· 5 min read
Your Agent Ran 400 Steps and Nobody Watched: Agent Observability
A practical spec for AI agent observability: what to capture in every trace — tool calls, token spend, decision forks, and the silent failures nobody logs.
Blog
From the Tamaton team
Practical writing on productivity, AI, and building software.
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· 4 min read
The Spreadsheet Is the Best Eval Harness You Already Own
You don't need an ML platform to measure AI quality. A well-structured sheet turns vibes-based prompting into something you can actually score and improve.
· 5 min read
How Tamaton Evaluates Its Own Agents Before You Do
Inside the eval harness we run on inbox triage, doc drafting, and calendar scheduling — the golden sets, the scoring rubrics, and the failure modes we refuse to ship.
· 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.
· 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
The AI Productivity Gap: Why Specialized Beats General
New adoption data shows the biggest productivity gains go to people using purpose-built AI tools, not general chatbots. The difference isn't model quality — it's context and integration.
· 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
The Productivity Tool Myth: Integration Beats Installation
Model quality isn't your bottleneck anymore — context portability is. We map where the time actually goes in AI-assisted work, and what to fix first.
· 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.
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