· 5 min read
Your Coding Assistant Skips the Boring Stuff. Here's Why.
LLM coding tools quietly omit rate limits, logging, and error handling — not because they can't, but because nobody named them. Here's how to prompt around it.
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
Evaluating Agents: Why 'It Worked in the Demo' Lies
Task-completion scores hide silent failures. Here's a working method for AI agent evaluation using judged rubrics, adversarial cases, and regression suites.
· 5 min read
How to Evaluate an AI Agent That Books Your Meetings
Task-completing agents can't be graded like chatbots. Here's an eval framework built around side effects, reversibility, and the cost of being wrong.
· 4 min read
Multi-Agent Systems Are Coordination Problems, Not Model Problems
The bottleneck for multi-agent setups isn't a smarter model — it's shared state, clean handoffs, and knowing who owns the calendar. Coordination is the real work.
· 4 min read
Production Bugs Live in the Past: The Case for Context Storage
Coding agents only see the present, so they keep re-solving problems your team already solved. The fix isn't a smarter model — it's durable, searchable context.
· 4 min read
Project Memory: The Missing Layer for Agent Workflows
Bigger context windows won't fix agents that forget. Persistent, structured project memory is the real unlock for sustained knowledge work.
· 4 min read
Agent vs. Workflow: Stop Letting the AI Improvise
A practical rule for AI-native software: use an agent only when the steps are unknown and the goal is clear. Use a deterministic workflow for everything else.
· 4 min read
Picking a Coding-Adjacent Model in 2026: A Selection Playbook
Model choice is now a routing decision, not a beauty contest. Here's how to match task, latency, and cost across the big providers.
· 5 min read
Everyone's Shipping ChatGPT Work. Here's What Breaks.
Bolting AI onto disconnected tools recreates the handoff tax it promised to kill. Here's why integration depth beats feature breadth in 2026.
· 5 min read
The Agent-to-Agent Protocol Problem Nobody's Solving
As AI agents start transacting on our behalf, the bottleneck isn't intelligence — it's the missing trust, identity, and handoff layer between them.
· 4 min read
AGI Is Coming? Fine. Your Spreadsheet Still Has Errors.
While leaders argue over AGI timelines, the winnable fight is narrow AI that checks its own document and spreadsheet output. Grounding beats grandeur.
· 5 min read
Custom Agents in Tamaton: Give an AI a Standing Order
Move past one-off prompts. Build a persistent Tamaton agent that watches your inbox, files, and calendar, then acts on a schedule with human checkpoints.
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