2026-10-18 digest
7 items on this page: 5 with their own page, 2 short.
A digest puts the short items from one day or one week on a single page. Opened alone, those briefs are often a headline and a sentence, which is a poor fit for a standalone article. Items that meet the importance threshold keep their own pages and are listed here by title.
Items with their own page
Microsoft pulls out as anchor tenant of Nscale's Loughton AI data centre in Essex, the UK government's flagship 'sovereign AI' site, after grid operators said power won't arrive until the 2030s
Anthropic cuts Claude's wait before the first token: Claude Code local sessions 3x faster (4.07 s to 1.33 s, p90), cloud sessions 2.8x, chat/Cowork and API 1.5x, helped by gzipping each turn's conversation
vLLM and NVIDIA use agent-written CuTe DSL kernels to speed up Kimi K3 decode on GB300: 842 tokens/s at batch 1 (1.73x stock vLLM), plus a 'fast-track' review process for agent-optimized code
NVIDIA releases Nemotron Labs Dory1.0-4B on Hugging Face, a looped 4B model whose single checkpoint trades inference loops for accuracy (SWE-bench Verified 50.3→61.8 at 1→4 loops, self-reported; 256K context, OpenMDW-1.1)
OpenCode confirms a breach tied to a 'large-scale distillation attack' hit 1.4% of Console users with linked OpenAI/Anthropic/Google keys; working with the three labs to remediate
Short items
Google researchers open-source Harness², which lets an agent rewrite its own prompts, tools and memory without touching model weights: one step lifts GLM-5 and Gemini 3.5 Flash by up to 11.5 points on WorkBuddy-Bench
【Key points】
Google Cloud AI Research and Northwestern University posted "Harness^2: Recursive Agent Harnessing for an Open World" on arXiv (2610.14224, October 9) and released the code under Apache 2.0 on GitHub. A "harness" is everything around the model: system prompt, tool descriptions, memory, skills, subagents and scripts. Harness² keeps model weights fixed and lets an agent rewrite that layer on unseen tasks.
Task level: run the original harness as a reference, propose cross-domain and domain-specific edits, run each on the same task, and compose a new harness from the behavioral differences, with no ground-truth answer needed. Harnessing level: store adopted harnesses and evidence-backed lessons in a library for later tasks.
The paper reports that one step improves GLM-5 and Gemini 3.5 Flash over their base harnesses by up to 11.5 points on WorkBuddy-Bench, 4.5 on JobBench and 11.8 percentage points on LAB's partial pass rate, with more gains from more iterations. The code supports OpenCode and Codex executors and has a local demo that needs no API key. The repo has about 3,100 stars; X discussion picked up over the past two days.
【Verifiable】
GitHub: https://github.com/google-research/harness2
arXiv: https://arxiv.org/abs/2610.14224
【Our read】
1. A research paper with open code, not a Google product launch; online since October 9, so this is a catch-up entry.
2. Gains are self-reported and scored by an LLM judge (WorkBuddy setup requires a Gemini judge); no independent replication yet.
3. Like DeepSeek's open-source dsh and the Apple/EPFL single-session agent study, it shifts competition toward self-adjusting harnesses. The cost: each task runs several extra times, multiplying compute and API spend.
Replit CEO Amjad Masad says Replit is 'no longer working with Anthropic', citing cost and that OpenAI's Sol/Astra beat Claude on its benchmarks; an insider says the partnership is still in place
【Key points】
Per TechCrunch, Replit co-founder and CEO Amjad Masad said onstage at TechCrunch Disrupt on Oct 16 that Replit is "no longer working with Anthropic," citing cost, partnership and performance: "I think ChatGPT is better now," with OpenAI's Sol and Astra consistently ahead on Replit's internal and public benchmarks for building vibe-coded apps from scratch. Replit announced an OpenAI partnership in August; Masad said Replit had been one of Anthropic's top five customers.
A person familiar with the partnership told TechCrunch it is still in place, and a late-September Replit blog post cites Claude Fable 5 and 5.1 in production.
【Verifiable】
TechCrunch: https://techcrunch.com/2026/10/16/replit-is-no-longer-working-with-anthropic-ceo-says/
【Our read】
1. This is an onstage remark; neither company has issued a statement, and what "no longer working" means (dropping Claude, ending the commercial deal, or switching defaults) is unclear.
2. The signal matters: a top coding platform publicly calling OpenAI cheaper and better, as Anthropic prepares for an IPO, is a public challenge to its strength in coding.
3. Watch whether Claude models actually leave Replit and whether Anthropic responds.
Aggregated by AGI Pulse. Titles and links only; no full text is republished. Editorial policy