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  • Using Screenshots and AI Codex for Tweet Analysis

    By

    @steipete

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    Yeah sometimes I just make a screenshot of the tweet and drag it into codex and copy paste the response.

    → View original post on X — @steipete

  • OpenClaw 2026.4.7 Release: Inference, Editing, Memory Wiki

    By

    @ceobillionaire

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    Second 🚢 of the day. OpenClaw🦞 (@openclaw) OpenClaw 2026.4.7 🦞 🔮 openclaw infer 🎬 music + video editing 💾 session branch/restore 🔗 webhook-driven TaskFlows 🤖 Arcee, Gemma 4, Ollama vision 🧠 memory-wiki: persistent knowledge, not just vibes Because “trust me bro” is not a knowledge system. github.com/openclaw/openclaw… — https://nitter.net/openclaw/status/2041714270212108657#m

    → View original post on X — @ceobillionaire, 2026-04-08 03:12 UTC

  • 6 Practical Tips for Building AI Agents with Claude and Codex

    By

    @scobleizer

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    Good tips: nitter.net/gkisokay/status/204062… Graeme (@gkisokay) Practical tips to save time and tokens when using Claude or Codex externally to build or debug your Hermes and OpenClaw agents. 1. After building externally, debrief Hermes/OpenClaw on every new feature In Hermes case, it owns the orchestration standards, memory architecture, and self-improving skill loops. Hermes itself should review any feature built outside to confirm it fits the framework before it runs. Do the same for OpenClaw as well, to ensure it fits its execution standards. 2. Scan the whole codebase when switching LLM models Don't assume a quick LLM swap will work. Ask Claude/Codex to audit every prompt string, config file, and env variable for stale model names. One missed reference will silently route to the wrong model, costing you hours of debugging. 3. Test viciously. Normally, agents fail new features on first runs Define the exact desired output, watch for it, and if it doesn't appear, keep iterating until it's consistent. Repetition is the only honest test. 4. Describe symptoms, not solutions Don't tell Claude/Codex how to fix it; describe what's wrong. "The memory isn't persisting between runs." Beat "rewrite the storage layer." Let it figure out the approach. You'll get a clearer answer and see where the actual problem is. 5. Paste the error, don't summarize it When receiving errors from your agent, use the exact error or full log dump every time. Claude reads noise better than you do, and the part you thought was irrelevant might be the part that matters. 6. If it breaks again later, return to the same session If the same feature fails weeks later, go back to the original Claude Code/Codex session before starting fresh. The context for what was built, why, and what was already tried is sitting there. Starting a new chat throws all of that away, and you'll loop the same decisions. These tips should address many of the recurring questions I've been receiving. Let me know if I can help you out further. — https://nitter.net/gkisokay/status/2040627715079098737#m

    → View original post on X — @scobleizer, 2026-04-08 02:46 UTC

  • AI Prompting Skills and Strategic Business Thinking Matter Most

    By

    @scobleizer

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    As a former strategist at Microsoft I like this trend where AI helps you prompt better. Just met with a new AI science company and believe it or not even smart people often don’t write great prompts. Strategic thinking is tough because you are dealing with unknowns from the start. Often we don’t know what to build and with newer AI (like the one I use) often need to be trained before they are highly useful. I talked with mine for almost three months before I released alignednews.com/ai I need a new business agent to help me get sponsors and hit up my connections on LinkedIn so will try this tonight. Vishal Virani (@Vishalvirani91) Rocket 1.0 is live. This is our first major step toward Vibe Solutioning. Vibe coding solved how to build. It never solved what to build, or why. That's the harder problem and the one where most products actually fail. @rocketdotnew connects the thinking and the building in one platform. Solve your hardest business question. Build from what you solved. Watch your competition while you work. Everything shares one context. Nothing resets between sessions. The video and blog explain it better than I can here. — https://nitter.net/Vishalvirani91/status/2041546557342855363#m

    → View original post on X — @scobleizer, 2026-04-07 23:16 UTC

  • LangSmith: Tracing and Evals for Agent Optimization

    By

    @langchain

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    LangSmith 🤝 San Francisco You don't know what your agents will do until you actually run them. What works in demos can break in the real world. Without tracing and evals, you're just guessing at why. Track what your agent actually does. Optimize and fix your agents. Then measure whether your fixes work. That loop is how agents get better, and LangSmith is built to power that workflow.

