DevHub

Most people get junk out of AI. Not because the model is weak — the task is given in one line, with no context and no goal.

Everyone switches models and waits for a miracle, while the gap between a weak and a strong answer almost always sits in how the question was put.

Habit one: give context, not a command. Name the role, the goal, the data and the format — the answer gets several times more precise.

Habit two: ask for a plan first. Check the steps, drop the extra ones — and only then let the AI do the work.

Habit three: verify the answer by doing. Run the code and open the source yourself — never take the model's word for it.

Habit four: match the model to the task. Give routine work to a fast one and hard work to a strong one; separate steps need not wait for each other.

Stronger still: ask several models at once. In AEVION multichat the question goes to all of them and you compare the answers side by side.

For a whole product there is DevHub. Say what you need in words — the agent plans it, builds it and shows you the result.

Give the AI hands — that is what MCP servers are. There are hundreds on GitHub: files, code, databases, mail, and more.

Write your project's rules into a memory file, and every new conversation starts with your context, so your prompts work again.

And the main thing: a strong model multiplies carelessness too. The more powerful the tool, the more an error costs — it is not only the upside that grows.

Context, a plan, verification and your own tools — that is the whole system. Most people feed AI junk. You no longer do.