Excerpt:
“Even within the coding, it’s not working well,” said Smiley. “I’ll give you an example. Code can look right and pass the unit tests and still be wrong. The way you measure that is typically in benchmark tests. So a lot of these companies haven’t engaged in a proper feedback loop to see what the impact of AI coding is on the outcomes they care about. Lines of code, number of [pull requests], these are liabilities. These are not measures of engineering excellence.”
Measures of engineering excellence, said Smiley, include metrics like deployment frequency, lead time to production, change failure rate, mean time to restore, and incident severity. And we need a new set of metrics, he insists, to measure how AI affects engineering performance.
“We don’t know what those are yet,” he said.
One metric that might be helpful, he said, is measuring tokens burned to get to an approved pull request – a formally accepted change in software. That’s the kind of thing that needs to be assessed to determine whether AI helps an organization’s engineering practice.
To underscore the consequences of not having that kind of data, Smiley pointed to a recent attempt to rewrite SQLite in Rust using AI.
“It passed all the unit tests, the shape of the code looks right,” he said. It’s 3.7x more lines of code that performs 2,000 times worse than the actual SQLite. Two thousand times worse for a database is a non-viable product. It’s a dumpster fire. Throw it away. All that money you spent on it is worthless."
All the optimism about using AI for coding, Smiley argues, comes from measuring the wrong things.
“Coding works if you measure lines of code and pull requests,” he said. “Coding does not work if you measure quality and team performance. There’s no evidence to suggest that that’s moving in a positive direction.”
“Why do I have to take 5 extra steps to just quickly save a file onto my computer, without needing literally everything on the cloud, especially if I am on a laptop on a device currently in airplane mode, most likely in a literal airplane in an area without reliable Internet connectivity?”
Also consider that there are places - third world nations, and so very MANY areas within supposedly “first-world” ones - that do not have reliable Internet, even today. The KISS principle still applies now, as it did back then too. Your argument screams privileged access, without acknowledging those basic precepts, including perpetual access to subscription services, which must always be maintained, e.g. even after someone retires.
And I disagree in that arguments of the form “LLMs currently do not perform better than my own human effort, in my inexperienced hands at least” will be outdated a decade from now. If LLMs get better, then they will become the musings of people who struggled with early tech before it was fully ready, which does not somehow invalidate their veracity especially in the historical sense.