What is an agent harness and why does it matter so much?
An agent harness is everything running around the model: context, tools, permission and cost. Why it explains more of the outcome than the model.
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An agent harness is everything running around the model: context, tools, permission and cost. Why it explains more of the outcome than the model.
Agent vs workflow vs chatbot: who picks the next step is what separates them, and most cases that ask for an agent are better off as a workflow.
An agentic prompt carries four sections a normal prompt doesn't: a tool policy, a stopping criterion, error recovery and a step budget.
An agent is a model inside a loop with tools and a stopping rule. What changes versus a single call, and when that trade is worth making.
The open problems in AI as of July 2026: reliability, autonomy, learning, cost and understanding — and what has already left that list.
What is artificial intelligence: systems doing work that would take human intelligence. How it works underneath, what changed, and where it breaks.
Keeping up with AI research is triage, not reading: where papers land, how to discard 99% of them, and how to read what survives in three passes.
What is this, and what can I do with it day to day?
How do I put this together, and what breaks in production?
Which option fits my case, and what does it cost?