“AI Skills” are worthless in 2026

yako21000

On what basis are you telling this? I think, it's more "outdated" skills that are worthless, but the interval of time we have to refresh those is getting ridiculously fast....

zahlman

> But a skill that can be picked up in a few weeks, and will be obsolete in a few months, has no value outside the moment. This does not describe the general skill of effective communication , which is a prerequisite to writing a prompt that actually describes what you have in mind. Nor does it describe the general skill of, well, having something coherent and sensible in mind. If anything, we are getting worse at acquiring these skills, thanks to an overreliance on AI. Everything turns to slop, if we let it.

no-name-here

> a skill that can be picked up in a few weeks, and will be obsolete in a few months What skills are being referred to? What's an example of such a skill that "can be picked up in a few weeks"? The only "AI" example they seem to give is: > in five years, I’m sure there will be old heads doggedly adding 'you are an experienced software developer, make no mistakes' 1. I don't think "make no mistakes" was ever considered a real AI skill - it was popularized as meme to mock those who did not know much about AI? 2. In years things may change, but Googling seems to indicate that mentioning a role in a prompt can be helpful as it quickly sets the stage for the AI to understand the persona/purpose/context/scope/desired response format for the rest of the prompt. On the other hand, I read that Anthropic found personas didn't boost result quality. But I'm still not sure it fits the article's core claim of "a skill that can be picked up in a few weeks, and will be obsolete in a few months". (Separately, even if not beneficial, that's also still not the same as "harmful" especially considering the few tokens it uses.) On the other hand, Anthropic and OAI both still have live docs using the "You are a __" format: https://platform.claude.com/docs/en/build-with-claude/prompt... https://developers.openai.com/api/docs/guides/prompt-enginee... Anthropic and OAI both have prompt guidance, including even version-specific guidance. I guess that might closest fit the article's definition, but personally I haven't heard about anyone taking "weeks" to learn it as a "skill", or at the very least I think most people know (since it's version specific) that it's not long-term. Personally I frequently use different open models so it makes less sense for me, but I do sometimes ask LLMs for prompt feedback, especially for items I reuse frequently over months or more. The criticism of the "prompt engineer" craze years ago would be valid, but I don't think criticizing that is relevant in 2026. https://platform.claude.com/docs/en/build-with-claude/prompt... https://developers.openai.com/api/docs/guides/latest-model

geokos

"Getting it right is more valuable than getting in first" is what I will agree with. I feel what the author is trying to say. The AI field is moving too fast. One day it is prompt engineering. Then it's RAG, MCPs, Loop engineering, and now harness engineering. But rather than fearing that these are becoming obsolete, I feel there is an opportunity to participate by hopping on and sprinting ahead.

__rito__

Every skill that any literate person can get in a few weeks is worthless. Always was the case.

pu_pe

This is not my experience at all. I see more people having difficulties in extracting value out of AI than the other way around. When I check what they're doing, they paint themselves in all kinds of weird corners, like keeping a mega-session full of unrelated questions, letting the AI model lead instead of managing it, misunderstanding the scope of what to ask for, etc. Of course all the crap about prompt engineering or whatever is meaningless, and it always was. That said, this idea that if AI gets good enough you will just jump in and use it is flawed. You learn by doing. It's almost self-evident to me that someone who has been working with AI models for the past 4 years will be much better at it than someone who started this week.

Leynos

"AI skills" are the same skills we always needed: - Learning in a self-directed way that aligns with the needs of your role and where it is going - Clear communication, the ability to edit and know how to say what is important - Forming and testing hypotheses - Evaluating and testing tools and work product, and being able to recognize and rectify deviations - Delegating, setting constraints, rubrics and escalation criteria - Having a clear definition of done and being able to stick with it - Understanding business domains and modelling them usefully - Collaborating with others, communicating your needs and capabilities clearly, eliciting the needs and capabilities of others, synthesizing conflicting needs and aligning compounding capabilities The adoption of genAI and agentic tooling really just serves to make all of these more important.

joshstrange

While I understand where this author is coming from. and agree that we’ve had a number of false starts or silly concepts like “prompt engineer”, there is definitely a skill in using LLMs, and it is a spectrum for different people. Being completely engrossed in the new trends is probably not necessary, but keeping abreast of what’s possible and trying new things is. People who have an ignored/avoided LLMs completely are not able to just pick them up today and be as productive as people who have been learning the best ways to use them over the last couple years. Many of the “skills” are not new, it’s the same skills you’ve been using throughout your career, just with a new tool. But any new tool requires practice and learning what it’s capable of. I’m constantly experimenting around the edges of what LLMs are good at because it keeps changing and just because an LLM wasn’t good at X task 6 months ago doesn’t mean it still isn’t good at it today. The only way you can know is by testing and trying out things. I work with a number of smart people, but their LLM proficiency is a wide spectrum. LLMs might/are a leveling factor, but there is still skill in getting what you want out of an LLM. This is most apparent to me when I interact with people who aren’t developers or aren’t as technically savvy. They just aren’t able to produce or get the same things out of an LLM that a developer or more technical person can.

thewhitetulip

AI skills is more of a writing skill. People, for the most part, don't know how to write well

Marol

I think the real "AI skill" that has to be learned, is to NOT get comfortable with your workflow. I have already changed it plenty of times and each time it required a complete overhaul but gave a huge improvement. Like you mentioned, people tend to stay with what they have first learned, but it's suboptimal. So I think the true AI skill will be to let go of everything you have learned and just embrace the stochastic brain and constantly adapt. I haven't been bothered to setup my IDE since may and my friends from uni are prompting claude to use svelte instead of react.

nitroedge

I'd say the majority of people don't know what a Reverse Prompt is, and its literally one of the most valuable things I have yet to see really go mainstream. Instead of forcing your ideas or brainstormed concepts onto the AI and make it pick, you ask reverse questions which won't include any of your bias such as starting out with: "If I were to build the best homelab for a coder, what key things should I be aware of and do?" or "What are some key questions to ask you if I want to best solve this problem <then state problem>"