Summary
Highlights
Dario Amodei, CEO of Anthropic, predicted that within 12 months, AI would be able to write all code, fully automated. The speaker highlights the importance of Dario's position in the AI space. Last year, Amodei predicted AI would write 90% of code within 3-6 months. The speaker agrees this timeline was aggressive but acknowledges its partial truth, depending on the field, language, company policies, and individual experience with AI.
For the speaker, AI currently writes 80-90% of their code for most projects. However, this isn't 'wipe coding' (not looking at the code at all) or AI doing it completely on its own without errors. Instead, AI can implement pre-planned tasks, but human review and steering are crucial. Developers remain responsible for the code, and AI still makes many mistakes. The speaker emphasizes that AI is a 'fast typer' for implementing detailed plans, not an autonomous developer.
The speaker clarifies that success with AI in coding requires extremely detailed plans, including specific libraries, patterns, and software architecture. This level of planning allows AI to generate a significant portion of the code, which then needs human review and fine-tuning. This approach makes coding faster than starting from scratch, but it doesn't mean AI does 90% of the work independently.
This year, Dario Amodei predicted AI would be able to write software end-to-end, fully on its own, within 6-12 months. The speaker expresses strong skepticism, finding it hard to imagine this coming true, not just in the near future but anytime soon. While acknowledging AI's capability for building software in a loop, the speaker argues that the full work of a software engineer involves much more than just code generation.
A software engineer's role encompasses building good plans, defining architecture and technologies, reviewing and analyzing code, fixing problems, and taking responsibility for the code. The speaker finds it difficult to foresee AI handling these complex, responsibility-laden tasks given its current limitations as a 'talented, fast writer' that requires clear guidance and makes mistakes. Achieving fully automated, error-free, and securely architected code by AI without extensive human oversight seems far off.
While recognizing the remarkable and steady progress of AI models and tools, the speaker believes this progress is not sufficient for full automation of software engineering in the near future. The speaker notes their open-mindedness and extensive use of AI, confirming it writes much of their code, but reiterates that it's far from full automation. The video concludes by inviting viewers to share their experiences and thoughts on AI in coding.