As long as we don't have AGI or superintelligence, we still need good software engineers. And even if we do reach AGI and coding is "solved," are we really supposed to just trust the generated code?

Outsourcing our cognitive thinking and understanding isn't the way to advance as humans, nor is it the way to stay ahead of AI. If we give that up, how do we limit AI slop? And how would we even pull the plug, if it came to that?

Understanding computer science concepts and developing good software engineering practices is still very much in demand, even as most students and engineers seem to be letting their coding and algorithmic reasoning skills atrophy.

Time to build those back up, in a fun and engaging way. If AI is good for one thing here, it's helping us learn, not thinking for us.

That's why we built a Claude skill that teaches computer science concepts by having Claude guide you through implementing their core components from scratch. It's open source and still early, so it's very much open to community contributions, with the goal of promoting computer science and algorithmic thinking.

Main skill repo: https://github.com/csacademy-ma/learn-by-building

Example exercises generated by the skill: https://github.com/csacademy-ma/learn-by-building-samples