GitHub Copilot: First Impressions
The AI coding approach is solving the wrong problem.  The problem isn&#x27;t with the low level detailed work.  That problem should be solved by building composable, tested, audited libraries.  Legos, if you will.<p>If the problem is trivial enough that you can completely trust the AI coded solution, then you could have either done it yourself very easily or used a premade solution from a good library or toolkit.<p>If the problem is not trivial, then you have the outsourcing challenges (which apply to a lot more scenarios than using AI to help you code).<p>If you are not personally capable of judging the outsourced work, then whether you use AI or type it yourself, you will end up with errors or misfeatures.<p>If you are capable of judging, then you must pay attention and read&#x2F;review.  So your job shifts from defining the problem and programming a solution to defining the problem and reviewing potential solution(s).  Either way, you must focus and think.  But again, perhaps you would be better off building a solution composed of known good blocks.  &lt;- This should be the future of software development...<p>Sadly, I think that open source and freedom to (re)invent has worked against us in the long run.  If instead of each of us going off and thinking, &quot;I can make a better language&#x2F;framework&quot;, we had built on existing technologies, I daresay we would be further along.  To be fair of course, some level of dissatisfaction and divergence would be necessary or we would still be using assembly.<p>Github does have one thing right though (from a business perspective) - they are making a remedy to a symptom, and in that they can expect longer term revenue than if they actually solved the core problem.