Most AI agent demos optimize for the first successful run. Real agent work gets interesting after...
Most AI agent demos optimize for the first successful run.
Real agent work gets interesting after the agent says "done."
For a coding agent, browser agent, or MCP-connected workflow, the final chat answer is not enough. I want a receipt: a compact operational record that helps a human trust, debug, replay, roll back, or explain what happened.
Not a giant transcript. Not a raw log dump. A receipt.
"Done" is not a state
Why most AI agents disappoint in production (and what to fix first)
Your AI Agent Works Perfectly in the Demo. Here Are the 6 Ways It Dies in Production. | Towards AI
68% of AI power users do one thing differently — and it is not a prompt trick
Most AI failures do not start at the prompt. They start in the folder. + 4 prompts to fix the room in 45 minutes.
You gave your AI agent real tools. Here's the 4-part control layer it's missing + the Judge Layer implementation guide
ReasoningBank: Enabling agents to learn from experience
Meta paper reveals improved coding agents through summary reuse
Most AI agent demos optimize for the wrong screenshot. They show the moment where the agent produces...
You know that slightly cursed feeling when an AI coding agent says "done", but you still have no idea...
Idempotency, validation, budgets, and tracing — the checklist for shipping AI agents that actually survive production.
Agents disappoint in production when we ask them to drive on roads built for dashboards. Build these four guarantees into the…
Every time I started a new agent session, I was re-explaining the same things. The architecture...
I’ve been thinking a lot about a failure mode in AI-assisted development that does not fit neatly...
