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…training recipe/data rather than architecture overhaul: @rasbt. Agents, harness engineering, and “local agents” momentum (Hermes/OpenClaw + model/harness training loops)Open-models-as-agent-engines is now mainstream positioning: Multiple…
…their thread. LangChain echoed the same shift with a new Deep Agents course and an open-source harness project in posts from @LangChain and @hwchase17. Google is also productizing this direction: Gemini API Managed Agents added background…
…and evals that can be used to measure and post-train agents over time (Vtrivedy10, hwchase17). LangSmith Engine also shipped >2× better performance on key internal benchmarks with better issue detection/clustering, SaaS and self-hosted…
…via Claude Code) @zachtratar; Cursor ships MCP Apps where agents render interactive UIs inside chat @cursor_ai. “Kill code review” debate: swyx frames removing human code review as a “Final Boss” of agentic engineering and SDLC inversion…
…harnesses, files, and secrets: Google updated Gemini managed agents with a new Antigravity-based harness plus two notably practical APIs: a Credentials API that keeps secrets out of model context via placeholders and trusted-domain egress…
…the how - while Navier-Stokes was done in 88 hours and 10,000 agents, these solutions were 3 hours of ChatGPT Pro on average. AI News for 10/5/2026-10/6/2026. We checked 12 subreddits, 544 Twitters and no further Discords. AINews’ website…
…FastConformer / RNN-T style design optimized for voice agents and streaming speech workloads (Piotr Zelasko, Together, fal availability). Anthropic’s Recursive Self-Improvement Framing and Internal AI-Coding Metrics Anthropic published the …
…fixing the “usability tax,” especially by @danshipper. 2. Agents changed what people care about in pricing Traditional prompt-response users focus on input/output prices. Agent builders focus on: cache reads long context reliability over…
…scaling. The system card reports scaling up to 100 parallel agents in Section 8.12. @scaling01 called it the first lab report of its kind. @maksym_andr highlighted it as evidence on multi-agent scaling laws. ProgramBench caveats.…
…Analysis’s Stirrup Slack integration, which adds Slack-native agents with documents, subagents, MCP, browser use, and code execution. MCP is not dead; it’s being normalized into production plumbing: Despite a wave of “MCP is dead” jokes…
…adoption, BUT without Goodharting waste? Memory: how are your agents/models improving as your users use them? World Models: how are you solving spatial intelligence and adversarial reasoning? Agentic Commerce: how are agents paying for…
…cycle point to a meaningful broadening of where and how coding agents run: mobile-first workflows via Codex Mobile walkthroughs, iPad/VPS session management from @npew, Telegram/home-server remote setups from @itsclivetime, and hints of…
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A conversation with Greg Brockman about OpenAI’s path to AGI, alongside our analysis of GPT-5, Codex, and the shift to agentic coding.
Thariq Shihipar on Claude Code’s next era: prompts, harnesses, plugins, and agents—and what it takes to keep pace with the frontier.
Marc Andreessen on the future of the browser, Pi and OpenClaw, and why this wave of AI feels different.
Priscilla Chan and Mark Zuckerberg on Biohub’s plans for frontier AI and virtual biology, and the ambition to cure or prevent disease.
Anima Anandkumar on modeling the physical world, from weather to fusion reactors, and why physics needs more than language models.
John Platt on automating science, tackling climate change, and how the next generation can contribute in the age of AI.
Anthropic brings interactive apps into Claude with an open MCP standard for richer AI interfaces.
What Sam Altman’s town hall reveals about building startups in the age of AI.
Moonshot’s multimodal model brings competitive coding, native image and video understanding, and parallel agents.
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