/AI Weekly/Issue 158

Issue #158 14 stories

Global AI Weekly

Is AI lock-in coming for enterprises?

Published Tuesday, July 14, 2026

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Highlights

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Research

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Global Workspace in Language Models: Anthropic research summary
linkedin.com

Global Workspace in Language Models: Anthropic research summary

One of our chapter leads, Veronika Kolesnikova, wrote an excellent summary of Anthropic's latest interpretability research on the newly discovered "J-space" in Claude. The research explores how language models appear to maintain an internal workspace that supports deliberate reasoning and coordination between concepts. Veronika breaks down the findings into an accessible overview, explains the connection to Global Workspace Theory, and discusses why this research is an important step toward more interpretable, trustworthy, and safer AI systems.

How to Use RLMs in Deep Agents
langchain.com

How to Use RLMs in Deep Agents

Recursive language models (RLMs) fix context rot by having agents write code that dispatches subagents over context chunks instead of pumping everything in one context window. Deep Agents now implements this through dynamic subagents and a lightweight code interpreter, letting agents programmatically fan out work like grep, map, and reduce over large inputs. We benchmark the approach on OOLONG, a long-context reasoning task, and show it holds up where turn-by-turn agents start to break down.

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Video

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The Evolution of Agents at Microsoft and Everywhere
youtube.com

The Evolution of Agents at Microsoft and Everywhere

Agents are changing fast. They are moving from basic chat tools to systems that can plan work, use integrations, hand tasks to other agents, and operate inside real apps and workflows. We’ll look at the new way to build and use agents today through concrete demos, not slides, and show what actually makes them useful in practice. We’ll also see how building agents is becoming accessible to a much broader set of people, not just developers, as these capabilities show up directly in everyday tools. Along the way, we'll introduce the use of rubrics to reason about agent behavior, reliability, and control as agents move into real-world use.

Trace Every Claude Code Session in LangSmith in Minutes
youtube.com

Trace Every Claude Code Session in LangSmith in Minutes

Amy Lu from the LangChain product team walks through configuring Claude Code so every session traces straight into LangSmith. You'll see the exact plugin install and settings file needed to capture every message, tool call, and sub agent run, then how to read that trace and follow a full multi-turn session in the Threads tab. Chapters: 0:00 Why your Claude Code agent's black box moments cost you debugging time 0:29 Three things you need before you start 0:44 Installing the LangSmith tracing plugin 1:10 Pointing the plugin at LangSmith with one settings file 1:21 The settings file, line by line 1:39 Running Claude Code with tracing turned on 1:49 Viewing your first trace in LangSmith 2:06 Following a full session in the Threads tab 2:17 Recap: three commands and one JSON block 2:25 Troubleshooting and what's next Docs: https://docs.langchain.com/langsmith/trace-claude-code

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Articles

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Upcoming Events

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Upcoming Events Around the World
globalai.community

Upcoming Events Around the World

From local meetups to full-day conferences, the Global AI Community brings developers, architects, founders, and AI enthusiasts together to learn, build, and connect. Discover hands-on workshops, expert talks, community gatherings, and flagship events like AgentCon, AgentCamp, and Global AI Construct. Whether you are exploring AI for the first time or building production-ready agentic systems, you will find opportunities to sharpen your skills, meet like-minded people, and become part of a thriving global community.

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Code

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Podcast

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Last Week in AI
open.spotify.com

Last Week in AI

This week's Last Week in AI covers several of the biggest developments across the AI landscape. Highlights include Anthropic's rollout of Claude Sonnet 5 with stronger coding capabilities and enhanced safety measures, Google's new NotebookLM video summaries and Nano Banana 2 Lite image model, DeepSeek's continued expansion, and Etched's push into AI inference hardware. The episode also explores emerging open-source models and benchmarks shaping the next generation of AI systems.

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