@UPing123zzz: I've noticed that many programmers, myself included, are especially prone to getting caught up in tinkering with technology for its own sake. Today we're exploring a new Agent framework, tomorrow it's RAG, and the day after we're fiddling with Skills, MCP, and all kinds of automated workflows. Every day we're browsing projects on GitHub and studying the latest models, feeling like we've learned…

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Summary

A programmer implementing AI in an enterprise reflects on how technical professionals can easily fall into “self-indulgent enthusiasm for technology,” emphasizing that technical skills do not equate to product or business skills. The real challenge lies in identifying needs, delivering value, and generating revenue.

I've noticed that many programmers, myself included, are especially prone to getting caught up in technology for its own sake. One day you're exploring a new Agent framework, the next you're studying RAG, and the day after that you're tinkering with Skills, MCP, and all kinds of automated workflows. Every day you're browsing projects on GitHub and looking into the latest models. You feel like you've learned a lot, and your technical skills really are improving. But if someone asks whose problems any of this actually solves, whether you have real users, or whether anyone is willing to pay, you often struggle to give a clear answer. Especially now that AI coding is becoming increasingly powerful, many features that used to take considerable time to develop can be built quickly with Codex. The barrier to building a website, an Agent, or an automation system on your own really is much lower than it used to be. But here's the question: when more and more people can build similar products, what makes you think anyone will buy yours? Technical implementation is just one part of the process. The real challenges may be identifying demand, building trust, controlling costs, and ensuring that customers keep getting value. I now work on implementing AI in businesses, and after working with GEO, RAG, Agents, and AI video generation, I've come to appreciate this more and more. Take a digital avatar video generation project, for example. The API integration works, and the video has been successfully generated. From a programmer's perspective, the job might seem finished. But if the subtitles, visual presentation, and image quality don't meet the customer's standards, the project still isn't ready to deliver. You can't tell a customer, "My API call returned successfully, so you should be satisfied." They're not buying a successful HTTP response. They're buying an outcome that actually solves a business problem. People in tech really should learn more about business, product development, user psychology, and communication. Being able to write code demonstrates technical ability. Getting people to want to use what you've built demonstrates product ability. Finding customers, understanding their needs, delivering the work, and earning revenue—that's real business ability. And I think the scariest thing isn't that your technical skills aren't strong enough. It's spending years becoming exceptionally good at technology without ever seriously examining how your abilities actually create value. Of course you should develop deep technical expertise, but never mistake technology itself for the ultimate goal.
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Cached at: 10/29/26, 12:00 PM

I’ve noticed that many programmers, myself included, are especially prone to getting caught up in technology for its own sake.

Today we’re exploring a new Agent framework, tomorrow it’s RAG, and the day after that we’re tinkering with Skills, MCP, and all kinds of automated workflows. Every day we browse projects on GitHub and study the latest models. It feels like we’re learning a lot, and our technical skills really are improving. But if you ask whose problems any of this actually solves, whether it has real users, or whether anyone is willing to pay for it, we often struggle to give a clear answer.

Especially now that AI coding is becoming increasingly powerful, many features that used to take considerable time to develop can now be built quickly with Codex. The barrier to building a website, an Agent, or an automation system on your own is certainly much lower than it used to be.

But here’s the question: when more and more people can build similar products, what makes you think anyone will buy yours? Technical implementation is just one part of the process. The truly difficult parts may be identifying needs, building trust, controlling costs, and ensuring that customers continue to get value.

I now work on implementing AI in businesses, and after working with GEO, RAG, Agents, and AI video generation, this has become increasingly clear to me. Take a digital avatar video generation project, for example. The API integration works, and the video has been successfully generated. From a programmer’s perspective, the job might seem finished.

But if the subtitles, visual presentation, and image quality don’t meet the customer’s standards, the project still isn’t ready for delivery. You can’t tell a customer, “My API returned a successful response, so you should be satisfied.” They aren’t buying a successful HTTP response. They’re buying an outcome that actually solves a business problem.

People in tech really should learn more about business, product development, user psychology, and communication. Being able to write code is a technical skill; getting people to want to use what you build is a product skill; finding customers, understanding their needs, delivering the work, and earning revenue—that’s real business ability.

And I think the scariest thing isn’t that your technical skills aren’t strong enough. It’s spending years becoming exceptionally good at technology without ever seriously examining how your abilities actually create value.

Of course you should develop deep technical expertise, but never mistake technology itself for the ultimate goal.

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