· 5 min read
Evaluating AI Output When There's No Right Answer
How to build evals for subjective knowledge work — emails, summaries, docs — using rubrics, pairwise comparison, and human-in-the-loop sampling.
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
Are You Leaking IP Through Your AI Tools?
A concrete audit of where your prompts, files, and context actually travel across AI assistants — and the data boundaries every enterprise should demand.
· 4 min read
Evaluating AI Agents: Why Task Success Beats Benchmarks
Public leaderboards reward the wrong things for agentic work. Here's a practical eval harness built around real task completion and side-effect safety.
· 4 min read
Spreadsheets as Tool Use: Letting LLMs Compute, Not Guess
Why LLMs should generate and execute formulas instead of hallucinating math — plus concrete patterns for verifiable spreadsheet automation.
· 4 min read
The Inbox Is the Hardest Agent Problem in Productivity
Email looks routine, but it's the toughest environment for autonomy: ambiguous intent, irreversible sends, and tangled threading state. Here's what reliable inbox automation really takes.
· 4 min read
Inbox Zero Is Obsolete: Triage for an Agent-Run Inbox
When agents read and draft your email, success isn't an empty inbox — it's well-designed triage rules, escalation thresholds, and approval boundaries.
· 4 min read
Evaluating AI Agents: Beyond Pass/Fail Benchmarks
Final-answer accuracy hides how agents actually work. Here's why trajectory, tool-use, and recovery metrics matter — plus a practical scoring rubric.
· 5 min read
How to Evaluate an AI Agent That Touches Your Inbox
Benchmark scores won't tell you if an email agent is safe to trust. Here's a practical eval harness built on task completion and harm metrics.
· 4 min read
Evaluating AI Agents on Multi-Step Office Tasks
Single-turn benchmarks miss what matters. Here's a practical eval harness for agents that move data across email, docs, sheets, and calendar.
· 4 min read
Model Selection in 2025: When Smaller Beats Frontier
A practical framework for routing tasks to small, fast models or frontier reasoning models based on latency, cost, and failure cost.
· 4 min read
The Hidden Cost of Context Windows in Agent Workflows
A quantitative look at how context window limits quietly degrade agent performance on email threading and document synthesis—and what to do about it.
· 4 min read
How to Choose an LLM for Each Task, Not Just the Best One
Stop defaulting to the largest frontier model. Use a cost-latency-quality matrix to route each task to the right LLM and cut spend without hurting output.
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