· 5 min read
Agents vs. Automation: When a Goal Beats a Script
A field guide to choosing between deterministic automation and goal-seeking agents — with a decision tree, cost math, and the honest cases where a plain script still wins.
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
· 5 min read
The Productivity Tool Myth: Integration Beats Installation
Model quality isn't your bottleneck anymore — context portability is. We map where the time actually goes in AI-assisted work, and what to fix first.
· 4 min read
Why Your Agent Forgets: A Practical Guide to Agent Memory
Memory, not model size, decides whether an agent finishes a task or loops forever. Here's how planning, working memory, and retrieval actually fit together.
· 5 min read
Why Time-Series LLMs Hallucinate Forecasts (And When Not to Trust Them)
A practitioner's guide to when LLM-based forecasting earns its keep and when it's confidently extending a trend line into thin air.
· 5 min read
From Chatbots to Reasoning to Agents: What Changed in 2025
Reasoning models solved 'can it answer.' Agentic training moved the hard part to 'can it act reliably' — and that shift changes how everyday work gets done.
· 5 min read
The Audit Trail Problem: Email as Agent Accountability
Enterprises can't deploy agents they can't review. Email threads already give every agent action a timestamped, human-readable, forwardable paper trail.
· 5 min read
Grounding Is the New Prompting: How to Stop Agents Guessing
Clever prompts don't make agents accurate — verified, fresh sources do. Here are the grounding architecture patterns that keep AI agents honest.
· 5 min read
Keeping LLMs Current: Knowledge Editing vs. RAG
Pretraining freezes your model's worldview on a date that has already passed. We compare knowledge editing research with retrieval as strategies for keeping an AI assistant accurate.
· 4 min read
Why Your AI Agent Fails at the Handoff, Not the Reasoning
Most agent failures aren't reasoning failures — they're broken context handoffs between tools, memory, and steps. Here's where the seams actually tear, and how to reinforce them.
· 4 min read
RAG for Your Own Files: Why Search Is the Hard Part
RAG over your email, docs, and spreadsheets usually fails at retrieval, not generation. Better search and chunking beat a bigger model almost every time.
· 4 min read
Five Questions Before You Pick an LLM for Real Work
A practical model-selection framework for applied knowledge work — covering cost, context, latency, tool use, and failure modes instead of leaderboard hype.
· 4 min read
When LLMs Forecast: Hallucination in Time-Series Models
New research shows LLMs hallucinate when forecasting time-series data. Here's why that matters before you point one at your spreadsheet.
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