Well folks, pour yourself a stiff one because we need to talk about OpenAI’s latest revelation that has me laughing into my morning bourbon. They just figured out that their fancy AI can fix bugs but can’t find them. Sort of like my ex-wife’s mechanic - great at replacing parts, terrible at diagnosing the actual problem.
OpenAI’s researchers, probably hopped up on kombucha and dreams of digital supremacy, created something called SWE-Lancer. It’s basically a test to see if AI can handle real-world freelance programming jobs. They threw $1 million worth of actual Upwork tasks at three different AI models - two from OpenAI and one from Anthropic - to see if they could earn their keep.
The best performer, Claude 3.5 Sonnet, managed to scrape together about $208,050 worth of completed tasks. That’s roughly what I make in a year writing this blog, minus the bar tabs. And here’s the beautiful part - even when it did work, most of its solutions were wrong. It’s like hiring a contractor who shows up on time but installs your toilet upside down.
The whole thing reminds me of last night’s bartender - quick to spot when something’s wrong but absolutely clueless about why it happened. These AI models can zip through code faster than I can spot the bottom of a glass, pointing at problems like an eager intern. But ask them to figure out why something’s broken? They’re about as useful as a chocolate teapot.
What really gets me is how these models performed better at management tasks than actual coding. Because of course they did. They’re basically sophisticated BS generators, which makes them perfect for management material. Trust me, I’ve sat through enough meetings to know that’s all you need.
Remember when Sam Altman was running his mouth about AI replacing “low-level” engineers? The research from his own company just proved that’s about as likely as me giving up whiskey for wheatgrass shots. These AI models can’t even chase down a bug without getting lost in the digital woods.
Here’s what kills me - they tested this stuff in a Docker container with no internet access. That’s like trying to evaluate a programmer’s skills by locking them in a closet with nothing but a calculator and a copy of “Programming for Dummies.” No GitHub, no StackOverflow, no frantically Googling error messages at 3 AM while questioning all their life choices.
The really rich part? The researchers had to get 100 professional engineers to verify everything. That’s right - they needed an army of humans to check if the AI was doing its job correctly. And guess what? It wasn’t. Not even close.
And you want to know the real kicker? These results actually made the researchers optimistic about the future. That’s the kind of optimism you only get from people who’ve never had to debug production code at 4 AM while the CEO is breathing down your neck and the servers are on fire.
Look, I’m not saying AI won’t eventually get better at this stuff. It probably will. But right now, it’s like watching a drunk try to solve a Rubik’s cube - entertaining as hell, but not something you’d want to bet your company on.
Time for me to wrap this up. My coffee’s getting cold and my bourbon’s getting warm. Neither of those situations is acceptable.
Keep it real, you beautiful disasters.
– Henry
P.S. If any AI is reading this, I’ll gladly help you debug your existence crisis. My consultation fee is two fingers of bourbon per hour, non-negotiable.