ThinkingCap - The Local Coding Model

In this video, Sam Witteveen looks at ThinkingCap, a fine-tune of the Qwen3.6-27B model. BottleCap's goal was intentionally conservative: do not try to make the model smarter or teach it new capabilities. They wanted to preserve knowledge, reasoning ability, answer quality, conversational style, instruction following, and safety behavior.

The only thing they wanted to change was the amount of computation spent reaching an answer. In other words: keeping the same model, and making sure it overthinks less.

Anthropic Just Fixed Graph Engineering's Greatest Flaw

AI LABS explores the technical shift from loop engineering to graph engineering in AI workflows. This guide details how to implement robust verification strategies, skill orchestration, and browser-based testing to improve agent reliability and manage complex task outputs effectively.

Boris Cherny: We Cut 80% of Claude Code’s Prompt

Fresh off the launch of Opus 5, Claude Code creator Boris Cherny joins Diana Hu at Startup School 2026 to talk about what the newest models can do, how Claude Code came to be, and what it means to build products when the underlying capabilities keep accelerating.

MCP just got its biggest update ever — here’s what changes
for AI agents

The Model Context Protocol, the open standard that has quietly become the connective tissue between AI agents and the world's software, is getting its largest update since Anthropic released it twenty months ago — a sweeping architectural revision that its maintainers and backers say finally makes agentic AI ready for massive enterprise production deployments.

The update, released today under the stewardship of the Agentic AI Foundation (AAIF), a directed fund under the Linux Foundation, finalizes MCP's transition to a fully stateless architecture, hardens its authentication model against a known class of attacks, establishes a formal 12-month deprecation policy, and graduates two headline capabilities — interactive server-rendered interfaces and long-running asynchronous tasks — into official protocol extensions.

Anthropic launches Opus 5

On Friday, Anthropic launched its Opus 5 model, the newest version of its long-standing heavyweight model. While smaller than Fable 5, the model will be both cheaper and less restrictive than Fable, likely making it preferable in most use cases.

Opus 5 is launching only two months after Opus 4.8, which became available on May 28. Mythos 5, Fable 5, and Sonnet 5 all launched in June, leaving only the lightweight Haiku model still waiting for an upgrade to the 5 series.

Poolside drops Laguna S 2.1, an open-weight coding model
that beats rivals 10x its size

Poolside, the San Francisco AI lab that has spent most of its three-year existence quietly selling coding models to governments and defense agencies, released its most capable model to date — and made an unusually aggressive bet that radical transparency, not raw scale, is how a smaller lab competes at the frontier.

The model, Laguna S 2.1, is a 118-billion-parameter Mixture-of-Experts (MoE) system that activates only 8 billion parameters per token, supports a context window of up to 1 million tokens, and — according to benchmarks published by the company — matches or beats open models several times its size on agentic coding tasks. The weights are available immediately on Hugging Face under the permissive OpenMDW-1.1 license.

AMD Ryzen AI Halo - 100% Local AI

Sam Witteveen explores the capabilities of the new AMD Ryzen AI Halo, which features 128GB of unified memory. The demonstration highlights how this architecture enables local operation of large language models, image generation tools, and fine-tuning workflows, while comparing the practical benefits of unified memory against traditional workstation setups with discrete GPUs.