The idea of self-healing code with LLMs is exciting, but balancing automation and human oversight is still crucial.

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By 2028, an estimated 75% of enterprise software engineers will use AI code assistants. While AI tools can increase productivity, they risk adding to technical debt if not used correctly. This post explores how self-healing code, enabled by large language models, can help mitigate technical debt. Such AI can automate code reviews, bug fixes, and dependency management. Success requires balancing automation with manual oversight, good data management practices, and continuous learning and training within teams.

How to Use Self-Healing Code to Reduce Technical Debt