.@bchesky and @Jason recently claimed that AI will boost software developers' productivity by ~30% across industry. As a developer and IC at a major tech company, let me debunk that. 1. Software developers don't spend all their time coding. Typically, coding occupies less than half of a developer's time. The rest goes to parallelization costs (meetings, documentation, alignment, planning) and operations (monitoring metrics, configuring alarms/pipelines, debugging). This limits the time that can be saved. Even with improved coding efficiency, the overall productivity gain would be modest. 2. AI might expedite coding but not code reviews. Every competent tech company reviews all code before production, often by multiple devs. If I use AI-generated logic, I must first understand it such that I can defend it in code reviews. Review time for others remains unchanged. Some will choose to ship AI-written code without understanding which will lead to inevitable disaster. 3. AI models must be fine-tuned for in-house frameworks, libraries, and practices. While the base models can write code using open-source frameworks, they are useless when it comes to in-house development. Overcoming this issue requires fine-tuning which demands capital and—ironically—more software developers. Additionally, fine-tuning AI models to a company's internal software and documentation isn't a one-time task. As frameworks, libraries, and best practices evolve, the AI model requires continuous updates and fine-tuning, consuming significant resources and development time. 4. AI excels at teaching, not executing. Experienced developers will see far less value. Learning a new tech stack is where AI is most impactful. ChatGPT is the most patient and knowledgeable teacher you could ask for. For a tech stack I've mastered over the years though, AI offers minimal value. It might help with boilerplate, but I'll rely on my own expertise for critical code. While I see significant value in AI as a software development tool, its immediate impact is overestimated, particularly in large tech companies. Execs, VCs, and others without boots-on-the-ground engineering experience are swayed by demos and Twitter thread bois. It's exciting and novel, but the proof isn't in the pudding. Startups might see more impact. They lack in-house frameworks and prioritize shipping over quality. They might hire less experienced developers who benefit from AI as a learning tool. But a 30% boost? No way. Not this year.
