· 5 min read
Agent Identity in Tamaton: Every Bot Gets Its Own Keys
Shared service accounts make agent activity untraceable. Here's how scoped per-agent identities, capability grants, and audit trails fix that.
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
· 5 min read
Unified Search Without Leaky Search: Permissions at Query Time
Tamaton search spans mail, docs, and files — but every hit is checked against the caller's grants at query time, so an over-eager agent can't retrieve what it was never allowed to see.
· 5 min read
Agents vs. Automation: When a Goal Beats a Script
A field guide to choosing between deterministic automation and goal-seeking agents — with a decision tree, cost math, and the honest cases where a plain script still wins.
· 5 min read
AI Agents Are a New Identity Class. Treat Them Like One
Every agent touching your inbox, files, and calendar is a non-human user with credentials and blast radius. Most orgs provision them like scripts and hope for the best.
· 4 min read
Why Your Agent Forgets: A Practical Guide to Agent Memory
Memory, not model size, decides whether an agent finishes a task or loops forever. Here's how planning, working memory, and retrieval actually fit together.
· 5 min read
Your Inbox Is the Best RAG Corpus You'll Ever Have
Mailboxes, files, and calendars are structured, timestamped, and permissioned — which is why naive vector search fails on them. Here's a retrieval design that works.
· 5 min read
Why Time-Series LLMs Hallucinate Forecasts (And When Not to Trust Them)
A practitioner's guide to when LLM-based forecasting earns its keep and when it's confidently extending a trend line into thin air.
· 4 min read
Aggregate Scores Lie: What EduFairBench Teaches AI Evaluation
Averaged benchmark scores hide the subgroup failures that break real workflows. Here's how to build disaggregated, reproducible evals for triage, summaries, and spreadsheets.
· 5 min read
One Model to Rule Them All Is a Myth: Routing for Real Work
Chasing the single 'best' LLM is a losing game. Here's a practical framework for routing each task — code, extraction, drafting, reasoning — to the model that actually fits.
· 5 min read
From Chatbots to Reasoning to Agents: What Changed in 2025
Reasoning models solved 'can it answer.' Agentic training moved the hard part to 'can it act reliably' — and that shift changes how everyday work gets done.
· 5 min read
Grounding Is the New Prompting: How to Stop Agents Guessing
Clever prompts don't make agents accurate — verified, fresh sources do. Here are the grounding architecture patterns that keep AI agents honest.
· 5 min read
Small Models, Big Inbox: When Not to Reach for a Frontier LLM
For classifying, routing, and summarizing email, a small fast model usually beats a frontier one on cost and latency. Here's how to choose per task instead of per vendor.
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