Mentor dos Nerds

Where to use AI in the company? A practical guide to finding bottlenecks and choosing between process, automation, AI assistance, agents, and human decision-making.

Why useful agents need to expose uncertainty, point out blind spots, and turn human criteria into a verifiable system.

AI can produce content, but its value goes beyond the feed: coordination, validation, automation, and governed decisions rooted in real bottlenecks.

AI automates tasks; it does not absorb context by osmosis. Firing the expert too early can turn efficiency into error at scale.

How I use a revisable portrait of my patterns to build agents that add counterweights without diagnosing, deciding, or thinking for me.

AI can converse, execute, validate, organize evidence, and decide within policies. The useful limit starts with the problem, not the chat window.

How I use a Markdown and Git wiki to separate hypotheses, decisions, and syntheses before silent inferences start governing the system.

Pseudo-experts turn recent discovery into authority. The antidote is to look for artifacts, consequences, review, limits, and responsibility.

Real cases show why reviewing AI-generated content isn't polish: it's authorship, accountability, and control before publishing or deciding.