Ask HN: Will I get left behind if I don't jump on AI train?

Against the grain here: Yes, you will.

You should try to understand what it is useful for and what it isn't. You don't need to vibe code at all; in fact, it's the exact opposite. You should read the code and be able to figure out what LLMs are bad at and how they make inhuman mistakes.

I personally like the prompt completion of functions. The act of manually writing out in detail what needs to happen and how help me think about what I want to have done.

Anyway, the main argument I have that you should be using it is that the first and experience of using it will teach you about what to look for in broken LLM code and also help you guide others into producing less broken LLM code.

No.

Read real books. Talk to real people. Do real things.

You can catch up when everyone else actually gets somewhere, and have spent the whole meanwhile on self exploration.

I think there is something happening here and whats needed is your own independent opinions of the technology. I think a lot of people dont like the idiots hyping the tech up and the incessant nonsense. Thats what turns them away from AI. But its a very useful bit of technology and your relationship to it should be direct with no middlemen.

So if you want to work and adopt AI, make your own workflows. Interact directly with ChatGPT or even the API as opposed to learning cursor shortcuts or Lovable prompts.

I use AI very frequently and I love to spell out my thinking and even have AI critique it. Once done, I generate code in phases to save typing. I dont think anything will replace software engineers but engineers with more knowledge will replace those with less. You have to snatch that knowledge. Moronic VCs and tool vendors wont help, direct involvement will.

You don't _NEED_ to know it, but it's probably good for your career to have some exposure in 2025 to LLMs.

Download ollama and mess with a model locally, implement your own RAG system so you get a feel for what that entails and what good and bad use cases look like. I use LLMs every day for random stuff, but not really because I need the output, more because I need to know and understand where it's strengths and weaknesses are.

You're not trying to become an overnight expert here. Nobody expects that. But there's this gap right now between what stakeholders think AI can do (basically everything) and what it actually can do. And guess who needs to bridge that gap?

As a software engineer part of your responsibility is to advise non-software engineers on what is just now possible with technology, because when a stakeholder comes to you with some wacky idea, you need to be able to judge it and decide on the investment of time the idea might require, or if it's even possible today/now.

Not knowing your profession, although we know you are not a developer, but you could be an AI professor, it is hard to answer the second part of your question.

For the first part, consider this the Smart Phone of this age. You will need to know and understand how to prompt the AI. You will need to be comfortable with it. If not expect to be asking your children to help you do it as they will grow up with it and be very familiar.

If you’re not a developer you might as well use AI to become one?

Back in my day we used learn x in y minutes to get up to speed on a new language and then a week to get comfortable.

Now I can do that for anything in like 15 minutes.

Of course, coding is the easy part and anyone can do it.

Software engineering (key word: engineering) is the hard part and requires that you understand the computer, design patterns, and how to build robust systems.

IMVHO it's worthwhile to invest some time playing with the new technologies, as you may appreciate them and found them useful. Give a try to Claude code, Gemini-cli, copilot in vs code with agent mode, or in GitHub.

But I don't think you need to stress, there is a lot of hype and there will be time to learn how to use the winners later.

No, you don't need to try to keep up with new tools. I would recommend you try the models though, even for a short time every few months. Send them questions or things you're working on, and see how they do. Provide sufficient context.

It's a good approximation to say that all tools are thin wrappers on top of the models, and having a good grasp of what the models can/can't do right now gets you 80% of the way there.

When companies are changing their names to include buzzwords, it’s hype. This happened during the dotcom bubble, with crypto, and now AI.

Whatever your job is will dictate if, or how much, you may care. How things shake out at the end of the day will likely look much different than they do right now.

If you’re not someone who likes to try and ride hype waves with various get rich quick schemes, and not in the space, I wouldn’t worry about it. Sit back with your popcorn and watch these people fight for a few years and let the bubble pop. Then we’ll see who is left and what it’s actually good for. You can then adjust from there if needed.

Yes, you should.

As you're not a developer, but haven't told us your field, here are some general reasons why.

My non-devwloper friends (we're in our 40s) are using it to improve their productivity. They have already realized that the AI is bad at some tasks but great at others. For example, a person in PR now no longer writes the 'day to day' PR releases. It's a complete waste of their time, they're really just a formality anyway, and an AI can do it. But they still do all the important ones.

It can release you from routine tasks, or make them trivial.

I've also heard of someone who's using it to find jobs to tender for that they previously didn't have time to figure out. Filter + summarize. So tasks and opportunities that were too time consuming are now viable.

People are making their own mini apps for personal use that are specific for their field.

You don't necessarily have to have the ideas, but you do need to talk to people in your field and find out what they're doing.

MCP/Agents/etc. are pretty cutting edge, but you will start hearing non-techies using them soon.

Agents/MCP means the LLM can do things. You can ask it to make a plan of action, and then DO the actions. It's still a bit ropey.

But soon you might be able to ask your AI to go into HubSpot, find 10 leads that look like they've gone stale and send them a special offer. (It's not quite there yet, and a bit unreliable on something as high level as that, code is less fuzzy and so it performs better).

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