· 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.
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
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
Picking the Right Model per Task: A Router's Playbook
Stop chasing one 'best' model. Route each task — drafting, summarizing, spreadsheet reasoning, coding — to whichever model wins on quality-per-dollar.
· 5 min read
AI Agent Identity: Why Your Bot Needs Its Own Credentials
Borrowing a human's login is a security disaster waiting to happen. Here's why AI agents deserve their own scoped, revocable, auditable identities.
· 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.
· 4 min read
Context Windows Are a Trap: Why RAG Still Beats 1M Tokens
Frontier models keep bragging about million-token context windows. For real knowledge work, disciplined retrieval still wins on accuracy, cost, and latency.
· 4 min read
How to Evaluate an AI Agent Before You Let It Touch Your Inbox
A practical evaluation framework — task success, tool-call accuracy, hallucination rate, and recoverability — for deciding whether an agent is safe near your email and calendar.
· 4 min read
Shell Injection in AI Coding Agents: A Defense Playbook
Autonomous coding agents run commands you didn't write. Here's how to sandbox them like the untrusted executors they are — instead of trusting model alignment.
· 4 min read
The Calendar Is a Reasoning Problem, Not a UI Problem
Most scheduling agents fail because they treat the calendar as slots to fill instead of constraints to reason about. Here's what real calendar reasoning requires.
· 4 min read
Real-Time Guardrails Beat Better Models for Code Quality
The Sonnet 4.6 guardrail results suggest output validation, not raw model choice, is the highest-leverage lever for reliable AI code.
· 4 min read
LLM Quantization: What You Actually Lose at 4-Bit
A measured look at where 4-bit quantization degrades reasoning and retrieval — so you pick precision by task instead of chasing the smallest model.
· 4 min read
Evaluating AI Output When 'Looks Right' Isn't Good Enough
Fluent isn't the same as correct. Here's how to build task-level evals, groundedness checks, and regression testing into everyday AI features.
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