· 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.
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
Does Your AI Tool Leak IP? A Data-Flow Audit Guide
A practical framework for tracing exactly what leaves your environment when AI touches your documents, code, and email — before it becomes someone else's training data.
· 4 min read
How Tamaton Selects Models Per Task, Not Per Vendor
A routing layer picks the right model for each request — summarization, extraction, or reasoning — so quality and cost stay flexible instead of locked to one provider.
· 4 min read
Agentic AI vs AI Agents: Why the Distinction Matters
A single-task AI agent and a goal-directed agentic system are not the same thing. Here's the capability boundary, and what each is actually good for.
· 5 min read
Most AI Agents Nobody Needs: The Utility Test
A practical framework for deciding when an autonomous agent actually beats a prompt or a plain feature — and when it's just expensive theater.
· 4 min read
Fine-Tuning vs Prompting for Knowledge Work in 2026
LoRA and lightweight fine-tuning are cheaper than ever, but for most inbox and document tasks, prompting plus retrieval still wins. Here's the decision tree.
· 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
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.
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