Two years ago, if a mid-sized business came to us with a problem that needed a custom software solution, we'd have a hard conversation early. Custom software is expensive. It takes time. The build cost is just the beginning. For most organisations, unless the problem was central enough to justify a multi-year commitment, the answer was usually: find a SaaS product that's close enough and live with the gaps.
That calculation has changed. Fundamentally, and faster than most organisations have realised.
What's Actually Different
The shift isn't just that developers can write code faster. The economics of software delivery have been restructured.
Delivery timelines have compressed dramatically — not incrementally:
- Work that used to take a year now takes three to four months
- Work that used to take three months now takes three to four weeks
- Prototypes that validate an idea can be in hand in days
The quality bar isn't lower. In many cases it's higher, because engineers have more time for the work that actually requires careful thinking. This isn't theoretical — it's what we're delivering for clients across regulated industries right now.
What This Unlocks
Problems that weren't worth solving before now are. A workflow inefficiency that costs your team ten hours a week, or a customer experience that's been 80% of what it should be for years — these problems often didn't justify a custom build under the old economics. The threshold for "worth addressing with software" has shifted considerably.
You can own your workflow instead of fitting it to someone else's. Off-the-shelf SaaS products are built for the median customer. Custom software is built for your exact workflow, your data model and your specific integration requirements. As the cost of custom comes down, the tradeoff looks different.
Full ownership means no lock-in. One of the underappreciated costs of SaaS dependency is what happens when the vendor changes pricing, changes the product or gets acquired. Custom software is yours — you control the roadmap, the data and the integrations.
The Catch
The drop in delivery cost doesn't mean the problem of delivery is solved.
Building fast with AI still requires experienced engineers who can review what's being generated, maintain quality, architect systems that are maintainable and make the judgment calls that AI can't. The cost of senior engineering expertise hasn't gone down — what's changed is the leverage that expertise creates.
It also means organisations need to think about stewardship, not just delivery. Software that ships isn't software that's done. AI products in particular need ongoing monitoring, tuning and iteration.
The Opportunity Right Now
The organisations that move fastest are the ones that recognise this shift and act on it — not by rushing into builds without thinking, but by taking a clear-eyed look at the problems they've been unable to address because the cost was too high, and asking whether that calculation has changed.
In most cases, it has.