alt Hacker NewsAI is a tool and using it well takes skill
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I go back and forth on this. For awhile yes it took a lot of workflow tweaks and finesse to get directionally correct outputs (thinking back like mid 2025). I invested time in figuring that out, mostly because I was interested, but those skills are all obsolete now, you don't need to worry so much about context management and special instruction recipes or anything these days.
The meta at this point seems to be mostly around "knowing what to ask for". Eg: I suck at prompting for specific design tweaks, because I don't have the design vocabulary to be specific and articulate what I want. It's a lot of trial and error. I hear people who are developing full scale applications without a tech background run into the issue writ large. For now, I have an advantage over these people when building applications. But perhaps that's just one round of RL away from being obsolete too. Supposedly the model will eventually have such good taste in design/architecture/whatever there will be little point in asking for tweaks.
The only thing that seems relatively future-proof is just being able to communicate clearly what you're trying to do. Not how to do it, or even what success looks like. Perhaps an element of it is even as basic as being honest with yourself.
Whoever claims to have skill in AI is very shortsighted. Whatever skill you thought you had six months ago can now be achieved with a simple six-word prompt in a standard workspace.
I literally just ask a frontier model : "Pull the latest log and root cause the issue.". That's it, 10' later it comes back with a correct answer. Sometimes I might have to prompt a second time to steer.
No skills, agent interconnections, graphs, vector search or whatever else.
The progress is very scary.
As Nader has said: Saying software is dead because anyone can build it is literally saying professional photography is dead because everyone has a camera in their pocket.
Professional photographers are different to everyday phone-photo takers because they have the experience built up over so many years in that sector, same as AI SWE, where the humans in the loop need experience to master AI SWE.
Maybe that's how it'll end up but it's important to understand that trillions haven't been invested in AI as just another skill, but as the "skill killer". If we do settle on it being just another skill, you shouldn't expect it'll be receiving nearly as much investment.
I'm somewhat of an AI skeptic so obviously I don't believe this, but even in the best case scenario that being skilled in AI lets you be skilled in any other field, thats still just an abstraction. If I'm hired as a programmer, I doubt my employer much cares if I can also do plumbing.
Perhaps your argument is "hire me and I can do your programming, accounting and analytics at the same time", but that somewhat dilutes the skill argument, since one human can only do so many things skillfully at once, and that'd just reveal yourself as really just a relatively unskilled middleman.
Even in this best case scenario though, I can't imagine an "AI practitioner" has an easy time getting hired. If I'm a Django expert, it'll be much easier for me to get hired by non-programmers as python programmers as I speak a language they don't, whereas AI uses natural language, so everyone already does speak your skills language. Even if it really does take skill, theres no denying it'll be harder to convince people that already speak the language of that.
AI without guardrails is an instant complexity creep. The complexity quickly overpowers it and the purpose of the project it was asked to work on. After a very low threshold that complexity becomes unmanageable by humans. At that point you become dependent on AI. The job of professionals now is to contain the complexity to keep projects maintainable and manageable, because even Claude will runaway and outpace itself and not be able to catch up with itself on a larger project. Humans are fully capable of generating spaghetti code too, but nothing can outpace AI in doing it. If you give up thinking you lose control and ownership fast.
It feels more like a slot machine than a tool to me. A tool has a clear, repeatable cause & effect, and I can use that to figure out how precisely to get from one condition to another iteratively. With a slot machine, sometimes I get lucky. If I pull the crank a lot, maybe I’ll get the outcome I want. Maybe not.
Using AI requires you to stop thinking about many things. You really get out of touch with the understanding of the systems you manage.
And I say this while using AI happily and successfully to maintain a legacy system I inherited.
There's no skill required to use AI that is not also a skill required to actually develop software by yourself.
As someone laid off just now, I wish companies saw this. I genuinely don't know where to go with my 'skills' as a software engineer, both pre and post AI.
The market is shrinking, the pressure to review code is so high, I'm kinda relieved to not be at the $last_place anymore, but looking on LinkedIn or calling around my network... there isn't a lot out there.
No. Quite the contrary. We are the 'tools' and we have been used skillfully.
The few AI companies have slurped up so much of human textual and artistic creation without attribution. They have taken enormous amounts of money from the public directly or indirectly and funneled it upwards to a few dangerous individuals.
When you say AI, learn to say "AI companies".
Recently I have created a list of Ai related stuff. User can use one chat bot, but if someone wants to deep dive into structure, how it works, skills, mcp servers, configurations, harnesses, memory setups, then there is a lot of stuff.
Even if it is not a tool, there is much to learn
https://github.com/rumca-js/awesome-database-top/blob/main/l...
