I am not sure software engineering was ever what we thought it was
18 hours ago
- #Cognitive Debt
- #AI in Software Development
- #Career Evolution
- The analogy of a professional footballer's evolving career is applied to software engineers, highlighting that career evolution is inevitable and should be embraced rather than resisted.
- The rise of AI in software development is reshaping skill sets, with middle managers being laid off and developers transitioning to part-time product roles, indicating a reshuffling of competencies.
- Historically, learning software engineering was hands-on, but AI's growing role may reduce deep learning from tasks, potentially leading to skill atrophy even as its use becomes obligatory for efficiency.
- Cognitive death and cognitive surrender are distinguished as risks when using AI, where the former involves losing understanding of systems, and the latter is blindly accepting AI outputs, both accumulating cognitive debt.
- The economic sustainability of AI tools like those from OpenAI and Anthropic is questioned, as current subsidized models may not represent future realities, urging caution in over-reliance.
- An alternative approach to AI involves using it to enhance code quality and thoughtful exploration, such as generating tests and examining edge cases, rather than just speeding up output.
- The core value of software engineering is reframed as understanding problems deeply to know what to ask for, rather than merely translating human intent to machines, which is becoming easier with AI.
- While AI agents can assist in rapid prototyping and exploring design options, the cognitive load to ensure long-term maintainability often makes manual coding for core features more cost-effective.
- Despite challenges, AI is revolutionizing software development, and learning to use it effectively is essential, as evidenced by experienced developers adopting LLMs despite past reluctance to other tools.