I’m fine with AI use in the back end, nobody really codes without something along the lines of copilot or claude anymore anyway.
Well that’s just straight up untrue. My org did an AI pilot to see if it was something we wanted to invest in and it ended up coming back with reduced productivity among devs (largely due to a massive increase in debugging time because of the slop output from the AI). Our devs write good code, faster, without the AI involved.
It’s mostly in management where we’ve seen productivity increases, because of how many emails they are writing on the average day and for transcription of meetings.
Heck, it is objectively measured by a LLM adjacent seller like Faros AI.
The more LLM code in your company, the slower delivery and more bugs that you likely find on production.
Literally data is at 60% of daily tasks being LLM assisted, the throughput is (every value is an average) 500% slower, company delivers 10% less and the bug rate is +50% per PR and +250% production incidents.
At 40% of daily task being LLM assisted the bug rate was +9% vs pre-LLM.
Well that’s just straight up untrue. My org did an AI pilot to see if it was something we wanted to invest in and it ended up coming back with reduced productivity among devs (largely due to a massive increase in debugging time because of the slop output from the AI). Our devs write good code, faster, without the AI involved.
It’s mostly in management where we’ve seen productivity increases, because of how many emails they are writing on the average day and for transcription of meetings.
Heck, it is objectively measured by a LLM adjacent seller like Faros AI.
The more LLM code in your company, the slower delivery and more bugs that you likely find on production.
Literally data is at 60% of daily tasks being LLM assisted, the throughput is (every value is an average) 500% slower, company delivers 10% less and the bug rate is +50% per PR and +250% production incidents.
At 40% of daily task being LLM assisted the bug rate was +9% vs pre-LLM.