    → View original post on X — @langchain

  • Users Discover Non-Chat AI Interface Beyond Original Learning Tool Purpose

    By

    @scobleizer

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    I'm blown away at what ppl are using this for!! I built it as a learning tool. But people seem to really love using it as an AI interface that isn't chat that can work in their program of choice. Examples of usage so far: – A Mom building her first app on Lovable – A dentist debugging his OpenClaw setup – A photographer getting feedback in Lightroom – A person learning to animate SVGs in Framer – Founders keeping track of their todos. – Designers getting feedback in Figma – A student outlining her thesis in G-Docs – Traders analyzing live stock charts And A LOT of people using it to advise them on how to best reply to messages in Slack/Email. Super cool. The people yearn for a non-chat interface haha. Also, it's kinda crazy how as the founder you really don't know what the product is until you put it in the hands of users. The minute it's in the hands of others, it's theirs now! And that's really where you find out what it is. Farza 🇵🇰🇺🇸 (@FarzaTV) I built this thing called Clicky. It's an AI teacher that lives as a buddy next to your cursor. It can see your screen, talk to you, and even point at stuff, kinda like having a real teacher next to you. I've been using it the past few days to learn Davinci Resolve, 10/10. — https://nitter.net/FarzaTV/status/2041314633978659092#m

    → View original post on X — @scobleizer, 2026-04-07 22:08 UTC

  • Rocket 1.0 Launches: Persistent Context Between Sessions for Product Development

    By

    @datachaz

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    "NOTHING resets between sessions." Anyone who's ever copy-pasted a 3,000-word prompt into ChatGPT for the 50th time just to remind it what app you're building knows exactly how MASSIVE this is! Huge congrats to the @rocketdotnew team 🤘 Vishal Virani (@Vishalvirani91) Rocket 1.0 is live. This is our first major step toward Vibe Solutioning. Vibe coding solved how to build. It never solved what to build, or why. That's the harder problem and the one where most products actually fail. @rocketdotnew connects the thinking and the building in one platform. Solve your hardest business question. Build from what you solved. Watch your competition while you work. Everything shares one context. Nothing resets between sessions. The video and blog explain it better than I can here. — https://nitter.net/Vishalvirani91/status/2041546557342855363#m

    → View original post on X — @datachaz, 2026-04-07 22:02 UTC

  • Which AI models are you using in your apps?

    By

    @mattshumer_

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    What models are you using, in what apps? Do you have thinking turned all the way up?

    → View original post on X — @mattshumer_

  • AI-First Hiring Framework: From Surface Users to Full Ownership
    AI-First Hiring Framework: From Surface Users to Full Ownership

    By

    @alliekmiller

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    I stole this framework, and it has genuinely been one of the most helpful hiring and onboarding guides my team uses. Being AI-first means nothing without solving real business problems. It's not enough to just use AI. I know plenty of folks using AI dozens of times a day, 7 days a week, who are still working at a Level 2. Even worse, they have no idea they're stuck as a surface user. You have to use AI for faster experimentation. To shorten the iteration cycle. To improve the actual outcome. Without those three, you're just wasting tokens. Most people I interview are at a 3 (solution-oriented, but not action-oriented). I want everyone to start at a 4 (action-oriented with a sense of technical, user, and business tradeoffs). And when they earn trust, we move up to a level 5 (full ownership of the problem, solution, and continued management of the work). Using AI doesn't replace your critical thinking. It means the work you can pull off now wasn't on the table a year ago, and your job is getting bigger. Save this for your next new hire. Source: this was a framework first introduced to me by Alex (@businessbarista) who was introduced to it by Steph (@stephsmithio). I added the AI parts.

    → View original post on X — @alliekmiller, 2026-04-07 18:01 UTC

  • Conversation with Ashe about Building in Public and Codex

    By

    @romainhuet

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    Really loved this conversation with @ashebytes
    . Ashe is one of the most original and creative builders in the community. We talked about building in public, relational intelligence, second brains, and how you can just build things with Codex. Full episode out later this week!

    → View original post on X — @romainhuet