> AI is much better than strong engineers at writing very short programs: in particular, it can produce ten to thirty lines of straightforward mostly-working code faster than any engineer.
> How can you leverage this? There’s not much demand for this kind of program in the day-to-day of a normal software engineer. Usually code either has to be a modification to a large program, or occasionally a short production-data script (such as a data backfill) where accuracy matters a lot more than speed.
While this may be technically correct — there’s little demand for standalone small programs — it overlooks a crucial reality: the demand for small code segments within larger workflows is enormous.
Software development (in my experience) is built around composing small units — helpers, glue code, input validation, test cases, config wrappers, etc. These aren’t standalone programs, but they’re written constantly. And they’re exactly the kind of 10–30 line tasks where LLMs are most effective.
Engineers who break down large tasks into AI-assisted microtasks can move faster. It’s not about replacing developers — it’s about amplifying them.
> AI is much better than strong engineers at writing very short programs: in particular, it can produce ten to thirty lines of straightforward mostly-working code faster than any engineer.
> How can you leverage this? There’s not much demand for this kind of program in the day-to-day of a normal software engineer. Usually code either has to be a modification to a large program, or occasionally a short production-data script (such as a data backfill) where accuracy matters a lot more than speed.
While this may be technically correct — there’s little demand for standalone small programs — it overlooks a crucial reality: the demand for small code segments within larger workflows is enormous.
Software development (in my experience) is built around composing small units — helpers, glue code, input validation, test cases, config wrappers, etc. These aren’t standalone programs, but they’re written constantly. And they’re exactly the kind of 10–30 line tasks where LLMs are most effective.
Engineers who break down large tasks into AI-assisted microtasks can move faster. It’s not about replacing developers — it’s about amplifying them.