AI code: Skilled developers matter more than ever (just not for the expected reasons)

Artificial intelligence has changed how software gets built, and with it the role of developers, who now go from code writer to technology strategist, translator and quality controller. That's according to Lancom Technology CTO Aimee Lin, who says the shift has left most organisations with a gap they haven't yet named.

"You absolutely can create applications with AI now. It's real, and pretending otherwise is a losing argument," she says. "But what you get is a prototype. It works and demos well but doesn't have the essential features necessary for production."

Tooling access has changed, putting advanced software development capability within almost anyone's fingertips. However, advanced hacking received a similar boost: the same models that build an application in an afternoon identify weaknesses just as quickly. "Security and governance, in other words, have never been more important. You're shipping at machine speed into an environment that attacks at machine speed," Lin points out.

There's a chasm between a prototype and production, too. "Even if a prototype works as it should, functionality is just one of three essential layers. The others are 'Safe to Deploy', and include security, reliability and hardening controls. And 'Ready for Scrutiny' which includes threat modelling, environment separation, and audit evidence."

It is these two factors that she says are missing in AI generated code and applications, and Lin says most organisations are poorly equipped to identify the gap.

"'Finished software' isn't one layer, it's all three. With most vide coded or AI coded applications, only the innermost layer is visible. The application works. It tells you nothing about whether authentication holds up under attack, whether the application scales appropriately, if it is fault tolerant. It tells you nothing at all about threat modelling, environment separation, and the audit evidence necessary when a regulator or an acquirer asks how your application was assessed."

Applications are about more than code, she adds. "There's also the infrastructure where it's hosted. And that is often overlooked."

Lin stresses that an application is only as sound as the physical location where it resides. "Environment separation, identity, backup and recovery, patching: what happens when the underlying platform has a bad day? This is part and parcel of application security. Hosted poorly, even the best programmed application is at risk."

These issues are always incorporated into professional software development, leaving nothing to chance. "That's precisely the work of experienced developers. It's building the checks that run automatically and knowing which checks matter most. Anyone can wire up a test suite. Knowing what it fails to cover is the part that takes a decade."

Rapidly developing the wrong software, whether poor fit, insecure, or improperly hosted, destroys advantage Lin points out. "The economics haven't changed. Get a prototype wrong and it costs an afternoon. Get it wrong in production and you're looking at an outage, a migration, or both."

This, Lin says, is why software development roles are condensing. "The handoffs are compressing, not the work. Requirements and design still happen, but they're no longer separate phases. Automated testing sits inside the build loop rather than at a stage gate. What once moved between analyst, designer, engineer and tester, now sits with fewer people holding more of the picture."

She says the bar is higher, necessitating advanced skills. "You need people who can be trusted to judge when agents get it wrong."

Lin adds that the emergence of AI tools has an upside that she is personally enjoying. "I had to choose either software architecture or hands-on coding; there wasn't enough time for both. Now, agentic tools accelerate productivity, allowing for a broader set of activities."

Emerging developers, Lin believes, are likely to enjoy greater flexibility in their roles. "It's possible they can build architectural judgement without stepping away from programming craft; good judgement will always be scarce. You can buy agentic capacity right now, but good judgment comes with practice and learning."

So, Lin stresses, "While AI has certainly made coding fast, it's also moved the hard part of software development to a place where most organisations aren't looking. That's exactly where experience earns its keep, because the developers who matter now are those who know how to deliver production applications that leave nothing to chance."