AINewsnow

Max effort lost to medium effort — notes on a visual agent harness

This story is from 2026-10-20. It is preserved in the archive; the latest stories are on the live feed.

I have a bad habit. When an agent fails a task, I turn the reasoning dial up. More thinking, more tokens, more chances to stumble into the right answer. It works just often enough to keep the habit alive, which is how bad habits survive in this field. A paper I read this week argues pretty directly…

Read the full story at DEV Community — AI ↗

Timeline · 1 report

  1. 2026-10-20 14:37 · DEV Community — AI
    Max effort lost to medium effort — notes on a visual agent harness

More stories

  1. DeepSeek releases DeepSeek-V4.1-Flash-1017 open weights under the MIT license — r/huggingface
  2. Build a semantic layer for agentic AI on AWS with AtScale and Amazon Bedrock AgentCore — AWS Machine Learning Blog
  3. DeepSeek open-sources DeepInfer, its high-performance inference framework that powers its production services, starting with support for DeepSeek-V4.1-Flash — Techmeme
  4. DHS Orders DeepSeek Technology Removed From Federal Civilian IT Systems — Wall Street Journal Technology
  5. Ex-OpenAI worker accused of bugging offices planned to 'flee' to Saudi Arabia, prosecutors say — Sky News Technology
  6. FairStress: A deeper evaluation of fairness in LLM decision-making — Allen Institute for AI (Ai2)
  7. ALTK-Evolve: How learned memory tops the τ²-bench leaderboard on customer service tasks without a frontier model — Hugging Face Blog
  8. Structured outputs for Anthropic Claude models on Amazon Bedrock — AWS Machine Learning Blog

Get the daily brief of stories like this at 6:30 every morning →