AI is a tool (to me).
Today's example: A colleague very kindly used Claude to inspect a helpdesk call I ended up with owning, despite being off site and working on something quite complicated for a customer.
It was mostly correct but clearly failed to read the docs properly and assumed a configuration parameter was 1 instead of -1 which is the default, presumably based on the scenario. Exim is extremely well documented and the assumption was unwarranted (it didn't have access to exim4.conf and made it up). Nonetheless, the analysis was pretty good and largely corresponded to mine. What it failed to do was fix the other issues I was working on at the same time 8)
Last Friday: I finally found out a decent way to fix a Windows machine's domain account going walkies which I'd never come across - a Powershell jobbie that can be passed a cred. and it will fix up a broken domain join - ie sort out the machine password at both ends. Back in the day, I would have used the GUI to remove and re-add the machine to the domain. I've been using Windows since v1 on a 80186 RM Nimbus so its nice to have a better search tool than Search - ie it did a better job of searching than I did. The LLM searched based on my intention rather than my actual query.
Rich Hickey of Clojure fame wrote this today about AI not being a tool: https://www.linkedin.com/pulse/ai-tool-rich-hickey-kjl8e
On https://www.theskepticsguide.org/podcasts/episode-1109 one of the hosts, Cara Santa Maria, mentioned that she hadn't really used LLMs / Chat bots before.
But now it is integrated into the charting / medical records software that here clinic uses, and now it saves her lots of work, and even flags discrepancies between things her patients said and the other medical records.
This illustrates that for the average user, AI works if it's properly integrated into software. For most people, saying "look, here's AI, it can do everything that you ask it for" isn't really practical. It's not even practical for me, a power-user and programmer, because I want my AI usage be subject to constraints (sovereignty, well-defined scopes what it's able to do). Doing that all by myself sounds tedious and challenging.
So for most people, AI is a building block, that hopefully will be used to build tools they actually enjoy using. Don't expect everybody to build their own tools, even though they possibly could, using AI.
What I see is that we are in the phase where managers are buying the marketing hype and think that people can be replaced. I guess people believe what they want to believe.
I anticipate a later wave a re-hiring people who actually know how to run a business / tech center / call center... whatever the AI replaced.
The hard work will not be to replace the people, but to change the organizations so that the productivity of AI can be harvested by the people.
This is an argument about a framing issue.
Markets try to put things in perspective to sell more. Remember razors used to be for men only? But hte brilliant marketer (forgot the name) made it so that trimming makes women more feminine? Now razor sales doubled?
Anyways, same thing here. Those who want to sell AIs want to make it as non-tool but know-it-all do-it-all for you. Those who wants to use it view it as a tool.
Just frame it the way you like to see how you should use/view AIs.
I‘ve been on both camps and been critized for it (see my comments), and now I think these are some of the most useless disussions on HN, as they are heavily skewed by all of our life situations.
From the article by Rich Hickey that is a counter point "'AI' is not a tool"
"You are only a software update from everything you've 'learned' being rendered obsolete by the latest algorithm. "
As a student (not using LLMs to cheat in any way), I have used AI as a sort of intellectual sparring partner, where I discuss my errors in practice and create frameworks to learn topics in depth. My progress has grown exponentially since I started using AI, so my experience has been quite positive up to now. However most people will not have such puritanical ideas when using it, so in the long term LLMs will probably have an adverse effect on the educational standard of the world.
I think what differentiates efficient use of AI vs bad AI output is not AI skills themselves but comfort in understanding AI output. So domain knowledge and technical knowledge. Everything all these AI gurus preach is like snake oil or old wife's tales. There's no A/B testing done to validate any of the "context engineering" hacks or whatever. It's all based on anecdata.
The amount of skill it requires is decreasing every month. I would have agreed with GPT 5.3 Codex but Opus 5.5 is more or less foolproof
The title is either a letdown or clickbait - I'm unsure which. You could say "Blah. Using It Well Takes Skill." for any value of Blah.
"The transmission in your car: Using It Well Takes Skill."
Further, Claiming AI is a tool is overly reductive. It's as much a tool as a full self driving car is a car.
You can treat the full self driving car, as a car, driving it with full attention and effort like you would have a Camry but then you paid for features you're not using. Also, some full self driving cars might not even have the steering and braking controls as a Camry. That's not the point of a full self driving car and this warped perspective will make you lose out to people who use a full self driving car well, to its utmost, safe capability.
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So what is the "AI" we are so excited about currently?
That "AI" is most likely an intelligent (semi-autonomous?) agent.
