WINDOW INTO THE FUTURE OF WORK

I heard Grace Clarke describe this really well on How I AI this week.

Grace teaches non-technical people how to use AI. She used to give students carefully engineered prompts so they could get a great result straight away. They told her it was actually making things harder.

What helped more was getting used to bringing AI into whatever they were already working on. Sometimes she’d literally send a Slack reminder saying: screenshot what you’re working on and drop it into Claude

Eventually they stopped needing the reminder. Grace calls it muscle memory.

You don’t need to become amazing at prompting before AI becomes useful. You need enough reps with the same kinds of work to start noticing what AI needs from you, what it keeps getting wrong and what’s worth keeping for next time.

And this is where I see people waste a surprising amount of time. So I’d do this instead.

How to make one good AI result reusable

1. Pick a task that gives you another rep

Don’t start with the task you hate most. Start with something that comes back and where you can tell fairly quickly if AI did a decent job. A good test is to ask whether you’d give this to a new teammate in their first week.

✅ A weekly project update that pulls from the same places and follows roughly the same format.
❌ A board report that changes every month and needs loads of judgement.

a16z found a similar pattern looking at AI workflows already running at scale: repeatable work with a clear path and an answer you can verify tends to work better. Good reps look more like:

• Teams interview → structured candidate notes you review

• 5 customer calls → repeated objections for the next campaign brief

• weekly project notes → drafts for social posts

2. Brief AI once instead of drip-feeding the job over six messages

I saved this prompt from Alex Prompter this week because it fixes a very normal problem: AI confidently starting before it has enough context.

His version makes AI ask questions one at a time instead of filling in the gaps itself. We use a similar exercise with non-technical professionals. For a task you want to repeat, try this:

💡 Voice works really well for this. You’ll usually mention the weird little details you’d never bother typing, and those are often the things AI needed in the first place. Once the summary looks right, keep it. That becomes the starting brief for the next rep.

3. Save the bits that changed the result

Don’t save every prompt. Save the things you had to teach AI before it became useful. For example:

Those are the things that make attempt #2 less random. A prompt can change completely while those four things stay useful.

4. Run the second rep

When the work comes back, don’t judge the setup by whether ChatGPT remembers your favorite adjective. Ask “What do you already know about how I work on this task, and what do you still need from me?” then run the real task.

DID I…

□ explain less?
□ repeat fewer old corrections?
□ get to something useful with less back-and-forth?

If you’re still explaining the same things, update the setup. If something new helped, keep it for rep #3.

WANT TO BUILD MORE OF THESE REPS?

This kind of repetition is a big part of our free 15 Days of AI challenge.

15 minutes each weekday practicing with AI on your real work. Over the 15 days, those little reps start turning into habits and reusable ways of working.

TRYING TO BUILD THE SAME HABITS ACROSS YOUR TEAM?

It gets harder when you’re trying to move hundreds of people beyond the occasional good ChatGPT conversation.

That’s what we work on with 15 Days of AI for Teams: repeated practice on real work until useful AI behavior and habits start sticking.

BEFORE YOU GO ✌️

See you next Sunday!