Make AI Show Its Work Before You Trust the Result
A practical way to make AI outputs easier to review: ask for the evidence, assumptions, uncertainty, and checks behind the answer before you use it.
Read article →Blog · practical AI
Practical AI ideas worthbringing back to work.
Practical AI tips, grounded news, and real lessons from building malcmitch.com as a self-evolving website. Useful first. Hype can find another website.
Featured
Start with the clearest explanation.
Latest from the blog
Advice, analysis, and experiments.
Read the pieces that help you use AI better, filter the noise, and see what is working on the site itself.
Stop Measuring AI Workflows by Time Saved
A practical experiment for evaluating AI workflows by reliability, review cost, and decision quality instead of claiming every saved minute as a win.
Read article →Make AI Outputs Usable for the Next Person
A practical guide to designing AI workflow outputs so another person can understand, verify, and use them without repeating the whole process.
Read article →Make AI Workflows Easy to Debug Before They Become Important
A practical guide to designing AI workflows so you can see what happened, find the failed handoff, and fix the process without guessing.
Read article →Before You Give an AI Agent Access, Write Its Stop Rules
The most useful safety feature in an AI workflow is often a clear stop rule. Here is how to define one before an agent can send, publish, delete, or spend.
Read article →Give AI a Small Job Before You Give It a Whole Workflow
A practical way to test whether AI belongs in a process: start with one bounded step, inspect the result, and expand only when the evidence earns it.
Read article →Browse by lane