· 4 min read
Production Bugs Live in the Past: The Case for Context Storage
Coding agents only see the present, so they keep re-solving problems your team already solved. The fix isn't a smarter model — it's durable, searchable context.
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#search#security#spreadsheets#startups#storage#tamaton#unified-workspace#workflow#workflows
· 4 min read
Zero-Trust for AI Agents: Scoping Permissions in Your Stack
Treat every agent action as untrusted by default. Here's how to build permission boundaries around inbox, files, and calendar instead of handing out blanket access.
· 4 min read
Search Across Your Files Is Broken — Semantic Won't Save It
Pure vector search over personal files stumbles on recency, permissions, and exact terms. Hybrid retrieval plus metadata is the fix.
· 3 min read
Intent-Based Search: Vector Embeddings Replace Keywords
Traditional keyword search fails when you can't remember exact terms. Semantic search understands what you meant to find.
· 3 min read
Hybrid Search: Why Vector Embeddings Alone Fail Professional Users
Professional productivity demands more than semantic similarity. Here's why combining LLM-extracted metadata with keyword search delivers the precision knowledge workers need.
· 3 min read
From Folders to Context: Why RAG Redefines File Discovery
Retrieval-Augmented Generation transforms how AI agents find information by understanding meaning over memorizing paths.
Get started
Reserve your @tamaton.ai email
Claim your address before someone else does — free to start, with an AI-native inbox built in.