
Your AI Agent Should Never Know Your Password
Agents that log in as you aren't a feature — they're a security architecture failure. The fix is scoped, revocable, auditable delegation at the workspace layer.

Agents that log in as you aren't a feature — they're a security architecture failure. The fix is scoped, revocable, auditable delegation at the workspace layer.

A concrete walkthrough of building a Tamaton agent that triages inbox, drafts replies with real context, and books follow-ups — with a human holding the approval button.

Only ~13% of IT orgs have sanctioned AI agents — but unsanctioned ones are already running on employee credentials with no scopes, no logs, and no way to revoke access.

Long, harmless context isn't neutral. It shifts model behavior and erodes instruction-following long before the window fills — a bigger day-to-day risk than prompt injection.

A first-person tour of the OWASP Top 10 for LLM applications from an agent that reads email, edits docs, and moves files all day — with mitigations that actually hold.

A practical guide to LLM non-determinism — temperature, sampling, seeds — and how to build evals and guardrails so 'creative' doesn't quietly become 'unreliable'.

E-discovery research found gen AI shifts review burden instead of removing it. That's a general law of applied AI: automation moves effort to verification. Design for it.

There is no single best AI tool. There are good matches between models, tools, and tasks — and a framework for wiring them into a stack that doesn't leak context or money.

New research shows conversational guardrails can be identified through probing. If your agent reads a shared inbox, its defenses are discoverable — and the fix is architecture, not a longer system prompt.

An agent's quality is mostly a function of what it knows at decision time. Here are concrete patterns for feeding, trimming, and persisting context across email, docs, and calendar.

Long-running AI agents rarely collapse because they can't think. They collapse from context decay, stale permissions, and lost intermediate state — all fixable at the workspace level.

Most productivity APIs were built for humans clicking buttons. Here's what email, docs, sheets, and calendars must expose to be genuinely agent-native — and how Tamaton built it.
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