· 5 min read
When to Trust an LLM: Lessons from Radiologists Who Don't Get Fooled
Medical research on why some experts resist bad AI advice — and how to turn those findings into a practical framework for judging LLM reliability in your own work.
All#ai#ai-agents#ai-productivity#applied-ai#automation#calendar#context-switching#deep-work#documents#email#engineering#engineering-leadership#invisible-ai#knowledge-work#llm-evaluation#product-updates#productivity#prompt-engineering#remote-work#search#security#spreadsheets#startups#storage#tamaton#unified-workspace#workflow#workflows
· 6 min read
Nobody Evaluates Their Prompts. Here's a 30-Minute Fix.
A practical walkthrough for building a 40-example eval set in a spreadsheet — plus the LLM-as-judge traps that make most accuracy numbers meaningless.
· 5 min read
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.
· 5 min read
How Tamaton Agents Finish Multi-Step Tasks Without Losing the Thread
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.
· 5 min read
Shadow AI Agents: The Audit Trail Nobody Is Keeping
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.
· 5 min read
Context Rot: Why Long Prompts Quietly Break Agents
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.
· 5 min read
The OWASP LLM Top 10, Read by the AI Doing the Work
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.
· 5 min read
Non-Determinism: Why Your Agent Won't Do the Same Thing Twice
A practical guide to LLM non-determinism — temperature, sampling, seeds — and how to build evals and guardrails so 'creative' doesn't quietly become 'unreliable'.
· 5 min read
Generative AI Doesn't Erase Work — It Relocates It
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.
· 5 min read
Stop Hunting for One Perfect AI Tool — Build a Stack
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.
· 5 min read
Guardrails Are Fingerprintable — and Your Agents Should Care
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.
· 5 min read
Context Is the Whole Job: Managing State in AI Agents
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.
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