How AI Accelerates Development and Exposes Flawed Business Decisions
The article argues that while AI has dramatically sped up developers' work, the old excuse of "slow" no longer holds, revealing deeper issues in business judgment, cost structures, and strategic direction.
Common belief that developers must improve efficiency
Programmers are often judged by three factors: high salaries, perceived slow development, and being the most visible part of the delivery chain. This leads to the assumption that the most expensive and slowest role should be optimized.
“Development slow” as a convenient explanation
Typical retrospective questions include:
Why isn’t it online yet?
Why is this requirement dragging?
Why is development efficiency low?
How to increase delivery speed?
Commonly proposed solutions are uniformly:
Introduce processes
Adopt new tools
Enforce standards
Apply agile practices
Use low‑code platforms
Make programmers a bit faster.
Few ask whether slowness is the actual problem or merely the easiest scapegoat.
AI removes the speed bottleneck
AI makes programmers genuinely faster: code is written more quickly, requirement changes are handled faster, delivery accelerates, and many repetitive tasks disappear.
Observed changes after AI adoption:
Development cycles noticeably shorter
Iteration frequency clearly higher
Delivery speed much faster
Business outcomes remain limited:
User growth average
Revenue unchanged
Product still fails to launch
Why isn’t the business taking off?
Shift from speed to cost and direction
When efficiency improves but business performance stalls, the discussion shifts to cost reduction.
Reduce cost.
Efficiency is already higher
Business still shows no progress
Problem is not in speed
Problem lies in cost structure
Resulting narratives focus on:
Too many people
High personnel cost
Organizational optimization needed
Resource reallocation required
Underlying strategic question
Was the initial direction wrong?
The core challenge becomes deciding what to build and whether it should be built at all, rather than how quickly it can be implemented.
Conclusion
AI accelerates developers, exposing deeper issues that were previously hidden behind the “slow” excuse. The fundamental problem remains making correct strategic decisions rather than merely speeding up implementation.
Code example
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