gokuljs

Why is this not trending on Twitter

They don't give a fuck about you. They have bigger customers to worry about. You are just paying them to improve their training dataset so that you can get kicked out of your own job :).

the end is here

That doesn't mean that you have to send shitty emails to founders right

Such interesting comments. I’d never find this kind of discussion on Twitter. It makes me think

Question: Why do you think it is a hype cycle?

Those will never go away, but they’re still not the best moats. There isn’t much defensibility in them.

Who are you calling troll here?. Tell me where I am wrong if you can't answer that, keep quiet

Right now, I’ll be very honest: it feels like a race to the bottom, except for the hardcore engineers working on genuinely difficult problems.

Only a small number of people will get the chance to work at that level as the field changes. I think there will be a radical shift from here.

Altman and Dario know this well. That is probably why the tone has changed from “engineering will disappear” to “engineering will change.” But I think we have already reached the inflection point where a large part of the work is getting automated.

Craftsmanship has already started moving somewhere else. Where exactly it moves depends on the kind of work, and I do not think everyone will figure out what the new end goal is.

I can see infra teams directly integrating agents into DevOps now. If something goes down, by the time the team looks at it, the PR with the fix can already be ready. That whole loop is getting automated too.

ya true

When a deeper question is asked, you dont have a proper answer

Prove me wrong. I’d be happy if you do. The only engineers I’ve seen who are extremely good tend to have 15 to 20 years of experience. The difference they bring is not really in the code. It’s in how aggressively they cut unnecessary complexity and how much more effective they are at system design.

Tell me about this critical system you're talking about. I want to know.

necessary not good enough

Prompt engineering is more than enough to build this. Not a hard problem

Hard disagree on the “useless professional” part. I can still write code without ChatGPT or Codex. That’s not even an issue. Becoming proficient used to take years if you did it the right way; with AI, you can get into pretty good shape much faster.

But define “proficient” here. What does that really mean in this context? A junior engineer, sure, you can tell they’re fucked for now, but for how long does that matter if the models keep getting better?

I feel that for a senior engineer, it’s already there. If you have enough scars, you’ll figure it out, get it done, and fix whatever breaks.

Tell me at least one interesting problem that you have encountered. That is related to coding and software engineering

On point 1, it depends, and I think it is a UX issue. There might be a little bit of friction in nailing things down, but the coding part is 100% solved.

On point 2, yes, again, there is a bit of friction. I would divide this into two cases based on what I have seen. Let’s say you don’t know coding and you are building a product for a decent number of users. Most people who don’t know coding get things wrong. I have seen that. But I have also observed that if they had asked better questions, much better questions, they would have gotten most things right.

The other case is when you are dealing with a large enterprise. That is a different game altogether, but not everyone faces that kind of problem.

Point 3 is completely solved. Most companies have integrated agents into the development cycle itself. If something goes wrong, you review it and merge it. The only bottleneck is when it is connected to external factors.

Point 4: an environment with proper `SKILLS.md` and `AGENTS.md` files writes better code than most senior engineers . Trust me, I am not even lying here.

It is dude, I am not joking here.

Yeah, even three months is already too late. Back at 4.8, it was already a solved problem.

If you can do system design well, prompt effectively, and ask the right questions, I don’t see much point in going extremely deep into all of this anymore. I’ve learned a lot of new things, but now it often feels like I can just prompt the model and get the implementation in one shot.

For problems with a closed feedback loop, I don’t think you need to spend nearly as much time learning every implementation detail. A person who never invested that time can often produce the same result with the right tools. That’s the part I’m struggling with.

Finally, I have reached 2026

A company can have money but can lose taste. look at IBM and microsoft

See, Google has just entered its IBM era.

Just take a tough project, an ambitious one. Then do system design first. Use AI and you, and figure out failure modes, all that where it can fail. Then start building piece by piece and start reading that code and publish thats it

AI SLOP

If your startup goes successful. Anthropic will copy your model and make it there’s. They are distilling each and every knowledge