Promptcrastination

Recently I found myself knee deep in building an agent to perform market analysis for me. It scraped Reddit, Twitter, forums, and other places my potential customers might complain about the pain they’d be willing to pay to solve. This thing was great. But I realized while I was adding the 17th additional feature to it that I’d missed the low hanging fruit. I hadn’t just reached out to the handful of specific users my very first run had found.

I’ve started calling this promptcrastination: using AI-friendly tasks as a sophisticated form of procrastination.

What promptcrastination looks like in the wild

Promptcrastination is often rooted in valuing output quantity over output quality, and with AI it’s really easy to output A LOT of quantity quickly with the illusion of quality.

Promptcrastination is when you:

• add another round of unit tests you don’t really need
• start building out a greenfield feature that sounds cool, but you don’t know has value
• generate 20 marketing angles instead of emailing 5 potential users
• build a new agent workflow instead of doing the uncomfortable work it was supposed to replace
• “research” competitors with AI summaries instead of talking to a real customer

Each of these can be useful. The trap is that they’re endlessly expandable and emotionally safer than the hard thing.

Why this happens (and why it’s rational)

AI amplifies what’s already true about human behavior:

• We avoid ambiguity.
• We avoid rejection.
• We avoid tasks where progress is hard to measure.
• We seek quick wins, especially when we’re tired.

AI gives you a slot machine for “progress”: prompts in, output out. It’s immediate feedback, low friction, low risk. The really diabolical thing, though, is that it looks like productivity and feels great in the moment.

So your brain does the sensible thing: it routes work toward where the gradient is easiest.

That’s core trap in a sentence: when capability shapes priorities instead of priorities shaping capability.

The cost isn’t time, it’s trajectory

The obvious cost is wasted hours.

The bigger cost is that it subtly changes what your “default work” becomes.

You start identifying as someone who is always refining instead of someone who ships and learns. You start optimizing for polish before you have signal. You get good at producing artifacts and bad at making serious bets.

You can end up with a very clean pile of output… and no meaningful progress. And it all feels great until you look back at your day, week, month and realize you’ve accomplished little of actual value.

How to fight it without rejecting AI

The goal isn’t “use less AI.” The goal is to stop letting AI decide what “productive” means.

A few tactics that work:

1. Prioritize your task list explicitly. Don’t have 5 things to do and do them in any order. Make the order explicit and enforce it. You’ll naturally want to gravitate to the “easy” tasks, but stick to the priority.
2. Celebrate results, not output. Keep your focus on the goal or outcome you’re trying to achieve and don’t get caught up in false productivity along the way. Write “identify 3 features that would get Acme Corp to switch” instead of “do market research”.
3. Measure contact with reality. If the work doesn’t touch users or potential users it’s worth being extra diligent to verify it’s actually a leverage point and not just more promptcrastination.

The takeaway

The solution isn’t to avoid using AI. It’s holding yourself accountable for whether the thing you’re prompting is the thing that actually matters.

Next time you catch yourself three hours deep in a beautifully polished something, ask: am I working, or am I promptcrastinating?