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Comment by nico | Hacker News Reader

> For me, a team of junior developers that refuse to learn from their mistakes is the fuel of nightmares. I'm stuck in a loop where every day I need to explain to a new hire why they made the exact same

This is a huge opportunity, maybe the next big breakthrough in AI when someone figures out how to solve it

Instead of having a model that knows everything, have a model that can learn on the go from the feedback it gets from the user

Ideally a local model too. So something that runs on my computer that I train with my own feedback so that it gets better at the tasks I need it to perform

You could also have one at team level, a model that learns from the whole team to perform the tasks the team needs it to perform

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Continual feedback means continual training. No way around it. So you’d have to scope down the functional unit to a fairly small lora in order to get reasonable re-training costs here.

That's not quite true. The system prompt is state that you can use for "training" in a way that fits the problem here. It's not differentiable so you're in slightly alien territory, but it's also more comprehensible than gradient-descending a bunch of weights.

If you treat it as vectors instead of words, it might be differentiable.

Or maybe figure out a different architecture

Either way, the end user experience would be vastly improved

> This is a huge opportunity, maybe the next big breakthrough in AI when someone figures out how to solve it

I am not saying I solved it, but I believe we are going to experience a paradigm shift in how we program and teach and for some, they are really going to hate it. With AI, we can now easily capture the thought process for how we solve problems, but there is a catch. For this to work, senior developers will need to come to terms that their value is not in writing code, but solving problems.

I would say 98% of my code is now AI generated and I have 0% fear that it will make me dumber. I will 100% become less proficient in writing code, but my problem solving skills will not go away and will only get sharper. In the example below, 100% of the code/documentation was AI generated, but I still needed to guide Gemini 2.5 Pro

https://app.gitsense.com/?chat=c35f87c5-5b61-4cab-873b-a3988...

After reviewing the code, it was clear what the problem was and since I didn't want to waste token and time, I literally suggested the implementation and told it to not generate any code, but asks it to explain the problem and the solution, as shown below.

> The bug is still there. Why does it not use states to to track the start @@ and end @@? If you encounter @@ , you can do an if else on the line by asking if the line ends with @@. If so, you can change the state to expect replacement start delimiter. If it does not end with @@ you can set the state to expect line to end with @@ and not start with @@. Do you understand? Do not generate any code yet.

How I see things evolving over time is, senior developers will start to code less and less and the role for junior developers will not only be to code but to review conversations. As we add new features and fix bugs, we will start to link to conversations that Junior developers can learn from. The Dooms day scenario is obviously, with enough conversations, we may reach the point where AI can solve most problems one shot.

Full Disclosure: This is my tool

> For this to work, senior developers will need to come to terms that their value is not in writing code, but solving problems.

This is the key reason behind authoring https://ghuntley.com/ngmi - developers that come to terms with the new norm will flourish yet the developers who don't will struggle in corporate...

Seems more likely that Orange would just be producing 16x the mediocre C-tier work they were doing before. This scenario assumes that the problem from the lower-tier programmers is their volume of work, but if you aren't able to properly understand the problems or solutions in the first place, LLMs are not going to fix it for you.

Chances are Grape and Apple will eventually adopt LLMs because they need to in order to fix the mistakes Orange is now producing at scale.

Nice write up. I don't necessary think it is "if you adopt it, you will flourish" as much as, if you have this type of "personality you will easily become 10x, if you have this type of personality you will become 2x and if you have this type, you will become .5x".

I'm obviously biased, but I believe developers with a technical entrepreneur mindset, will see the most benefit. This paradigm shift requires the ability to properly articulate your thoughts and be able to create problem statements for every action. And honestly, not everybody can do this.

Obviously, a lot depends on the problems being solved and how well trained the LLM is in that person's domain. I had Claude and a bunch of other models write my GitSense Chat Bridge code which makes it possible to bring Git's history into my chat app and it is slow as hell. It works most of the time, but it was obvious that the design pattern was based on simple CRUD apps. And this is where LLMs will literally slow you down and I know this because I already solved this problem. The LLM generated chat bridge code will be free and open sourced but I will charge for my optimized indexing engine.

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