> I think what the author misses here is that imperfect, probabilistic agents can build reliable, deterministic systems. No one would trust a garbage collection

> I think what the author misses here is that imperfect, probabilistic agents can build reliable, deterministic systems. No one would trust a garbage collection tool based on how reliable the author was, but rather if it proves it can do what it intends to do after extensive testing. > but rather if it proves it can do what it intends to do after extensive testing. Author here: Here I was less talking about the effectiveness of the output of a given tool and more so about the tool itself. To take your garbage collection example, sure perhaps an agentic system at some point can spin some stuff up and beat it into submission with test harnesses, bug fixes etc. But, imagine you used the model AS the garbage collector/tool, in that say every sweep you simply dumped the memory of the program into the model and told it to release the unneeded blocks. You would NEVER be able to trust that the model itself correctly identifies the correct memory blocks and no amount of "patching" or "fine tuning" would ever get you there. With other historical abstractions like say jvm, if the deterministic output, in this case the assembly the jit emits is incorrect that bug is patched and the abstraction will never have that same fault again. not so with LLMs. To me that distinction is very important when trying to point out previous developer tooling that changed the entire nature of the industry. It's not to say I do not think LLMs will have a profound impact on the way things work in the future. But I do think we are in completely uncharted territory with limited historical precedence to guide us.