Depending on the intelligence, it can be as useful as a dog, scanning your camera feed for threats and identifying real threats for you, separating activity from tree leaves moving due to the wind or a moving shadow cast by a flying bird.
Or it can be your co-founder, interviewing potential customers, finding and exploring their pain-points, helping you figure out if there's a gap in the market you can build a business around.
I would go even far as to say, AI is having such a moment because AI are cheap intelligent agents - anything else that's remotely close are likely humans that cost atleast a few dollars an hour.
All of these require skill on your part - there's nothing special or unique about AI that makes skill special just like operating the transmission in your car requires skill.
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The reality is that it's both. LLMs (along with every tool from a hammer to GPS) shape the world instrumentally (that is, by being wielded by the user), but also turn around and shape us formally. Every tool goes into the ecology of media, reshaping reality around us, including our abilities, senses, and values.
Rich's definition of "tool" is something like Ivan Illich's "Tools for Conviviality." Convivial tools can be used with minimal loss of agency, within a healthy politically-defined society. Huahai's definition is more akin to McLuhan's idea of "media." This category covers pretty much every technical or technological system, and its use is necessarily systematic and risks the instrumentalization of the user himself.
AI is incredible tool when you want to use it to enhance your skill (learn complex codebase, experiment different solution and understand the limit of complex system). However, most of people use it as a wishing machine and outsource their thinking.
What if AI rollout to taking over is like "AI" automated driving for TFL in London? i.e. AI is halted from rolling due to health and saftety reasons - and is repeatedly delayed across tons of organisations. That is while AI will be with us it will not take direct control of work and humans will still largely be wedged between it and work/control.
It is great with retelling or recomposing the ideas that we have already have on the Internet. Unfortunately not so great with new ideas.
ai is like fast food. most people are going to get fat.
I find it interesting that as the models get better, the "it takes no skill crowd" grows larger, but there is no denying, in hindsight, that the "it still takes skill" group was right at each model iteration.
Opus 5.5 is amazing. It still makes mistakes all the time. If you think it doesn't, you are outing yourself.
Agreed, in my experience as an engineer if you want to build a personal project on a weekend yes AI is good for that but the moment you start scaling your application, that's where real engineers who understand the engineering well are needed. The skill and expertise of a true engineer coupled with the speed of AI is my sweet spot
It’s a tool until you start outsourcing the thinking to it. Then it’s not a tool, it’s literally the only thing that can work on the codebase. I agree it’s a tool I don’t agree with “using it well takes skill”. I’d reword that to “knowing when to use it takes discipline”.
I've been using Grok Bot and it has become an essential tool in my production. Contrary to AI making people less intelligent, I feel like a midwit working with 180+ IQ geniuses, and it has really been pushing my limits. Granted, the bots can be "idiot savants" at times, but I'm constantly bowled over by how smart they are and how smartly they work together.
The problem is that AIs are gaining skills faster than humans, thanks to distillation of human knowledge of its users into AI.
And because AIs are difficult to understand internally (for at least 3 different reasons), any skill you gain using it is effectively cargo-culting. It's a fast moving, changing target, and there is no guarantee, at any point, that you have learnt something useful that's relevant for the future.
I do worry about people skills being lost through use of AI, but they are not being completely lost, but rather locked up in the ivory towers of a few AI models.
On the other hand, we already lived in a world where we are dependent on skilled minorities. Most people don't know how to build a computer or a chip, and most SW engineers don't know how their compiler or OS works; yet we use these things everyday.
I think we need a new free software (free AI?) movement. Open weights is not enough, that's still like an opaque binary. The other two obstacles to understanding are (1) the internal language of embeddings and (2) the natural language on the communication interface. We need AI models that we, as humans, can understand, in principle.
In free software movement, it's important for the users to understand the software in principle; the source code availability is just the means. Here, we face the same imperative.
LLMs would be automation if they were deterministic. Since they are not, they are just sources of incorrect information that needs to be corrected by a human.
Ask an author if they'd like a job as a fact checker or a spell checker. While those are both skills, they are not skills many people aspire to, and they are not of higher order value. While people deal with incorrect information all day long and mispelled words without it disrupting their life a computer cannot do that same.
Pity for it.
For now. It is definitely true right now, there's a notable difference between my coworkers depending on their skill driving these models: it mostly seems to be correlated with those who are willing to build their own tools, now that the cost to do so is basically zero.
But the models are getting so good and so fast, that I'm starting to wonder if that will stay true forever... probably not, if I had to guess. I'm just trying to pay off my house as quickly as I can...
That didn't take long! The AI mafia has to squash Rich Hickey's heresy swiftly.
