The shift from AI that answers to AI that does the work
Chat was the first act. The next one is software that plans a task, carries it out and checks the result. Here is what that changes for the people who use it.
AI
11 storiesA plain guide to AI agents: how they plan, act and check their work
Agents split a goal into steps, use tools, and verify the outcome. This is how each part works, without the hype.
Five questions to ask before an agent touches your data
Access, limits, logs, rollback and who signs off.
Why context matters more than model size
A smaller model with the right information often beats a bigger one without it.
Open models or closed models: the real trade-offs
Cost, control and speed pull in different directions.
What an AI benchmark actually measures
A high score is useful. It is not the same as being good at your task.
Small models, real results: running AI on your own servers
When a smaller model is the better choice, and what it costs to run one.
How AI coding tools change a developer’s day
Less typing, more reviewing. What teams say works and what does not.
What ‘reasoning’ means in an AI model
A plain look at how models work through a problem step by step.