· 5 min read
What AI Agents Can Actually Delegate (and What They Shouldn't)
A practical taxonomy of AI agents delegation built on reversibility, verifiability, and blast radius — five tiers from 'let it run' to 'don't, ever.'
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
Give Your Tamaton Agent a Job Description, Not a Prompt
Stop writing clever prompts and start writing employment contracts. A concrete walkthrough of scoping a Tamaton custom agent with permissions, escalation thresholds, and an audit trail.
· 5 min read
When Agents Collide: What Anthropic's Clashing Bots Teach Us
Identical agents don't cooperate by default — they clash, collude, and coordinate in ways nobody specified. That's an architecture problem, and it has fixes.
· 4 min read
Federated LLMs: Why Your Data Doesn't Have to Leave the Building
Federated training lets models learn across organizations without pooling sensitive data. Here's what that shift means for privacy-preserving AI and knowledge work.
· 5 min read
Your Agent Is Only as Smart as the Context You Feed It
"Humans lead agent success" is a polite way of saying context engineering. Here's why a unified workspace beats a pile of disconnected tools as RAG substrate.
· 4 min read
When Your AI Change 'Works' But Success Drops 20 Points
Prompt and model tweaks that pass every smoke test can quietly wreck real outcomes. Here's how to evaluate agents on results instead of vibes.
· 4 min read
Stop Vibe-Checking Your AI: Build a 50-Case Eval Set
Public benchmarks won't tell you if a model can triage your inbox or reconcile your spreadsheet. Here's how to build a private, brutally specific eval set in an afternoon.
· 5 min read
Chatbot vs. Agent: The Line That Actually Matters
A chatbot returns a response. An agent decides and executes a sequence. Confusing the two is why so many 'agentic' rollouts quietly stall out.
· 5 min read
One Model to Rule Them All Is a Bad Default
Picking a single LLM for every task leaves capability and money on the table. Route by task instead: cheap triage, strong drafting, dedicated verification.
· 5 min read
Your Inbox Is a Database. Query It Like One.
Email isn't a list of messages — it's an unindexed database you never designed. Here's how to query it in natural language without hallucinating your way into a bad reply.
· 5 min read
When to Trust an LLM: Lessons from Radiologists Who Don't Get Fooled
Medical research on why some experts resist bad AI advice — and how to turn those findings into a practical framework for judging LLM reliability in your own work.
· 6 min read
Nobody Evaluates Their Prompts. Here's a 30-Minute Fix.
A practical walkthrough for building a 40-example eval set in a spreadsheet — plus the LLM-as-judge traps that make most accuracy numbers meaningless.
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