381–390 of 511 posts
More often than not, I'd have an architectural idea that I'm not that confident in. The process of talking with the LLM takes a long time but it helps me sharpen the initial approach or even come up with a new one depending on the requirements.
As a junior, i do actually enjoy going back and forth with the AI discussing different ways to implement something and exploring alternatives. More often than not, I'd have an architectural idea that I'm not that confident in. The process of talking with the LLM takes a long time but it helps me sharpen the initial approach or even come up with a new one depending on the requirements.
Earlier quoted context omitted.
I think as long as it continues to be tangibly better these people will still exist and the intersection will continue to be valuable enough to survive.
> as long as it continues to be tangibly better these people will still exist Sure. But how long will that last? LLMs are getting better at programming much faster than I am. Imagine a plot with time on the X axis and LLM skill on the Y axis. The line goes up and to the right. On the left is GPT3, or GPT3.5 with the very first glimmers of programming ability just a few short years ago. In the middle is Opus 4.7 now.…
I have no doubt they will be better programmers than almost every human that has ever existed. But the role of a SWE will expand to fill the gaps that the LLM paradigm hasn't filled:
- Accountability
- Long term architectural vision, goal setting
- Everchanging business context
- Mercurial executives, people problems, relationships etc...
I've hit this point with AI where it's not a simple process, but a long drawn out back and forth. I'll use AI to design the implementation of a medium sized, cross cutting feature. Review all the details, maybe iterate on just that. Then implement with Claude 4.7 Max - which runs slower, but does a better job. Then review the implementation, then have Codex GPT 5.5 xhigh fast review it - which almost always finds cor…
As a junior, i do actually enjoy going back and forth with the AI discussing different ways to implement something and exploring alternatives. More often than not, I'd have an architectural idea that I'm not that confident in. The process of talking with the LLM takes a long time but it helps me sharpen the initial approach or even come up with a new one depending on the requirements.
We may be in the last Golden age of AI, where experienced professionals still exist who can code manually, and AI already exists who can code automatically, and when the former use the latter skillfully, wonders happen. This magical intersection may not exist iin the future, or become very rare.
Token efficiency is going to be the next big thing. Tokenmaxxing an army of juniors will destroy your business through slop induced tech debt and API costs. A senior that uses AI but is token efficient will be like rocket fuel.
Did you write this comment with AI, or can you explain why so many people use the exact same terrible metaphor?
As a junior, i do actually enjoy going back and forth with the AI discussing different ways to implement something and exploring alternatives. More often than not, I'd have an architectural idea that I'm not that confident in. The process of talking with the LLM takes a long time but it helps me sharpen the initial approach or even come up with a new one depending on the requirements.
I've hit this point with AI where it's not a simple process, but a long drawn out back and forth. I'll use AI to design the implementation of a medium sized, cross cutting feature. Review all the details, maybe iterate on just that. Then implement with Claude 4.7 Max - which runs slower, but does a better job. Then review the implementation, then have Codex GPT 5.5 xhigh fast review it - which almost always finds cor…