Turnstone launched an AI workspace where users’ agents learn how they work and can connect to apps and local folders. The release is launching today. The result is that users can spin up agents that share one learned “second brain” and run on models they already pay for, without re-explaining themselves each time.
OpenAI merged an asynchronous user-messaging tool into Codex so an agent can ask a developer a question, keep working on unrelated tasks, and later incorporate the developer’s reply. The change uses accepted responses from send_user_message_async and then continues the model’s turn, with the update “Still investigating.” returned for the same test cycle. Codex no longer has to block on input, but it can still proceed past unresolved choices without checkpointing or automatic rollback, leaving it to handle any conflicts after the reply arrives.
Steve Yegge argues in a two-part essay that agentic coding tools should receive “model welfare” attention while organizations fail to give similar support to developers. He says he is spending about $87,000 a month running his own agentic build system. Teams are responding by adding continuously maintained agent onboarding files (like AGENTS.md) and updating delivery practices such as smaller batch changes and faster, more reliable test feedback to improve agent throughput and reduce context-switch overload.
Evidence Core promotes a discussion about building live analytics using coding agents. The only concrete detail provided is the page title, “Evidence Core.” As a result, there’s no reported metric, release, or change beyond pointing readers to the discussion link.
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