The Declining Cost of Bespoke Development

There’s a quiet shift underway in the economics of bespoke software development. Costs are coming down – and not just marginally. While procurement teams may instinctively push back (after all, their spreadsheets suggest the opposite), that resistance often stems from looking in the wrong direction: inputs rather than outcomes.

The reality on the ground is changing. Teams today can deliver what took months or years in the past, faster and with fewer people. That’s largely thanks to advances in SDLC practices – agile over waterfall, automation in testing and deployment, and the rise of elite DevOps cultures capable of shipping multiple production releases a day without sacrificing stability.

And now we’re layering in AI. Already, we’re seeing early but meaningful gains: smaller teams, faster delivery, higher release cadence. The productivity curve isn’t just bending – it’s shifting entirely.

CTOs generally sense this, even if the measurement tools aren’t keeping pace. Procurement often doesn’t. And that’s a problem. Without a meaningful way to quantify outcomes, it becomes harder to make confident decisions around build vs. buy. Buying tends to look easier on paper: subscription-based licensing, infrastructure estimates, support and implementation rolled in. But that presumes the product works as advertised, and as many have learned, that’s often a generous assumption.

As development costs fall, we’re moving closer to an inflection point: where building may not only be more cost-effective but also deliver a better fit – particularly at the edges, where off-the-shelf products typically underperform or impose architectural and usability compromises.

The challenge, of course, is certainty. Buyers still carry the scars of legacy waterfall programmes – big budgets, blown timelines, shifting scopes. That makes it hard to trust new cost estimates, even when the dynamics have changed.

So what can we do differently?

One option is to rethink how we structure scope and pricing. Start by clearly defining the ‘core’ – the essential functionality and technical foundations where change should be limited and predictable. That’s where fixed pricing can work. Around that, layer the ‘edge’ – the areas where flexibility is essential and should be treated more like a burn rate model, perhaps tied to outcomes or delivery velocity.

This shift isn’t just happening in custom development. Commercial software vendors face the same pressures. But those locked into monolithic architectures are far less able to capitalise. Instead, we see the opposite: prices drifting up at contract renewal, driven not by rising input costs but by ownership structures or investor expectations.

In the end, the real differentiator will be the ability to measure outcomes meaningfully – and to do so early enough in the decision cycle to inform the build vs. buy debate. It’s not easy. But the ability to answer, with confidence, “what will this cost to get the outcome we want” is becoming one of the most critical capabilities in enterprise technology strategy today.