by Braden Kelley and Art Inteligencia

For about two years now, I’ve been hearing the same prediction at conferences, in elevator pitches and at the occasional awkward dinner party: AI is going to write all the code, so the people who write code are finished. Usually the person saying it has the calm, slightly sad expression of someone delivering news about a distant relative.

I’d like to offer a different diagnosis. I don’t think we’re watching the end of the coder. I think we’re at the start of a software renaissance, and the coders are about to be more in demand than ever, just not for the reasons we expected.

The old math of software

Start with why software used to be so scarce. Building a custom application was expensive: months of work, a team, a project manager, a budget with a comma in it. That cost only made sense if you could spread it across a very large number of users or a very large number of dollars. So software got built for the big problems at big companies with big customer bases. Everyone else got a spreadsheet, a pile of sticky notes, and a heroic employee named Linda who “just knows how it works.”

Think about everything that never got built under that math. The scheduling tool for the 12-person plumbing company. The inventory app for the regional distributor. The intake workflow for the three-attorney law firm. The little internal dashboard that would have saved a department four hours a week. Not one of them was a bad idea. They were all just too small to justify the price tag. Linda kept the whole thing running on memory and caffeine.

What changes when building gets cheap

Now bring the cost of building software down by a large factor, which is what AI-assisted development is doing. The math flips. A project that was impossible to justify at $200,000 becomes an easy yes at a small fraction of that. All those never-built applications suddenly clear the bar.

Economists have a name for this pattern. When something gets dramatically cheaper, people don’t use the same amount of it and pocket the savings. They find a hundred new uses for it. We’ve seen it with electricity, with computing power, with bandwidth. Cheaper software won’t mean less software. It will mean vastly more software, built for far more people and far smaller problems.

And somebody has to build, direct and look after all of it.

The coder’s job is changing, not disappearing

Here’s the part the doom-sayers keep skipping. AI can generate code at a rate no person can match. It cannot, on its own, decide what the plumbing company actually needs, notice that the requirements contradict each other, judge whether the thing it built is safe, or keep it running when the world around it changes. That work takes someone who understands systems, who can ask the right questions, and who is willing to be accountable when it breaks at 7:00 a.m.

So the role shifts from typing every line to orchestrating: defining the problem clearly, directing the AI, reviewing what comes back, handling security and data, and maintaining the result. Call it conductor, not typist. And the conductor now has a whole orchestra to lead, for clients who never could have afforded one before.

Every company that couldn’t justify a development team last year has a reason to want at least one capable person this year. That’s a lot of newly interested employers.

What the data says (and doesn’t)

I like to check my optimism against the numbers, so I did. According to Indeed’s Hiring Lab, U.S. software developer job postings rose almost 15% between February 2025 and June 2026, while postings overall fell about 7% over the same stretch. That’s the opposite of what the “AI replaces coders” story predicted.

I’d be telling you only half the story if I stopped there. Those same postings are still about 27.5% below where they stood in February 2020, so this is a partial recovery from a low base, not a boom. And much of the recent growth is in senior roles and roles with AI in the title. Indeed also describes the link to AI tools as a correlation, not proof of cause.

I actually find that last point supports the renaissance thesis rather than undermining it. If the demand is for experienced people who can direct AI and own the result, that is exactly the orchestrator role I’m describing. The loss, at least for now, falls hardest on the entry-level, typing-focused end of the job. That’s a real problem, and it deserves its own conversation about how the next generation of developers gets trained. But it’s a shift in the work, not a vanishing of it.

The deflation angle

Now for the part I find most interesting, and I’ll flag that this is an argument, not a forecast.

The latest numbers show headline inflation at 3.7% in September, up from 3.4% in August. The Fed raised rates to a range of 3.75% to 4.00% last month, its first hike in three years, and has signaled more may follow. When the central bank’s main tool is making money more expensive, it works by slowing down demand. That’s a blunt instrument.

There’s another way to bring prices down: produce more with less. This is the oldest anti-inflation tool there is, and it has nothing to do with interest rates. Productivity.

Here’s how a software renaissance fits in. When a small distributor builds the inventory tool it always needed, it wastes less stock. When the law firm automates its intake, the same people handle more clients. When the plumbing company schedules its crews well, it makes more calls per day. Each of those is a small business doing more with the same or fewer resources. Multiply that by millions of small and mid-sized businesses, and you have a broad productivity gain that pushes the cost of delivering goods and services down, not up.

I don’t want to oversell it. Software alone won’t tame inflation, productivity gains take time to show up in the data, and the forces behind current prices are bigger than any one technology. But if cheap, custom software lets millions of organizations do more with less, that’s a quiet deflationary force working in the same direction as the Fed, and unlike a rate hike, it doesn’t require anyone to give up growth to get there.

What to do about it

If you run a business: make a list of the work in your organization that lives in a spreadsheet, someone’s head, or a stack of email. Each item is a candidate. Then find someone who can orchestrate the AI to build it and keep it healthy, whether that’s an employee, a contractor or a small firm.

If you’re a developer: lean into being the person who can define the problem, direct the tools, check the output and own the outcome. That skill set is in demand and is likely to stay that way.

If you’re worried about all this: I understand. Every technological shift feels like an ending to those standing in the middle of it. But I’ve spent my career studying what happens next, and the pattern is rarely “the work disappears.” It’s “the work changes, and there’s a lot more of it than anyone expected.”

Linda, for the record, will be fine. She’ll finally get to take a vacation.

Image Credits: Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude to clean up the article.

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