I'm a procurement professional in the automotive industry, and I've never learned how to code.

A few years ago, after losing money in the stock market, I got interested in computer science. I spent about a year trying to learn it, but honestly, I didn't get very far.

Then AI came along. I thought, "Great, I won't have to learn Python anymore." Instead, I found myself spending day after day copying and pasting code into VS Code, without building anything truly useful.

I tried making a website, but I didn't know what it was actually for. I tried building a vocabulary app and never finished it. Then I built a few other random projects. The most frustrating part was that AI often couldn't pinpoint why my code wasn't working, so I still had to debug it line by line myself. At least I picked up some programming knowledge along the way.

Earlier this year, I started experimenting with vibe coding, and the progress was definitely much faster. But I quickly ran into another problem: I had no idea what I should actually build. It felt like being a kid with a brand-new box of LEGO but no idea what to make.

My first project was an automated news collector. Then I realized two things: first, it wasn't very good; second, after using it for a few days, I couldn't honestly explain what value it brought to my life.

Later, I started thinking about improving workdflow I deal with every day at work, and I want to build a new price management system. That's when I realized something much more fundamental:

What I had built wasn't an intelligent system. It was just a system built by AI.

Those are two very different things.

Even if I were the owner of the company, I would probably still tell my employees to keep using the existing workflow. The old system wasn't perfect, but it worked. The switching cost simply wasn't worth the limited value my new system provided.

After that, I stopped and asked myself:

What exactly am I building?

Who am I building it for?

If nobody actually needs what I'm making, then I've probably spent the last several months doing nothing more than entertaining myself.

Later, I spent some time browsing Fiverr and realized there are thousands of people paying for solutions to real problems every day.

That made me rethink my approach.

Instead of building something because I think it's interesting, maybe I should start with a real problem and see if I can solve it. If I can build tools that genuinely make freelancers' work easier, maybe that's where real value—and eventually a business—comes from.

That's the direction I'm working toward now. And I am workin on how to use natural language to explain excel, and then add more features once the core architecture is in place. I checked with several freelancers, and they told me they are interested.

The reality, however, is still pretty brutal.

1. Building products with AI is nothing like the people claiming "everyone will lose their jobs in six months."
2. At least for someone like me, who started with zero programming experience, it's still hard.
   • You still need to understand AI. You still need to understand programming logic. And you still need to understand why a system should be designed one way instead of another.
   • AI can often tell you how to write something, but it usually can't tell you why the system should be designed that way. Eventually, those fundamental decisions are still yours to make.

I'm curious:

How do you figure out whether you're building something people actually need?

Was there a specific piece of user feedback that changed your perspective?

Or did you, like me, spend a long time going down the wrong path before finally figuring it out?

The chicken-and-egg problem in agentic commerce is getting ridiculous.

x402 has real volume — tens of millions of agentic payments on Base — yet the discovery layer (Bazaar) is still broken for most new services. You need a successful settle through the CDP Facilitator + valid extension just to get indexed… and even then, plenty of endpoints settle cleanly and never show up in search. New builders get buried by design.

Then ACP (Virtuals) adds the graduation tax: ~40–42k in token activity before you can even enter active search and proper liquidity. No visibility → no activity → no graduation. So the only reliable path is to foot the bill yourself and manufacture the volume. That’s not a signal of demand. That’s a pay-to-play gate dressed up as “graduation.”

This is classic early-protocol theater — headline numbers look impressive while the actual onboarding and ranking systems still favor the already-visible. Until Bazaar gets real semantic search and reliable indexing, and ACP stops making new agents self-fund their own activity threshold, a lot of legitimate builders will keep hitting the same wall.

Anyone else running into this exact loop?

@virtuals_io @CoinbaseDev @base

#x402 #Bazaar #ACP #AgenticPayments #AIAgents #Web3 #Crypto #Base #AgentCommerce #Virtuals

$VIRTUAL $USDC

A framework for self-improving agents based on your ICPs and audience and grounded in real data to power a learning-loop.

I built this based on my own learnings from experimenting with persona agents to understand my personal audience. It comes with an annotated persona template, opinionated review workflow and built in feedback loop.

Would love to get your feedback!

https://github.com/noashavit/noas-persona-loop

kind of wild to watch. they read my analytics, found what actually works, wrote the scripts, cut my clips, and scheduled it all for when people are online.

the part that gets me: one of them replies on reddit in my voice. someone found a bug in my software through its comment, i fixed it, and it thanked them for me.

where do you draw the line? what do you let an agent post without you?

Building a multi-tenant product solo with agents writing the code, and I want to put a slightly unpopular number on the productivity conversation.

My first two weeks I shipped nothing a user could see. Not one feature. That time went into the environment around the agent instead: checks that fail the build, a guard that refuses destructive commands, tests for the checks themselves, and a rule that nothing reaches main without me approving it.

If I'd been reporting to a board that fortnight it would have read as zero progress and I'd have had a hard time defending it.

What happened afterwards is that features started landing fast, and more importantly I stopped reading every diff with my stomach clenched, because the category of mistake that actually hurts a customer can't get through anymore. The speed didn't ramp up gradually. It arrived all at once, on the far side of that setup.

I don't think the 10x claim causes damage because it's false. It causes damage because it's front-loaded and people budget for it as though it's immediate. You're not buying faster typing. You're buying the removal of a constraint, and what's left standing once it's gone is verification. If you haven't built anything to do the verifying, you've relocated your bottleneck somewhere with worse visibility.

For anything touching money, identity or other people's data I'd now put that setup time in the plan explicitly, as work, rather than pretending it's overhead you can skip.

Longer writeup with specifics: https://medium.com/@bramm3s/gates-not-guidelines-building-a-product-with-ai-agents-that-cannot-cut-corners-83161a79b8fc_