You might see what I did with https://
alignednews.com/ai — I have a Notebook LM feed already prepared for you, and a feed for your Hermes too.
TOOLS
-
Notebook LM Feed for AI News Aggregation
By
–
-
Using Screenshots and AI Codex for Tweet Analysis
By
–
Yeah sometimes I just make a screenshot of the tweet and drag it into codex and copy paste the response.
-
OpenClaw AI Auto-Updater System Documentation
By
–
We have an auto-updater. https://
docs.openclaw.ai/install/updati
ng#auto-updater
… -
AI Model for Business System Development
By
–
The model my nerd is using to build my business system. https://t.co/hlfYsR152N
— Robert Scoble (@Scobleizer) 8 avril 2026The model my nerd is using to build my business system.
-
OpenClaw 2026.4.7 Release: Inference, Editing, Memory Wiki
By
–
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
-
OpenClaw 2026.4.7 Release: AI Inference, Media Editing, Knowledge System
By
–
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…
→ View original post on X — @ceobillionaire, 2026-04-08 03:06 UTC
-
AI Awakening Class Kickoff with Steve Jurvetson at Stanford
By
–
What an awesome way to start my AI Awakening class at Stanford! The legendary @FutureJurvetson has a knack for seeing around corners thanks to his deep technical knowledge. I can't wait to see the projects the students deliver in 10 weeks. Steve Jurvetson (@FutureJurvetson) 🤖 Just did the kickoff guest lecture at Stanford Business School for "The AI Awakening" — a new class cross-listed with CS where the students will use agentic AI to forge new businesses in 3-person teams. So I vibe coded a rocket launch tracking calendar app that integrates launches big and small (from SpaceX to the local LUNAR rocketry club). It took 4 minutes for me + 30 minutes of compute: rocklaunch-rptzu8y3.manus.sp… We discussed many topics, including the new "society of thought" paper that dropped 40 years after Minsky's Society of Mind, and five years after Hawkins' memory-prediction framework in A Thousand Brains: science.org/doi/10.1126/scie… — https://nitter.net/FutureJurvetson/status/2041693675877756999#m
→ View original post on X — @ceobillionaire, 2026-04-08 02:57 UTC
-
Creative Writing with Mythos AI Without Complex Prompting
By
–
Creative and unique writing from Mythos without complicated user prompting.
-
LangSmith Billboards Launch Campaign for Agent Optimization
By
–
I love these almost as much as i love using langsmith https://t.co/WJVg1aFPsE
— Hayden Wolff (@HaydenWolff1) 8 avril 2026I love these almost as much as i love using langsmith Harrison Chase (@hwchase17) LangSmith 🤝Fix your agents You'll see our billboards around SF and NYC over the next few months. The themes all point to the same problem: 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. If you spot one around, send it our way! — https://nitter.net/hwchase17/status/2041546634895757684#m
-
LangSmith Enables Agent Tracing and Optimization Loop
By
–
as always, it's an exciting time to be working at LangChain! https://t.co/JrgR2YMT4Q
— Sam Crowder (@samecrowder) 8 avril 2026as always, it's an exciting time to be working at LangChain! LangChain (@LangChain) 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. — https://nitter.net/LangChain/status/2041656189860393383#m