Navigating the Complexity of LLMs in Software Development
The emergence of Large Language Models (LLMs) as a potential abstraction layer for software development is intriguing, but challenges remain. While they promise a streamlined process—turning prompts into systems, akin to compilers—serious issues persist.
Key Considerations:
- Complexity Increases: Software is never static; changing requirements elevate complexity. Despite technological advancements, even the best engineers struggle with this reality.
- AI Limitations: Current LLMs grapple with non-determinism and hallucination. Even if these problems were resolved, AI would encounter the same challenges as human developers, possibly even faster.
- Cost-Benefit Analysis: Building out a 500k LOC codebase with today’s LLMs could take days and incur significant expenses, shifting workload from human cognition to machine resources.
Ultimately, we can’t escape the 2nd law of thermodynamics: processing information requires energy.
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