· 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.
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
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
How to Evaluate an AI Assistant Before You Trust Your Inbox
Stop judging AI assistants on vibes. Build a 50-item golden set from your own work and score them on retrieval, refusals, and cost per resolved task.
· 5 min read
Your Inbox Is a Retrieval Problem, Not a Sorting Problem
Folders and filters were a workaround for bad search. In an AI-native stack, your inbox is a messy index — and treating it that way changes triage, search, and follow-up.
· 5 min read
Bound the Blast Radius: Scoping Custom Agents in Tamaton
An agent with access to every email, doc, and file is a liability until you scope it. Here's how to define, test, and audit custom agent permissions in Tamaton.
· 5 min read
RAG Is Not a Search Bar: Retrieval for Real Knowledge Work
Demo RAG retrieves from one clean corpus. Real work means retrieving across email, docs, spreadsheets, and calendar — where context is stale, duplicated, and contradictory.
· 5 min read
Memory Is Not a Feature, It's a Retrieval Problem
Assistants don't fail at memory because models forget. They fail because memory gets stored as a text blob instead of a governed store with recency, decay, provenance and conflict rules.
· 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
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
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
How Tamaton's AI Reads Your Inbox So You Don't Have To
A concrete walkthrough of Tamaton's inbox triage agent: how 84 unread messages become a ranked queue with searches run, drafts written, and calendar holds already placed.
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