDER WORKFLOWS FOR YOUR AGENT modeling, UVs and more as ready skills for Claude Code, Codex and Cursor. 3. TRELLIS.2 - ONE IMAGE IN, ONE 3D ASSET OUT detailed shapes with realistic PBR materials, by Microsoft. 4. Open Design - AN AI DESIGN STUDIO ON YOUR LAPTOP motion, prototypes, websites and apps with an agent. local-first and open source. 5. Impeccable - GIVE YOUR AGENT DESIGN TASTE critique, audit, polish and catch the AI slop before your client does. 6. HyperFrames - WRITE HTML, GET A VIDEO built for agents. your promo is now a file, not a week of editing. 7. Superpowers - MAKE YOUR AGENT WORK LIKE A SENIOR it plans before it builds, tests its own work and debugs instead of guessing. 8. Graphify - YOUR COMPANY'S MEMORY turns code, docs, SQL and PDFs into a knowledge graph your agent can actually query. 9. Browser Use - AN AGENT THAT USES THE WEB FOR YOU research, forms, dashboards. it clicks so you don't have to. 10. Google Workspace CLI - PUT YOUR AGENT INSIDE GMAIL, DRIVE AND SHEETS one tool for Drive, Gmail, Calendar, Sheets and Docs. the scary part? every repo here is public. your competitor just has to find this post before you do. and the toy head you're looking at? a giant see-through head packed with tiny smiling heads. 201 objects, 412,876 vertices, rendered in Blender Cycles. built with an AI agent. one of my latest 3D experiments. want to make one like it? LIKE + BOOKMARK + REPOST. comment "LEGO" and I'll send you the prompt.
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holy f*ck, you WILL lose your job in 2027 if you don't learn this. not to AI. to the person next to you who runs 5 agents while you're still clicking through 1 app. one person with the right agent stack now does modeling, materials, design, video and research before your first meeting ends. 10 repos to learn before it's too late: 1. dream-loop - YOUR AI 3D ART DIRECTOR the agent imagines the final scene, builds it in Blender, and a critic agent checks it until it matches. 2. Blender Skills - PRO BLENDER WORKFLOWS FOR YOUR AGENT modeling, UVs and more as ready skills for Claude Code, Codex and Cursor. 3. TRELLIS.2 - ONE IMAGE IN, ONE 3D ASSET OUT detailed shapes with realistic PBR materials, by Microsoft. 4. Open Design - AN AI DESIGN STUDIO ON YOUR LAPTOP motion, prototypes, websites and apps with an agent. local-first and open source. 5. Impeccable - GIVE YOUR AGENT DESIGN TASTE critique, audit, polish and catch the AI slop before your client does. 6. HyperFrames - WRITE HTML, GET A VIDEO built for agents. your promo is now a file, not a week of editing. 7. Superpowers - MAKE YOUR AGENT WORK LIKE A SENIOR it plans before it builds, tests its own work and debugs instead of guessing. 8. Graphify - YOUR COMPANY'S MEMORY turns code, docs, SQL and PDFs into a knowledge graph your agent can actually query. 9. Browser Use - AN AGENT THAT USES THE WEB FOR YOU research, forms, dashboards. it clicks so you don't have to. 10. Google Workspace CLI - PUT YOUR AGENT INSIDE GMAIL, DRIVE AND SHEETS one tool for Drive, Gmail, Calendar, Sheets and Docs. the scary part? every repo here is public. your competitor just has to find this post before you do. and the toy head you're looking at? a giant see-through head packed with tiny smiling heads. 201 objects, 412,876 vertices, rendered in Blender Cycles. built with an AI agent. one of my latest 3D experiments. want to make one like it? LIKE + BOOKMARK + REPOST. comment "LEGO" and I'll send you the prompt.

kiosa

126,564 просмотров • 1 день назад

how to build a 1-person AI company that: - runs locally - is 100% open source - has no human employees, only ai agents - lets every agent collaborate through email most people already know that multiple ai agents can work together. frameworks for that have existed for a while. the harder part is figuring out how to organize those agents in a way that actually makes sense. instead of building complicated workflows with dozens of connected nodes, this project treats your ai system like a real company. every agent has a specific job. every job reports to a manager. instead of talking to every agent yourself, you only communicate with the manager, who delegates tasks to the right agents and brings the results back to you. just like a real business. that's exactly how alook works. each agent runs in its own claude code, codex, or opencode session. every agent has a clearly defined role and its own email inbox. they communicate with each other through email while everything runs locally on your own machine. your data stays on your computer. nothing is sent to someone else's servers. here's a simple example. imagine building an ai sales team. one agent becomes the sales manager. another researches companies and finds qualified leads. another writes outreach emails, handles replies, follows up with prospects, and reports the results. you don't need to coordinate any of this yourself. the manager agent handles the communication between the team and sends you one clear update. it's a much more natural way to build multi-agent systems because you're organizing ai the same way people organize companies. the entire project is open source. github link:
0:39

how to build a 1-person AI company that: - runs locally - is 100% open source - has no human employees, only ai agents - lets every agent collaborate through email most people already know that multiple ai agents can work together. frameworks for that have existed for a while. the harder part is figuring out how to organize those agents in a way that actually makes sense. instead of building complicated workflows with dozens of connected nodes, this project treats your ai system like a real company. every agent has a specific job. every job reports to a manager. instead of talking to every agent yourself, you only communicate with the manager, who delegates tasks to the right agents and brings the results back to you. just like a real business. that's exactly how alook works. each agent runs in its own claude code, codex, or opencode session. every agent has a clearly defined role and its own email inbox. they communicate with each other through email while everything runs locally on your own machine. your data stays on your computer. nothing is sent to someone else's servers. here's a simple example. imagine building an ai sales team. one agent becomes the sales manager. another researches companies and finds qualified leads. another writes outreach emails, handles replies, follows up with prospects, and reports the results. you don't need to coordinate any of this yourself. the manager agent handles the communication between the team and sends you one clear update. it's a much more natural way to build multi-agent systems because you're organizing ai the same way people organize companies. the entire project is open source. github link:

