The Hidden Cost Was Attention

When people ask what it costs to build something with AI, I think they usually mean money.

Fair question.

But with my first attempt at a construction bid platform, the cost was not just AI credits. It was time, attention, and a little bit of humility.

The project was called BidPilot AI Suite. It was my earlier attempt before I restarted and moved toward MyBidPilot.us. Looking back, it was short. Only 18 messages. That sounds almost funny now, like I barely got started.

But those 18 messages covered a lot.

I had a 2-step AI Quote Builder with versions, a BOM, and PDF export. A BOM is just a bill of materials — the list of stuff needed for a job. I also had an AI proposal writer that could help with a cover letter and a scope narrative. And I had started a live pricing module with a material and freight catalog.

On paper, it looked like progress.

In my head, it looked like magic.

This is where the cost started to show up.

Every time I asked the AI to build something, explain something, or change something, I was spending credits. Not huge sums in one dramatic moment, but little by little. Like leaving a faucet dripping. One more question. One more adjustment. One more feature because I thought, well, while I’m here...

That part is easy to underestimate.

But the bigger cost was attention.

I was trying to build something useful for construction bidding, and pricing is the heart of that. If the pricing is wrong, the rest can look beautiful and still be useless. So I asked the question I needed to ask: is it realistic to get supplier API feeds?

An API is basically a way for one computer system to talk to another. In my mind, maybe I could connect the app to suppliers and get current material prices flowing in automatically.

That would have been wonderful.

The answer was less wonderful.

The AI explained that live steel mill pricing APIs are not really sitting out there waiting for a small builder like me to plug into. Pricing is relationship-based. It depends on suppliers, accounts, locations, timing, freight, and probably a dozen other things I do not know enough about yet.

That was the moment the ceiling came down a few feet.

The price book I had was not real market pricing. It was placeholder seed values. In plain English, fake starter numbers so the app had something to work with.

That does not mean the work was wasted. But it did mean the dream I had in my head was ahead of the real-world plumbing.

And that is another cost: realizing you have built toward an assumption that may not hold.

I do not have a coding background, so I am learning the software part and the business logic at the same time. At 50, my brain does not always appreciate this arrangement. Some days I feel curious and energized. Other days I feel like I opened twelve junk drawers and dumped them on the kitchen table.

This was one of those projects where I had to admit, I was automating too much too soon.

The builder could help me create screens, workflows, documents, and pieces of an idea. But it could not magically make the supplier world more open than it is. It could not turn placeholder pricing into trusted pricing. It could not erase the need for real relationships and real data.

So I restarted.

Not because the first version was a total failure. More because it taught me what not to bet the whole product on.

The cost reality, at least for me, is this: AI makes building cheaper and faster, but it does not make thinking free. It does not remove the need to ask whether the thing you are building can actually work outside the demo.

Credits matter. Time matters. But attention may be the most expensive part, because once you spend it chasing the wrong assumption, you do not get that week of brain space back.

Small takeaway: before building faster, I need to check what is real.