How to use AI to release your product faster

Tens of thousands of software developers laid off at major tech companies, coding AI agents taking over software development - just two striking headlines from recent years. How is this going to affect your business when it comes to releasing a new product? On the surface, it might look like “coding is solved” and development will be cheap and abundant. In reality, two opposite trends are happening at the same time:

• Routine coding is getting faster and cheaper thanks to AI.

• Finding someone who can turn vague ideas into reliable, maintainable systems is getting harder.

AI tools are excellent at generating code, boilerplate, and prototypes. They can help you spin up an MVP faster than ever before. But they don’t:

• Talk to your users and understand their real needs.

• Design an architecture that won’t collapse under real-world usage.

• Take responsibility for security, performance, and long-term maintenance.

• Balance trade-offs between speed, cost, and quality for your specific business.

This is why, even in a world of AI coders and mass layoffs, good engineering is still a bottleneck. The challenge shifts from “who can type this code?” to “who can define the right thing to build, steer AI productively, and keep the system healthy over time?”

For you as a business owner or product lead, this means you can expect faster delivery of features and prototypes.

You’ll get the best results by working with someone who uses AI to speed up development but applies senior-level judgment to requirements, architecture, and maintenance.

In my work with clients, I use AI tools where they make sense—code generation, scaffolding, refactoring, research—but I stay fully accountable for how the system behaves, scales, and evolves. In terms of Test-Driven Development (TDD), I do not let AI do both coding and testing. That can go wrong quickly by generating less relevant tests and then passing them easily. I prefer to create all the tests myself.