AI Automates Complex Code Porting, Redefining Developer Expertise

In a striking demonstration of AI's growing capabilities, an engineer leveraged OpenAI's Codex to port the OpenCV CSRT tracking algorithm from C++ to Rust in just one hour—a task that would traditionally demand days of meticulous coding. The AI not only translated the algorithm flawlessly but also generated a functional GUI, allowing for immediate integration into the developer's project without cross-compilation hassles. This feat, shared by Onur Ozkan, showcases how tools like Codex are transforming numerical computing workflows, automating up to 95% of the "low-level grunt work" involved in fields like computational mechanics and finite element methods (FEM).

Ozkan's experience underscores a seismic shift in developer roles. With years spent mastering intricate tasks like tensor math and solver code debugging—where a single sign typo could derail progress for days—he notes that AI now handles such pain points effortlessly. Yet, this automation comes with a caveat: while newcomers can "fast forward" through foundational work, they risk missing the deep, hard-won insights gained from manual implementation. As Ozkan observed, "Kids these days both have it easy and hard... They will never understand things as deeply as someone who wrote the whole thing by hand."

This paradox heralds the rise of "depth-on-demand," a meta-skill where developers must fluidly zoom between high-level AI assistance and granular problem-solving. When AI stumbles—such as generating subtle errors in complex numerical code—experts need to quickly diagnose issues, apply fixes, and return to abstraction. Ozkan emphasizes that success now hinges on adaptive learning: "The quicker you can pick up new skills and knowledge, the more successful you will be."

For the tech industry, this evolution demands a rethink of skill development. Educational programs and professional training must prioritize flexibility over rote specialization, preparing developers to partner with AI rather than compete against it. As automation reshapes coding, the true value lies not in writing every line, but in mastering the agility to dive deep when precision is paramount.

Source: Originally posted by Onur Ozkan on X (formerly Twitter) and detailed on solmaz.io.