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Life-inspired interoceptive artificial intelligence for autonomous and adaptive agents

Nature Machine Intelligence, Published online: 26 August 2026; doi:10.1038/s42256-026-01296-8 Lee, Oh et al. propose interoception as a biologically inspired framework for building more autonomous and adaptive AI agents, learning from living organisms to build autonomous and adaptive intelligence.

We haven't written up this one. Nature Machine Intelligence has the full story — the link below goes straight to it.

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What Actually Breaks When You Put AI Agents In Front Of Real Customers

I have spent the last year building AI automation systems for small businesses. Chatbots, multi agent workflows, the kind of stuff that looks great in a demo and then meets an actual customer who types "idk just fix it" and breaks everything. Most articles about AI agents talk about architecture.

  • Real users often provide contradictory, half-formed inputs that break AI agents.
  • Explicitly instructing the model to say "I don't know" when uncertain is crucial.
  • Maintenance is the most significant challenge due to frequent API and model changes.

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