· 5 min read
The Productivity Paradox: When AI Doubles Your Workload
AI rollouts often add work instead of removing it. Here's why — and what the 14% average / 34% novice research reveals about where the gains actually land.
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
Giving AI Agents a Wallet: What Machine Payments Mean
Agent identity and payment rails are shipping for real. Here's what actually changes when your agent can pay for things without you in the loop.
· 5 min read
Fine-Tune, Edit, or Steer? Adapting LLMs Without a Retrain
Fine-tuning, knowledge editing, and activation steering solve different problems at wildly different costs. Here's how to pick the right one — and what breaks when you don't.
· 5 min read
Agent Strategy Decks Are Everywhere. Working Agents Aren't.
Every vendor shipped a 2026 AI agent strategy framework this quarter. The agents that survive real work share three unglamorous traits — and break in predictable ways without them.
· 5 min read
LLMs as Research Instruments: What the Skeptics Get Right
Public policy researchers are arguing about whether LLM-assisted coding counts as method. Their objections — bias, reproducibility, opaque provenance — apply to your Tuesday afternoon analysis too.
· 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.
· 4 min read
Give Your Agents an Identity, Not a Borrowed Password
Shared service accounts and copied human credentials make AI agents untraceable and over-privileged. Here's what agent-native identity looks like in a real productivity stack.
· 5 min read
Package Hallucinations and Other Ways Agents Invent Reality
A field guide to grounding failures — fabricated npm packages, invented spreadsheet columns, phantom calendar events — and the design patterns that catch them before they ship.
· 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
The Least-Privilege Agent: How to Scope What Bots Can Touch
A practical permissions model for AI agents where every action — reading email, editing a doc, calling an API — is a privilege that must be earned, not assumed.
· 5 min read
Agent Identity: The Access Problem Nobody Budgeted For
AI agents can already do the work. The bottleneck is authorization — and most teams are quietly lending agents a human's credentials and hoping for the best.
· 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.
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