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We’re introducing Cursor 3. It is simpler, more powerful, and built for a world where all code is written by agents, while keeping the depth of a development environment. pic.twitter.com/rXR9vaZDnO
— Cursor (@cursor_ai) 2 avril 2026
We’re introducing Cursor 3. It is simpler, more powerful, and built for a world where all code is written by agents, while keeping the depth of a development environment.
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Thank you for the mention and for sharing this excellent 3-page visual guide, @TerenceLeungSF! Looking forward to seeing how others are applying these practices. #ClaudeAI #AIProductivity #AI Terence Leung (@TerenceLeungSF) Start Coworking with Claude I have put together this three-page visual guide. My hope is that we can all go from zero to supercharged in literally 5 minutes together. What is inside the full infographic: • Exact 5-minute setup with the CONTEXT folder • Which model to pick when • The 4 modes that matter most • Power workflows and pro tips I wish I knew on day one This can the system we use every single day to build up trust with Claude to be the highest-performing teammate. Save it. Build the folder. Come back and tell me what is working for you so we can keep learning together. Who else is going all-in on Claude as their daily AI coworker? Please let us know how and the hurdles and benefits. #ClaudeAI #AIProductivity #LearnClaude @mvollmer1 @morgfair @ChuckDBrooks @Nicochan33 @enricomolinari @NancySinatra @Ronald_vanLoon @alvinfoo @KirkDBorne @Hana_ElSayyed @JimHarris @MikeQuindazzi @Shi4Tech @mhcommunicate @ipfconline1 @kashthefuturist @rwang0 @HeinzVHoenen @YuHelenYu @BetaMoroney @antgrasso @kuriharan @PawlowskiMario @EvanKirstel @HaroldSinnott @terence_mills @FrRonconi @TamaraMcCleary @UrsBolt @pascal_bornet @HeinzVHoenen @SpirosMargaris @richardturrin @Xbond49 @psb_dc @rshevlin @JimMarous @IanLJones98 @Khulood_Almani @enilev @GlenGilmore @DeepLearn007 @KamLardi @debashis_dutta @sallyeaves @EstelaMandela @NevilleGaunt @IngridVasiliu @Eli_Krumova @baski_LA — https://nitter.net/TerenceLeungSF/status/2039394402993569821#m
→ View original post on X — @terenceleungsf, 2026-04-02 18:00 UTC
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🚀 Today we’re launching Trent’s Security Advisor for Lovable. Lovable gives builders a strong security baseline. 💪 Trent adds what’s been missing: continuous, in-context security advice while your app evolves. ✅ Ongoing code analysis ✅ Prioritized mitigation plans ✅ Direct fixes in Lovable via MCP ✅ No manual triage ✅ No security expertise required You build with Lovable. You secure with Trent. Read more ↓ trent.ai/blog/trent-security… Ready to secure your agent or app? Sign up for early access today. #CyberSecurity #AI #Lovable #MCP
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My AI already wrote some words about it. We should talk about how AI is about to change news. https://
alignednews.com/ai
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TBPN gets bought. My AI picks up the news and writes about it fast: https://
alignednews.com/ai You can't read 10,000 posts in 30 minutes. AI can.
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Google just released Gemma 4, and from an outside perspective, it is a massive leap for the open-source community. They have successfully packaged Gemini 3 technology into a highly capable, fully open agentic model. What is genuinely impressive is the licensing. It ships
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harness eng day 4: production readiness deployed agents need to be resilient! model timeouts, rate limits, tool failures are inevitable @langchain's ModelRetryMiddleware handles retry logic with configurable retry count, backoff factor, and initial delay
→ View original post on X — @langchain, 2026-04-02 17:38 UTC
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The thing that surprised me: we didn't set anything up.
— AI Highlight (@AIHighlight) 2 avril 2026
No API keys. No deployment. No "connect your OpenAI account."
We opened it, talked, and our AI team started working. https://t.co/UajMFjUnKX
The thing that surprised me: we didn't set anything up. No API keys. No deployment. No "connect your OpenAI account." We opened it, talked, and our AI team started working. ZooClaw (@ZooClawAI) One tool. A whole team inside. Introducing ZooClaw 🐾 — https://nitter.net/ZooClawAI/status/2039742640233894114#m
→ View original post on X — @aihighlight, 2026-04-02 17:36 UTC
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Most coding agents do not fail because they are weak. They fail because they are hard to inspect. The real problem with coding agents is not autonomy. It’s easy to make them “autonomous”. The problem is observability. A lot of tools still look impressive right until the moment they say “done”, move on, and when you check, the thing is half-built, wrong, or never happened. It happens to me almost every day, and if you don’t check for it, you might as well skip half your to-do tasks… That is why I care so much about observability and control in agentic coding. Not just more tool calls. Not just more agents. Not just more autonomy. I want to see the diff. I want to review the exact line and ensure it was done, and understand how. I want to send (only relevant) feedback back into the context. I want to compare models on a real task in my repo instead of guessing. That is what I found interesting in the rebuilt Kilo Code extension on VS Code. Yes, the parallel subagents and tons of features are cool. But the part I care about more is the (human) review loop around them. You can inspect what each agent changed, comment directly on the diff, and send those comments back as structured context. That matters. Because the value of these tools is not just in generation. It is correction. It is debugging weird hallucinations (and other LLM weaknesses). It is catching the moments where the model says “I made it” and absolutely did not. And honestly, model comparison on real tasks is underrated too. Benchmarks are nice. Your repo and actual use case are way nicer. If a tool helps you compare quality, behaviour, and likely cost on your own codebase, that is real value. A 2026 tool NEEDS to be focusing around models’ weaknesses, which starts with observability and monitoring. And, unfortunately, observability, control, and evaluation are still missing layers in many agent products. I highly recommend trying it out and taking the time to review agents’ code in general! I put the link in the comments if you want to try it. What do you care about more in coding agents today: more autonomy, or more observability?
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The LangSmith Signal: Azure's share of OpenAI traffic grew nearly 4x in under 3 months. We're sharing how devs are building agents, by the numbers. While most orgs started by connecting directly to OpenAI, over the past 10 weeks we've watched Azure's share of that traffic grow from 8% to 29%. We've analyzed this trend via LangSmith Observability data across more than 6.7 billion agent runs. Our hypothesis: 💡 Early adopters moved fast and went direct, but the enterprise wave is now arriving in force 💡 Azure gives teams the compliance, security, and procurement infrastructure they already have in place 💡 Azure traffic 4x-ing in 10 weeks likely indicates AI development is maturing quickly
→ View original post on X — @langchain, 2026-04-02 17:00 UTC