Picture a software business a few years into its growth. The product works, customers renew and revenue is climbing, yet every release takes more effort than the last and nobody can quite say why. It’s a story I hear more than any other.
Growth also raises the stakes. Customers bring tougher questions about security, and with good reason: government figures show 67% of medium-sized businesses suffered a cyber breach or attack last year. At the same time, 84% of developers now use or plan to use AI tools. Code has never been cheaper to write, but the responsibility for owning it hasn’t gone away. Both put more weight on the technology underneath the product.
So why does software that works stop scaling? Rarely because of one big failure. More often, the foundations were built for the business you were, not the one you’re becoming. Below are some patterns I’ve seen across the market. Every business is different, so not all will apply, but they’re worth checking for.
In the early years, building whatever the next deal needs, and taking a few shortcuts to get there, is often exactly the right call. The challenge comes when shortcuts become the norm and every sprint goes on new features. Upgrades, monitoring and maintenance get squeezed, and automated test coverage stays sparse.
For a while, nobody notices. Then shortcuts harden into workarounds, each new feature becomes harder to build, and ageing software makes upgrades more complicated. Bugs surface unexpectedly, releases get bigger and less frequent, and the database that handled ten thousand records starts to struggle with ten million. Without proper visibility into the system, customers can end up spotting problems first.
You’ll often see it in the roadmap before you see it in the code, as plans start to be shaped by what feels safe rather than what customers need. Simple changes take weeks, and “that will touch everything” becomes a familiar refrain in planning meetings. Hiring alone rarely solves it, because new engineers tread on each other’s work while the corners of the codebase nobody wants to touch, often written by someone who has since left, stay exactly as they are.
The hosting bill tells its own story too. If costs rise as fast as your customer base, the architecture starts eating into your margin. And once product conversations regularly start with “we can’t do that because…”, technology has gone from enabling growth to constraining it, which is often when the questions from outside get harder too.
Public sector buyers and larger enterprises will want certifications such as Cyber Essentials Plus or ISO 27001, recent penetration test results and clear answers about where their data lives. At that point, security stops being purely an IT matter and starts influencing whether deals are won or lost.
What these reviews uncover is rarely exotic: early staff who still have admin rights to everything, shared passwords, leavers who were never fully offboarded, and customer data kept apart by habit rather than by design. Backups may exist but have never been restored, and an untested backup isn’t much of a recovery plan.
Data follows a similar pattern. Reports run straight off the live system and slow it down for customers, while messy and duplicate records go unnoticed until someone tries to analyse them or build an AI feature on top. It’s why many AI projects run into challenges with data rather than models.
All of this is technical debt, and every software business carries some. Early shortcuts are often what got the product to market in the first place. Like financial debt, it only becomes a problem when the interest outweighs what it bought you, whether that means more effort going on workarounds than new development, or deals being held back because of it.
The temptation then is a heroic rewrite, but in my experience those seldom land. What works is less dramatic: make the debt visible, explain it in business terms and give it a steady share of the team’s time, often 15–20%. When we look at a business, we don’t expect zero debt. We look for a team that knows where it is, what it costs and how it plans to deal with it. AI, meanwhile, is adding a new dimension to all of this.
AI has cut the cost of writing code, but not the cost of owning it. Reviewing, testing and securing that code are increasingly the real bottlenecks. With good tests, a clear structure and up-to-date documentation, AI can help a team ship more, safely. Without those foundations, it can simply create more code that needs to be understood, reviewed and maintained.
This matters beyond the codebase, too. The platforms that thrive will be the ones that work openly with other systems and, where it makes sense, with AI. That ability starts with the same basics.
Start with where the business is going rather than with the technology. Ask what tripling your revenue would really demand of your product, data and team, then work back from there. The biggest wins are usually unglamorous, and five questions will quickly tell you where you stand:
Fixing these takes more than technical changes, though. It also takes the right people. Put engineering and product leadership in place before you need it, not after. That raises a question founders sometimes leave until later. The people who build a brilliant first version aren’t always best placed to run what comes next, and that’s no criticism. The strongest founders play to their strengths and bring in the experience they need around them.
As for that business we pictured at the start, none of its problems were a sign of failure. If anything, they were a sign that the company had grown faster than its foundations. Your technology is a commercial asset, and anyone investing in your business will look closely at it. Get the foundations right, and growth becomes something your technology is ready to support.
If you’ve built an ambitious software or tech-enabled services company and are considering its next chapter, we’d love to hear your story. Get in touch at enquiries@elevaresoftware.com.
.png)
Charlie Pickering has 30+ years experience in private equity-backed organisations. He leads technology strategy at Elevare Software Group, supporting portfolio businesses to build resilient, scalable platforms. He specialises in engineering transformation, product modernisation, cloud platform delivery, and unlocking greater value from data and emerging AI capabilities.



If you run a software company and are considering your next chapter, we’d love to hear from you.
enquiries@elevaresoftware.com