The fear: LLMs will do everything. There won’t be any need for anyone to ever write a new product again! The world will be ruled by bespoke software products written by every Tom, Dick and Harry with a laptop! R.I.P. Good Times!

Wow. Just wow.

Relax folks. Deep breath. Step back from the ledge.

Yes, our world is changing but the need for software development doesn’t end here. First things first, the act of software development is the act of describing a product in unambiguous detail*. Most people can’t do this. Being extremely detail oriented is a trait found in few professions, software development being one of them.

Second, while LLMs may be able to write code, they can’t invent the idea out of thin air. That still comes from you. You, dear software developer, still need to own the initiative and still need to own the outcome. You need to make sure you get what you asked for. And guess what? Verifying that takes extreme focus on detail.

Third, Jevons Paradox states that when a technology makes a resource more efficient, the total consumption of that resource often increases rather than decreases. Applied to software: will we get the same code with far fewer developers, or far more code with the same or more developers?

Now, Jevons describes consumption, not employment — cheaper coal didn’t save coal miners. But software’s bottleneck has never been typing. It’s judgment: knowing what to build, describing it precisely, verifying it works. LLMs accelerate the typing, not the judgment. So when typing gets cheaper, judgment becomes the constraint — and that’s what developers do.

Let’s be clear, none of this means what counts as economically viable software won’t change and change drastically. Before the web, the norm was apps that ran on your computer and didn’t talk to anything else. Many of them made great money. After the web, that model was generally unviable — the winners were apps built around communication and connection.

The availability of LLMs will also change this. Apps that used to be economically viable will no longer be so. But that’s a far cry from no software will ever be economically viable again.

We already have hints. The pattern: “LLMs do reasoning. Apps do execution.”

How do we know this? Because the business model requires it. Each of the LLM purveyors makes their money by selling tokens. Anything deterministic, anything involving execution, does not sell tokens. So they specifically defined the method by which we call external systems to circumvent this problem. This is admitting, straight up, that Claude, ChatGPT, and Gemini won’t do everything and won’t try. It’s not an accident; it’s admitting to their business model.

We’ve seen this pattern throughout software’s history. There is a long history of dominant platform companies choosing to partner with liability-heavy and customer-specific companies rather than develop their own, especially when orthogonal to their own business models.

• AWS could have built payment processing. They didn’t and deferred to Stripe. PCI compliance, chargeback liability, and regulatory exposure are all things a general-purpose platform doesn’t want.
• Salesforce easily could have absorbed DocuSign but instead chose to partner. E-signatures require ESIGN Act compliance, evidentiary burden and jurisdiction-specific legal exposure.
• Microsoft, which owns business communication, could have bought Twilio but telecom regulatory compliance is a specialty and the company didn’t want the burden.
• Google, organizers of the world’s information, could have purchased Plaid, the owner of massive amounts of financial data. Financial data aggregation carries bank and compliance obligations orthogonal to Google’s business model, though.

You might reasonably ask: doesn’t this change now that AI makes building these things cheap? No. The build cost was never the hard part. The liability was, and liability doesn’t get cheaper because code gets cheaper. A Claude-generated payment processor still needs PCI compliance, chargeback infrastructure, and a legal team. The partnerships are durable because the regulatory moat is durable.

I believe the same will be true here – and full disclosure, I’m betting on it. TrueMath is designed to guarantee mathematical execution for regulated and high stakes businesses. LLMs reason, TrueMath executes. That’s the partnership.

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* I love this definition. Thanks, Kevlin Henney and John Siracusa!