MIKE

19,938 просмотров • 4 месяцев назад

Create your Copy-Trading Agent with vibe-coding in Lucy. Input and monitor any wallet address, and let your agent automatically seize smart money routes 24/7. An agentic automated trading terminal should be democratic for everyone. See how easy it is to build now.
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Create your Copy-Trading Agent with vibe-coding in Lucy. Input and monitor any wallet address, and let your agent automatically seize smart money routes 24/7. An agentic automated trading terminal should be democratic for everyone. See how easy it is to build now.

Delysium - $AGI 🟨

15,771 просмотров • 1 год назад

GLM 5.4/ GLM 5.5 on the way... ZCode just got what might be its biggest update yet with the new Workflow mode, and it feels like a completely different experience! I asked it to orchestrate 10 subagents at once and now I can actually watch each one working independently, see how the tasks are progressing and follow the entire workflow in real time. What I love the most is the interface, everything is so well organized and being able to see exactly what each agent is doing makes the whole experience much better, especially when you're working on complicated projects with multiple agents. To give you an idea of how Dynamic Workflows works, instead of having an AI agent coordinate everything through chat, you now have code that coordinates the agents directly, which makes managing complex tasks much more structured. And when you combine this with Goal Mode, Execution Modes, support for multiple models and GLM's long context window, ZCode is becoming one of the most advanced tools I've tried in 2026 for large development projects that require multiple agents working together!
0:45

GLM 5.4/ GLM 5.5 on the way... ZCode just got what might be its biggest update yet with the new Workflow mode, and it feels like a completely different experience! I asked it to orchestrate 10 subagents at once and now I can actually watch each one working independently, see how the tasks are progressing and follow the entire workflow in real time. What I love the most is the interface, everything is so well organized and being able to see exactly what each agent is doing makes the whole experience much better, especially when you're working on complicated projects with multiple agents. To give you an idea of how Dynamic Workflows works, instead of having an AI agent coordinate everything through chat, you now have code that coordinates the agents directly, which makes managing complex tasks much more structured. And when you combine this with Goal Mode, Execution Modes, support for multiple models and GLM's long context window, ZCode is becoming one of the most advanced tools I've tried in 2026 for large development projects that require multiple agents working together!

Iam_

30,417 просмотров • 22 дней назад

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!
2:51

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!

Andrew Ng

467,452 просмотров • 6 месяцев назад

this is f*cking insane, that's what your agent looks like when it stops reading everything over and over Xerj launched Corpus Hub: 103 open-source knowledge corpora your agent can search instead of swallowing whole files the problem is simple, most agents dump entire documents into context just to find one paragraph you pay for every token, every single time with a corpus, the agent works differently: - it searches the corpus before opening anything - it pulls only the passages that answer the task - everything else stays out of the context window - it runs locally, so your files stay on your machine a bigger context window doesn't make an agent smarter, it just makes reading more expensive i gave my agent the same task with and without Xerj, here's the difference: > output tokens: 3× fewer > cost: $4.57 down to $1.98, 57% lower > tasks completed: 7/16 without Xerj, 16/16 with Xerj pick a corpus on connect it to your agent, then ask: "Work on this task using the connected corpus 1. Search the corpus before opening any full document 2. Pull only the passages you need and note where each one came from 3. If the corpus doesn't cover something, say so instead of guessing 4. At the end, list the passages you used and the files you never had to open" start with one corpus that matches your stack and one real task, then compare the token count before and after
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this is f*cking insane, that's what your agent looks like when it stops reading everything over and over Xerj launched Corpus Hub: 103 open-source knowledge corpora your agent can search instead of swallowing whole files the problem is simple, most agents dump entire documents into context just to find one paragraph you pay for every token, every single time with a corpus, the agent works differently: - it searches the corpus before opening anything - it pulls only the passages that answer the task - everything else stays out of the context window - it runs locally, so your files stay on your machine a bigger context window doesn't make an agent smarter, it just makes reading more expensive i gave my agent the same task with and without Xerj, here's the difference: > output tokens: 3× fewer > cost: $4.57 down to $1.98, 57% lower > tasks completed: 7/16 without Xerj, 16/16 with Xerj pick a corpus on connect it to your agent, then ask: "Work on this task using the connected corpus 1. Search the corpus before opening any full document 2. Pull only the passages you need and note where each one came from 3. If the corpus doesn't cover something, say so instead of guessing 4. At the end, list the passages you used and the files you never had to open" start with one corpus that matches your stack and one real task, then compare the token count before and after

Anatoli Kopadze

18,791 просмотров • 28 дней назад

🧠 Want to give your coding agent new capabilities? Use Agent Skills in Visual Studio Code! Agent skills let you package instructions and resources into reusable capabilities for your agent. Skills can be loaded on demand and called directly from chat using slash commands like /skill-name. Learn more:
0:26

🧠 Want to give your coding agent new capabilities? Use Agent Skills in Visual Studio Code! Agent skills let you package instructions and resources into reusable capabilities for your agent. Skills can be loaded on demand and called directly from chat using slash commands like /skill-name. Learn more:

Visual Studio Code

55,219 просмотров • 7 месяцев назад