Code beginners with Claude: everyone says to create 7 files first. You only need one, and Claude builds the rest itself. Here's how:
TOOLS
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NVIDIA Metropolis VSS 3: Video Search and Summarization with 16 New Skills
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NVIDIA Metropolis Blueprint for video search and summarization (VSS) 3 is here.
— NVIDIA AI (@NVIDIAAI) 24 juin 2026
Now your coding agent can analyze massive live streams and libraries of videos with a simple natural language prompt. Here's what's new:
– 16 new agent skills: Search, summarize, alert, report,… pic.twitter.com/UojjUu8orkNVIDIA Metropolis Blueprint for video search and summarization (VSS) 3 is here. Now your coding agent can analyze massive live streams and libraries of videos with a simple natural language prompt. Here's what's new: – 16 new agent skills: Search, summarize, alert, report,
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My AI agent reads 30,000 posts daily and picks best
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That's cool. I did the same to build: https://
alignednews.com/ai (my agent reads 30,000 posts a day and picks the best). I can't wait to see where you take this. I need to do more like this. -
GitHub blocked by output policy in Claude Code
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Claude Code for the web has just started saying "GitHub is blocked by the output policy", which is a big problem for me because most of my prompts there start with things like "clone simonw/sqlite-utils to /tmp to see the docs in
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Voyager 1.6 divides AI deployment into compile and run phases
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Deploying AI models to embedded targets usually means a full SDK on a device that doesn't necessarily have room for it. So Voyager 1.6 splits that workflow in two. You compile your model on a development machine using axelera-devkit, which produces an .axm file. Then you run it
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New Siri will replace small Google searches for hotkeys
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New Siri is going to eat up so many of the small Google searches. All of the “how do i…” “whats the hotkey for…” Just works.
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Brain reads threads and provides a complete deliverable
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Users can mention Brain on any task, doc, or discussion to read the entire thread, extract from connected apps like Google Drive, GitHub, and Slack via MCP, and then provide a complete deliverable. Try it.
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Closing the Agent Loop with LangSmith and Context Hub
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"Most agents don't learn, they just leave traces."
— LangChain (@LangChain) 24 juin 2026
In 12 minutes, @jakebroekhuizen breaks down how to actually close the loop.
Surface issues with LangSmith Engine
Write memory updates back to Context Hub
Let the agent actually improve between runs
If you're thinking about how… https://t.co/aIfMwT33hM pic.twitter.com/QcjKez5SQ4Most agents don't learn, they just leave traces. In 12 minutes,
@jakebroekhuizen
explains how to actually close the loop. Surface issues with the LangSmith engine
Write memory updates to the Context Hub
Let the agent -
Give AI Agents Persistent Memory with LangGraph and MongoDB
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3/ Last → users HATE forgetful chatbots. You must give your agents a persistent brain. The 'Memory for AI Apps' module teaches you to use LangGraph and MongoDB to build stateful AI apps with isolated, long-term memory across sessions. Sweet. > https://
fandf.co/4uY0nN3 -
Vector Search Perf module for slow AI retrieval diagnosis
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2/ Next problem → sluggish AI retrieval. Scaling it up is notoriously difficult. This Vector Search Perf module walks you through diagnosing slow queries with Atlas Metrics. PLUS actually managing memory sizing and quantization in full production > https://
fandf.co/4b6Q3uW