· 5 min read
Your Inbox Is the Best RAG Corpus You Already Own
Email, calendar, and file storage are already chunked, timestamped, and permission-aware. Treating them as your retrieval corpus beats dumping documents into a vector database.
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
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
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.
· 5 min read
Agents Don't Fail at Reasoning. They Fail at Hour Three.
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.
· 5 min read
Designing an Inbox an Agent Can Actually Use
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.
· 4 min read
Most 'AI Agent Use Cases' Are Cron Jobs With Anxiety
A practical test for when to use an AI agent versus a plain script in an LLM costume. Three questions decide it: ambiguity, branching, and recoverable failure.
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