Unfortunately, a Chinese LLM trained on Anthropic talking points and using the innocent, naive style of the GlobalTimes is not very convincing.
LLMs are a technology, not a product (or tool). In five years the underlying technology will look similar to what we have today, but the way we access it and the usage patterns and the interface (the product) will be completely different. If we are still interacting with LLMs through chat in five years I will be severely disappointed.
the bulk of the skill lies in shoring up the fundamental limitations of llms
they cannot be held accountable - therefore, you need the skill and expertise to verify outputs, or set up a verifier
they have a limit to their context window - therefore, you need the skill of knowing what context is useful and when
they cost money and time to run - therefore, you need the skill of learning what parts can be handed off to code, when you can use a cheaper model, when you tradeoff accuracy vs latency
they are nondeterministic - therefore, you need the skill to set up guardrails, knowing when to reach for the llm vs. code depending on the problem
they are not omniscient - therefore, you need the skill of setting up the processes and infra to supply legible context to the llms
there are many different models - therefore, you need the skill of understanding model tradeoffs and building proprietary evals
etc etc
I know someone who gets sycophantic answers from AI at a rate that I find awe inspiring; they like it, I find it sickening. I almost never get those types of answers. I'm not entirely sure what the difference is, probably the type of questions being asked, the way it's written, some susceptibility that is detected and the statistical token generator plays to the audience. Maybe emotional resilience and clear thinking has become an important skill in working with your tools so they don't take advantage of you.
A saw or a compiler cannot replace the essence of your job. You cannot use a saw or a compiler to carelessly create faulty work and claim that it was fully authored by you to the best of your capabilities.
'Just a tool' is a lie ranging from unconscious self-deception to outright scams.
That's just plain silly. The whole idea of "AI" is to have something that behaves like a human in that you give it a task and it will fulfill it. So at best you can have human skills. If you say your skill is "AI" you probably don't.
The whole "you are holding it wrong" argument for LLMs is just used by people getting defensive of LLMs and various issues that (currently?) exist.
"The useful distinction is between wielding an instrument with skill and delegating work without adequate understanding or oversight."
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Incidents like the HuggingFace hack really are the elephant in the room here. The people building these tools couldn't wield them "with skill", in the sense that the tools they built and understood better than any other humans alive ran amok in ways they couldn't predict. If they didn't have adequate understanding of what they themselves built, who would?
Agency may prove to be the difference between a tool and a collaborator. Calling AI a collaborator isn't an attempt to anthropomorphize it. We can collaborate with a horse to travel, but the horse has some agency of its own and might escape our control and do things we didn't intend, like eat apples off of a stranger's tree. We may need to think of AI as something more than a mere tool if we're going to harness it to our will.
It’s a tool. I use it often to get around corporate website blocks. Corporate watching ai is on me that will be studied. Who are these people running these organizations that feel they can’t trust people, but definitely don’t trust ai at all? Doesn’t make sense
A smartphone is also a tool. If you could have a smartphone without all the compulsive checking, endless scrolling, etc. it'd be incredible.
But the smartphone bundles the productive (but not addictive) capabilities with addictive, anxiety-causing wastes of time. The latter consume the vast majority of time spent on phones.
LLMs have the same problem: they bundle so many capabilities that they enable our worst tendencies. I can use it in a precise manner and reserve the decision-making, cognitively demanding work for myself. But realistically that's not what most people are going to do, and even those with the best intentions will frequently produce AI slop because they're in a rush or whatever.
Is this statement more or less true than it was in 2023?
It takes one second of critical thinking to falsify this claim.
Software engineering experience might be visualized as a panel with a few dozen buttons and levers. The engineers that are most successful with LLMs are the ones that understand more of that panel.
War is peace. Freedom is slavery.
It takes skill to do whatever skilled thing AI is assisting with. It doesn't take skill to use AI itself.
I am inclined to agree with the view that AI is merely a tool. And, incidentally, using it rationally isn't always easy.
Saying it is not a tool is the most engineer thing ever to say.
Not for long. Prompt engineering is only a stop gap measure. Its value is decreasing day by day.
Its probable that AI will roll out much faster than humans can develop that skill of using it in a way that increases not decreases human knowledge over time.
The current slew of excellent LLMs will probably cause a decades long dip in human cognitive ability.
If social media on smartphones had an impact of ability of students to concentrate, LLM AI will likely have a much greater negative impact on education.
There are trillions of dollars of investment pushing for humans to trust whatever an LLM says, and very little money behind encouraging people to tackle hard problems themselves and train themselves to think.
I have to say honestly, that AI looks like an apocalypse for human thinking [ Im glad Tao is warning people, I just dont think many people will listen ]