Two engineers with an AI coding assistant, for one week. That’s roughly $7,700 of salary to rebuild a tool your company pays $30,000 a year for (illustrative numbers, the full model is in Exhibit 1).
On paper, the math looks obvious. And more teams are running it, because software bills keep climbing. The average organisation in Zylo’s 2026 SaaS Management Index spends $55.7 million a year on SaaS, up 8% in a year.
Traditionally, when a company wanted a new tool, say a CRM or a ticketing system, it would license a ready-made solution. Now that AI tools get better every month, many teams are asking, what if we build this ourselves?
This used to be a debate for large organisations with large engineering teams. Today, it’s a common conversation between a startup’s CEO and CTO.
When everything is so cheap to build, what is the case for buying anymore?
Sponsored by Hyphenate
Finance is where “we’ll build it ourselves” gets expensive fast, because every reconciliation needs someone accountable for it.
Hyphenate just raised $45 million in Series A funding to scale autonomous finance for the office of the CFO.
▫️ Does the work: reconciles cash, runs invoicing, maintains subledgers and moves the close forward
▫️ Keeps people in charge: learns from every exception your team resolves and leaves the judgment calls to them
▫️ Fits your stack: layers onto your ERP and banking systems and keeps evidence behind every action
Key Takeaways
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Software has 2 costs: making it and owning it. AI coding tools cut the first one, so owning the tool is now the bigger bill.
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Owning code eats engineering time. In Stripe’s Developer Coefficient survey, developers estimated that 17.3 of a 41.1-hour week goes to maintenance, about 42%.
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Internal builds look cheap because their upkeep hides inside engineers’ salaries. Give each one a shadow budget line.
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Vendors get the same AI discount and spread upkeep across their whole base. In MIT NANDA’s 2025 research, AI tools bought from specialised vendors succeeded about 67% of the time, against about a third of the time for internal builds.
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AI-written code creates comprehension debt. In Anthropic’s trial, developers who used AI scored 50% on a quiz about the code they had just written, against 67% for those who coded by hand. Build small, low-risk tools with a written exit, and buy anything whose failure would be catastrophic.
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