· 4 min read
The Inbox Is the Real Agent Benchmark
Email is the hardest test for an AI agent: ambiguous intent, irreversible actions, and real trust. Here's why most demos quietly avoid it.
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From the Tamaton team
Practical writing on productivity, AI, and building software.
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
Why Multimodal Benchmarks Still Fail Agentic Work
Most multimodal benchmarks test isolated perception, not the chained document-to-action tasks agents actually perform. Here's what better evaluation looks like.
· 4 min read
How to Evaluate an Agent That Edits Your Spreadsheet
Spreadsheet edits demand cell-level, deterministic evaluation — accuracy, reversibility, and formula integrity — not vibes-based scoring.
· 4 min read
Why AI Agents Aren't Coworkers — and Why That Matters
Calling AI agents 'digital employees' quietly erodes human accountability. Treat them as orchestrated, audited tools instead — here's how and why.
· 4 min read
Why Agents Fail at Long Tasks (And How to Fix Drift)
A diagnostic framework for why agentic workflows degrade over multi-step tasks — context loss, tool errors, and goal drift — plus concrete mitigations.
· 4 min read
Difficulty-Aware Prompting: When Chain-of-Thought Hurts
Reasoning depth should scale with task difficulty. Here's when chain-of-thought helps, when it hurts, and how to spend reasoning tokens wisely.
· 4 min read
Prompting Is Becoming Spec-Writing
The clever one-liner prompt is fading. Durable AI work needs specifications: constraints, examples, and acceptance criteria you can reuse.
· 4 min read
AI Workflows vs. AI Agents: When to Use Which
A decision framework for choosing constrained AI workflows over open-ended agents — and the specific conditions that justify going agentic.
· 4 min read
I Audited a Week of 'AI Productivity' — What Actually Saved Time
A rigorous time-and-error log of AI in real knowledge work — separating genuine wins from rework and the hidden review tax.
· 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.
· 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
Why Most RAG Pipelines Fail at Retrieval, Not Generation
When a RAG pipeline gives bad answers, the LLM usually isn't the problem. Retrieval is. Here's where chunking, ranking, and recall actually break.
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