The soft skills of working with AI

Most of the writing on this site is about shipping the right thing, the judgment that kicks in after the first version works. This post is narrower. It is about the actual working relationship with the AI, the back and forth at the keyboard.

Build closely with AI for a while and the lessons start to surface. You expect them to be about the tool, which command, which mode, which clever prompt. Most are not. Almost every real lesson turns out to be an old professional skill, surfaced and pointed at a new tool.

Here is what that means. These are the things that move the needle when you work directly with AI, and not one of them is a feature you can look up.

Knowing when to slow down

Some work you just do. Some work you think through first, before a line of code exists. Telling the two apart is judgment, not a setting.

Showing instead of telling

A loose description gets read differently every time. A concrete example, this input gives this result, removes the room to guess. Being specific is a skill.

Saying what good looks like up front

Decide how you will know it is right before you ask for the work. That is the same discipline as writing the acceptance criteria before the build.

Letting yourself be questioned

The best move before building something is to let the AI interview you. The questions surface the things you had not thought of. You have to be willing to not have all the answers yet.

Giving feedback that lands

When a few things are wrong, the skill is knowing which to raise together and which to hand over one at a time. That is just clear communication.

Staying the driver

When the AI answers, do not just hit return. Stop, read what it did and think. If it has gone somewhere you did not expect, ask a question or reframe until it is clear. What it did might be right, but you are the one driving, so check before you move on.

And not only the soft skills

The moment you need AI to hand data back in a fixed form, an old hard skill surfaces too: data modelling. Define the shape, constrain the values, decide what is allowed to be absent. The AI fills the row, you design the table. Anyone who has built a database already has the instinct.

None of that is new. It is briefing a contractor, defining a spec, asking good questions, giving clear feedback. AI does not hand you a new skill. It surfaces an old one and makes it matter more.

This is why the gap is widening between people with the same access to the same tools. The features are learnable in an afternoon. The craft underneath is not. Shipping the first version is easy now. The hard part, the second version, the right version, is still human craft.

Where this shows up

If you want the hands-on version of these, the framework has a hub for every kind of AI work: Working with AI.

This is a working list, not a finished one, and it grows as more surface. So, a question for you: if you are building with AI, what soft skill has surfaced for you? What old habit turned out to matter more than any prompt? Leave a comment below, or reply if this reached you by email. This post is being built in the open, with you.