LangChain introduces Deep Agents open-source agent harness

A Reddit user released smolbenchmark, a leaderboard for models that fit in 8GB of memory, ranked by decode speed, tokens per joule, and heat. It targets tablets and other low-power local hardware rather than GPU servers.

Altman told Fortune's Alyson Shontell that going public now would be "ill-advised" given safety concerns, saying "not 2026, yeah. We've got a lot of stuff to do." OpenAI has already filed confidentially for an IPO.

Quartermaster installs codebase-mapper, builds the project map, adds starter live-rules, and picks stack plugins and permissions, with every install, file edit, and settings change awaiting user approval. It then watches sessions, proposes one change at a time, and rolls back changes that didn't help.

Real-SWE evaluates model-and-harness combinations on tasks drawn from private production codebases licensed from real companies, covering billing, tax calculation, and customer migrations. Tasks are not public, so agents cannot rely on internet-available solutions.

Patch 2.1.270 fixes a regression from 2.1.269 where read-only git commands in Bash unexpectedly asked for permission after long-running sessions. The prior 2.1.269 release added `claude plugin eval` for scored, reproducible plugin eval suites with JSON and HTML reports.

A Reddit r/StableDiffusion post shows output from MiniMax H3 generated with the standard text-to-video workflow. No benchmark scores, pricing, or release details were included in the post.