AI changes the economics of software rewrites
thetruthasiseeitnow.com
July 9, 2026
2 min read
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50/100
Summary
AI impacts economics by favoring codebases with clear, common patterns over proprietary or inconsistent systems. The quality of AI output for coding tasks relies on the model's training data and the context provided, primarily derived from the existing codebase.
Key Takeaways
- AI changes the economics of software development by favoring codebases with clear, common patterns over proprietary or inconsistent systems.
- The quality of AI output is influenced by the model's training data and the context provided, particularly the structure of the codebase.
- Popular tech stacks give AI an advantage due to the abundance of examples, while proprietary languages require more effort for the model to understand.
- Rewriting codebases to establish clear patterns can enhance AI performance and reduce the time spent on training the model to understand inconsistent systems.
Community Sentiment
Positives
- Developing bespoke software solutions is now a lot cheaper than it used to be, making it a viable option for many businesses.
- Doing in days what used to take months feels like a game changer for the industry, revolutionizing how we approach software development.
Concerns
- LLMs are quite bad at large scale pattern fidelity, leading to code that feels like a patch-on-patch-on-patch mess.
- A rewrite preserving all behavior without observable changes is a recipe for disaster; AI should not be trusted to make those decisions.
- AI-generated content often feels formulaic and lacks depth, pointing to limits on what it can ultimately achieve.
