Comment by mmaunder
2 months ago
But my AI didn't do what your AI did.
Cherry picked AI fail for upvotes. Which you’ll get plenty of here an on Reddit from those too lazy to go and take a look for themselves.
Using Codex or Claude to write and optimize high performance code is a game changer. Try optimizing cuda using nsys, for example. It’ll blow your lazy little brain.
Yeah right. A LLM in the hands of a junior engineer produces a lot of code that looks like they are written by juniors. A LLM in the hands of a senior engineer produces code that looks like they are written by seniors. The difference is the quality of the prompt, as well as the human judgement to reject the LLM code and follow-up prompts to tell the LLM what to write instead.
Lol what. The difference is that the senior... is a senior. Ask yourself what characteristics comprises a senior vs junior...
You're glossing over so much stuff. Moreover, how does the Junior grow and become the senior with those characteristics, if their starting point is LLMs?
I’m not glossing over anything. You and I are talking about the exact same thing phrased differently. How does a senior know when to reject some LLM code and start over? Experience. I don’t disagree with you but your tone is aggravating.
This. I really wonder how trainees are supposed to grow in an age where they are asked not to code themselves but guide a machine doing so.
Prompting is just step 1. Creating and reviewing a plan is step 2. Step 0 was iterating and getting the right skills in place. Step 3 is a command/skill that decomposes the problem into small implementation steps each with a dependency and how to verify/test the implementation step. Step 4 is execute the implementation plan using sub agents and ensuring validation/testing passes. Step 5 is a code review using codex (since I use claude for implementation).
I kind of agree. But I'd adjust that to say that in both cases you get good looking code. In the hands of a junior you get crappy architecture decisions and complete failure to manage complexity which results in the inevitable reddit "they degraded the model" post. In the hands of seniors you get well managed complexity, targeted features, scalable high performance architecture, and good base technology choices.
It’s easy to get AI to write bad code. Turns out you still need coding skills to get AI to write good code. But those who have figured it out can crank out working systems at a shocking pace.
Agreed 100%. I'd add that it's the knowledge of architecture and scaling that you got from writing all that good code, shipping it, and then having to scale it. It gives you the vocabulary and broad and deep knowledge base to innovate at lightning speeds and shocking levels of complexity.
I am sorry for asking, but... is there guide even on how to "figure it out"? Otherwise, how are you so sure about it?
Right here: https://codemanship.wordpress.com/2025/10/30/the-ai-ready-so...
This series of articles is gold.
Unsurprisingly, writing good software with AI follows the same principles as writing it without AI. Keep scopes small. Ship, refactor, optimize, and write tests as you go.
When a new technology emerges we typically see some people who embrace it and "figure it out".
Electronic synthesisers went from "it's a piano, but expensive and sounds worse" to every weird preset creating a whole new genre of electronic music.
So it seems plausible, like Claude's code, that our complaints about unmaintainable code are from trying to use it like a piano, and the rave kids will find a better use for it.
I'm working on one here: https://simonwillison.net/guides/agentic-engineering-pattern...
That's actually a great question. Truth be told the best way right now is to grab Codex CLI or Claude CLI (I strongly prefer Codex, but Claude has its fans), and just start. Immediately. Then go hard for a few months and you'll develop the skills you need.
A few tips for a quickstart:
Give yourself permission to play.
Understand basic concepts like context window, compaction, tokens, chain of thought and reasoning, and so on. Use AI to teach you this stuff, and read every blog post OpenAI and Anthropic put out and research what you don't understand.
Pick a hard coding problem in Python or Typescript and take a leap of faith and ask the agent to code it for you.
My favorite phrase when planning is: "Don't change anything. Just tell me.". Save this as a tmux shortcut and use it at the end of every prompt when planning something out.
Use markdown .md docs to create a planning doc and keep chatting to the agent about it and have it update the plan until you're super happy, always using the magic phrase "Don't change anything. Just tell me." (I should get myself a patent on that little number. Best trick I know)
Every time you see an anti-AI post, just move on. It's lazy people making lazy assumptions. Approach agentic coding with a sense of love, excitement, optimism, and take massive leaps of faith and you'll be very very surprised at what you find.
Best of luck Serious Angel.
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How do you figure anything out? You go use it, a lot.