Companies are learning the hard way that relying solely on large language models (LLMs) to replace developers can lead to brittle systems, runaway cloud bills, and a painful rebuild. The initial promise of “software will soon be free” has proven to be an illusion. LLMs can generate code, but they cannot replicate human judgment and oversight.
Many companies have mistakenly treated AI as a developer replacement rather than a tool to amplify engineering capabilities. This approach has resulted in unmaintainable generated code, security vulnerabilities, and operational instability. The cost of this approach is high: cloud costs skyrocket, teams struggle to understand the code, and the organization becomes increasingly dependent on the system.
To succeed in the future, companies must pair developers with AI tools, invest in platform discipline, and demand measurable quality and maintainability. They must treat the model as a power tool, not an employee, and remember that software is stewarded, not just produced. By taking this approach, enterprises can harness the benefits of AI while avoiding its pitfalls and creating more resilient, secure, and cost-efficient systems.
Source: https://www.infoworld.com/article/4141358/the-ai-coding-hangover.html