So far most impressive AI achievements for me were both by ChatGPT o1 pro:
Case one. I configured IPsec VPN on a host machine which run docker containers. Everything worked from the host itself, however containers were not able to reach IPsec subnet. I spent quite a bit of time, untangling docker iptables rules, figuring out how iptables interacts with IPsec, running tcpdumps everywhere. However my skills were not enough, probably I would resolved the issue given more time, however I decided to try ChatGPT. I made a very thorough question, added everything I tried, related logs and stuff. Actually I wanted to ask the question on some Linux forums, so I was preparing the question. ChatGPT thought few minutes and then spewed one iptables command which just resolved the issue. I was truly impressed.
Case two. I was writing firmware for some device using C. One module was particularly complex, involved management of two RAM buffers and one external SPI buffer. I spent two weeks writing this module and then asked ChatGPT to review my code for major bugs and issues. ChatGPT was able to find out that I used SPI to talk to FRAM chip, it understood that my command usage was subtly wrong (I sent WREN and WRITE commands in the one SPI transaction) and highlighted this issue. I tried other modes, I also tried Claude, but so far only o1 pro was able to find that issue. This was impressive because it required to truly understand the workflow of the code and it required extensive knowledge of protocols and their typical usages.
Other than that, I don't think I was impressed by AI. Of course I'm generally impressed by its progress, it's marvellous that AI exists at all and can write some code that makes sense. But so far I didn't fully integrate AI into my workflows. I'm using AI as Google replacement for some queries, I use AI as a code reviewer and I'm using Copilot plugin as a glorified autocomplete. I don't generate any complex code with it and I rarely generate any meaningful code at all.
Case one. I configured IPsec VPN on a host machine which run docker containers. Everything worked from the host itself, however containers were not able to reach IPsec subnet. I spent quite a bit of time, untangling docker iptables rules, figuring out how iptables interacts with IPsec, running tcpdumps everywhere. However my skills were not enough, probably I would resolved the issue given more time, however I decided to try ChatGPT. I made a very thorough question, added everything I tried, related logs and stuff. Actually I wanted to ask the question on some Linux forums, so I was preparing the question. ChatGPT thought few minutes and then spewed one iptables command which just resolved the issue. I was truly impressed.
Case two. I was writing firmware for some device using C. One module was particularly complex, involved management of two RAM buffers and one external SPI buffer. I spent two weeks writing this module and then asked ChatGPT to review my code for major bugs and issues. ChatGPT was able to find out that I used SPI to talk to FRAM chip, it understood that my command usage was subtly wrong (I sent WREN and WRITE commands in the one SPI transaction) and highlighted this issue. I tried other modes, I also tried Claude, but so far only o1 pro was able to find that issue. This was impressive because it required to truly understand the workflow of the code and it required extensive knowledge of protocols and their typical usages.
Other than that, I don't think I was impressed by AI. Of course I'm generally impressed by its progress, it's marvellous that AI exists at all and can write some code that makes sense. But so far I didn't fully integrate AI into my workflows. I'm using AI as Google replacement for some queries, I use AI as a code reviewer and I'm using Copilot plugin as a glorified autocomplete. I don't generate any complex code with it and I rarely generate any meaningful code at all.