This is an interesting conversation: some of you correctly pointing out that so much AI driven development is not having a positive effect on business profitability, and others correctly pointing out positive results that give evidence for great future progress.
I have an unusual set of metrics for evaluating AI. I am old and comfortably retired but I still like to experiment with AI tools for updating many of my old (or ancient) open source projects and creating new projects. I am blown away by how good my dedicated Hermes Agent setup on a VPS and also running Google AntiGravity with Claude and Gemini are. Both systems are unbelievably good.
I can only imagine how effective companies with a solid engineering process will be as appropriate roles for human and AI developers solidify. I can also imagine companies with a poor process and poor engineering taste will waste a lot of money.
Where is the software that is produced using the purported efficiency gains and why are you pulling up the ladder behind you?
If you were in AI for such a long time, of course you are biased and want to see it succeed.
Look at what has been written in open source since 2023. Very little. There are no efficiency gains and the incessant talk about prompts and AI just paralyzes the entire field. And people who love to talk have the ears of the managers.
I have an unusual set of metrics for evaluating AI. I am old and comfortably retired but I still like to experiment with AI tools for updating many of my old (or ancient) open source projects and creating new projects. I am blown away by how good my dedicated Hermes Agent setup on a VPS and also running Google AntiGravity with Claude and Gemini are. Both systems are unbelievably good.
I can only imagine how effective companies with a solid engineering process will be as appropriate roles for human and AI developers solidify. I can also imagine companies with a poor process and poor engineering taste will waste a lot of money.