· 4 min read
How Tamaton Handles the Inbox an Agent Can't Stop Filling
When agents send and reply at machine speed, triage becomes a routing and evaluation problem. Here's how we approach ai email management built for bots, not just humans.
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
· 4 min read
Why Your RAG Pipeline Fails on the Inbox
Email and calendar data breaks most RAG setups because relevance is temporal and social, not just semantic. A bigger embedding model won't save you.
· 4 min read
How AI Agents Should Prove Who They Represent
Authentication tells us an agent is real. Delegation tells us who it's acting for — and that's the primitive we're missing. Here's how to build it.
· 5 min read
Custom Agents in Tamaton: Give an AI a Standing Order
Move past one-off prompts. Build a persistent Tamaton agent that watches your inbox, files, and calendar, then acts on a schedule with human checkpoints.
· 4 min read
Small Models, Big Inbox: Where 200M-Param MoE Actually Wins
A recent 200M-parameter hobbyist MoE is a great reminder: email triage, classification, and routing rarely need frontier models. Here's where small wins.
· 4 min read
RAG Is Not Search, and Your Inbox Proves It
Retrieval-augmented generation quietly breaks on email and files because it ranks documents, not conversations. Here's why, and what to do about it.
· 4 min read
Choosing an LLM for Real Work, Not Benchmarks
A practical framework for picking the best AI model for productivity tasks — weighing latency, cost, and reliability over leaderboard scores.
· 5 min read
How We Let an Agent Touch Your Inbox Without Losing Trust
A product deep-dive on the permission, preview, and rollback design that makes an AI email agent safe to actually act — not just suggest.
· 4 min read
How Tamaton Grounds Agent Actions in Your Real Data
A concrete look at how shared context across inbox, docs, sheets, and calendar gives AI agents verifiable grounding — and fewer confidently wrong actions.
· 4 min read
Automating Inbox Triage With Agents: What Actually Works
A field-tested breakdown of which inbox tasks AI agents handle reliably today, and where human review still isn't optional.
· 4 min read
Most AI Agents Are Demos. Here's What Real Ones Do.
A field guide to separating agents that actually finish work from the reasoning-superhero hype — and the boring, bounded jobs they quietly win at.
· 4 min read
Give Your Agent a Login: Custom Agents in Tamaton
A concrete walkthrough of building a scoped Tamaton agent that triages your inbox, drafts replies, and files documents — with its own identity and permissions.
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