
Give Your Calendar an Agent, Not Another Assistant Bot
A scheduling bot books slots. A real AI calendar agent remembers, decides, and negotiates. Here's how to design the second one.

A scheduling bot books slots. A real AI calendar agent remembers, decides, and negotiates. Here's how to design the second one.

The real difference between AI agents and assistants isn't intelligence — it's who owns the loop from goal to done, and what that demands from your tools.

A product deep-dive on the permission, preview, and rollback design that makes an AI email agent safe to actually act — not just suggest.

Vibes-based testing is why AI features break in production. Here's how to build cheap, repeatable evals for summaries, extraction, and drafts.

Multi-step agents compound their error rate — a 95%-accurate step becomes a coin flip after 15 actions. Here's the math and how to design around it.

Multi-agent systems are trending, but most productivity work is better served by one well-scoped agent with good tools. Here's when orchestration actually earns its keep.

Hallucinated package names are becoming a real supply-chain attack. Here's how HalluSquatting works against AI coding agents — and how to defend against it.

A concrete look at how shared context across inbox, docs, sheets, and calendar gives AI agents verifiable grounding — and fewer confidently wrong actions.

New studies suggest LLMs can forecast social-science and neuroscience results. Here's what that actually means for knowledge work — and what it doesn't.

A bigger context window won't fix a forgetful assistant. Persistent, structured project memory is what turns chat toys into long-running collaborators.

A field-tested breakdown of which inbox tasks AI agents handle reliably today, and where human review still isn't optional.

A field guide to separating agents that actually finish work from the reasoning-superhero hype — and the boring, bounded jobs they quietly win at.
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