If you're working in software development in 2026, you've probably already had this conversation with a client, founder, or manager.
They’ve seen GitHub Copilot demos. They’ve read that AI makes developers 55% faster. Maybe they even used Claude to scaffold an MVP over a weekend.
Now they want to know:
"Why hasn’t software become 60% cheaper?"
It’s a fair question.
But it’s based on a misunderstanding of where project time actually goes.
For decades, software projects have roughly followed the 40-20-40 rule:
• ~40% planning and design
• ~20% coding
• ~40% QA, testing, integration, deployment, and stabilization
AI has absolutely transformed that middle 20%.
Coding tasks that once took days can now take hours. In many workflows, the coding portion has effectively compressed from ~20% down to somewhere around 8% to 12%.
That productivity gain is real.
But the burden didn’t disappear. It shifted.
And that’s the part most headlines skip.
Stack Overflow’s 2025 developer survey found that 45% of developers say debugging AI-generated code is actually more time-consuming than writing code manually.
Sonar’s 2026 survey found that 96% of developers still don’t fully trust AI-generated output without human review.
The result is what many teams are quietly calling the “2026 Quality Tax.”
Teams save time generating code, then spend that time validating, debugging, testing, reviewing, and production-hardening it.
Especially on large or complex systems.
And the 40% on either side of coding?
Still overwhelmingly human.
Requirements gathering is still messy. Stakeholders still change priorities halfway through development. Architecture still requires judgment. Security still requires expertise. Production incidents still require humans who understand systems deeply enough to debug edge cases under pressure.
That’s why the realistic industry expectation for AI-driven software cost reduction is closer to 10% to 25%.
Not 60%.
The agencies offering massive discounts usually aren’t removing effort.
They’re removing process.
Less QA. Less testing. Less review. Less resilience.
And eventually the technical debt arrives like a boomerang wrapped in fire 🔥
The more interesting question isn’t:
"How much cheaper can software become?"
It’s:
"If AI makes teams faster, what additional value can we ship within the same timeline and budget?"
That’s where the real shift is happening.
👉 Full breakdown with data and sources on FoundersBar: https://foundersbar.com/articles-and-research/why-software-development-quotes-arent-dropping
For the devs here: has AI actually reduced your total workload, or has it mostly shifted your time from coding into reviewing and debugging?
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