Practical Considerations for Advancing AI Collaboration in Software Development
TL;DR Human-in-the-loop is essential; AI offers probability, not certainty. AI excels at word-smithing , so spend more time on documentation and context. Leverage diverse AI models for varied research, improvements, and analysis. Be wary of deskilling : if AI makes a task trivial, agents may soon replace it. You should feel like you are testing the boundaries of what AI is capable of for at least some tasks. The Problem AI’s proficiency in handling routine coding allows human engineers to dedicate more time to strategic activities such as system design, architectural planning, intricate requirement elicitation, and the rigorous evaluation of application performance across multifaceted metrics. Tools often amplify underlying behaviours and failures — Rob Lambert Value is increasingly found not in rote knowledge, which AI can often provide, but in the capacity to frame complex problems effectively for AI, critically evaluate its probab...