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this post was submitted on 17 Jul 2026
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Fuck AI
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A place for all those who loathe AI to discuss things, post articles, and ridicule the AI hype. Proud supporter of working people. And proud booer of SXSW 2024.
AI, in this case, refers to LLMs, GPT technology, and anything listed as "AI" meant to increase market valuations.
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The fact that you have to "prompt-engineer" means that the tool has a terrible interface.
In your flaslight analogy, there's an on/off button that doesn't work. You have to flip the flashlight, tap it twice, check the batteries and flip it twice again. Then it turns on.
The fact that LLM coding tools are basically micro-managing with a special twist "knowing how to prompt", makes it a shit tool for a lot of people. And they are justified in thinking so.
You can't hone a skill you have little control over. It's like a hammer that strikes a random area within a certain radius of a nail.
I both agree and disagree.
As for having little control, I feel like that happens in other disciplines too. The best archers need to account for the stochastic nature of wind patterns, and thus they do not always hit their intended target. But still, their accuracy is far greater than a novice. There is both skill and "luck" - if you will - involved in the process. You definitely can hone a skill you have little control over in the beginning, I believe. Maybe this is the analogy that should’ve been made.
I will say, "knowing how to prompt" feels like a weird skill, and I think the way we interface with these tools is kinda wacky. Regular text feels to fuzzy.
But it does help immensely, I find, to take every wrong agentic coding output as a learning experience. When I know the answer, and the agent failed, I ask myself why it didn’t fint it. Taking these opportunities has led me to be more proficient in the use of skill files, agent files, subagents, context window management, etc., all which have improved the agents output massively. I feel like a year ago, it was just prompting and copy-pasting (at least for me), but now, with tools like OpenCode, I can get a better looping effect with fewer errors.
I am curious about your findings
Don't forget we are talking about a tool.
A good tool is easily documentable, and then usable with said documentation. A good tool has perfect repeatability It is easy to predict the outcome of using a good tool.
Current LLMs have neither. For all the user knows, it's a black box that takes input and poops out output. You can only steer the output after some output has already been given.
I think we disagree on the nature of a tool. Or maybe I am thinking about more than a "tool", but not using the appropriate word for it.
Image riding a very fast horse. There is no perfect repeatability, it might veer off, or react to something you didn’t see, but a good rider would probably manage to arrive at the intended destination. I think I view it the same with agentic coding.
Now, I agree a horse is not a tool, and that’s why I mentioned that my language is perhaps a bit imprecise. (I guess you could even call it an agent.) But maybe an "instrument" or an "implement" fits, although that’s a bit cold wording for a horse in general, as they have other qualities, as being cute etc.. But I think you get my point.
I very much think LLMs can fall under the description of "useful implement for coding" today. But I do think it is a very poor knowledge retrieval implement. In fact I sucks for all these one-off questions, I my opinion.
I think the more interesting discussion is about how these AI companies consolidate power even more, how they steal data, how they pollute like crazy. But I think people who dismiss their use in coding perhaps view LLMs more like a flashlight and less like a very fast horse moving you from A to B.
Context engineering is a skill analogous to communicating a problem to fellow maintainers. This typically involves articulating the issue within an issue tracker, pull request, or comment using written text. Therefore, proficiency in "prompt engineering" is essentially a measure of one's articulacy.
So it's not a "useful tool for coding" then, if the quality of the output depends of one's ability to articulate in a way that tickles the LLM "the right way".
Also, no matter how well you articulate, the output is still somewhat random. You can produce two different sections of code with (essentially) the same prompt, which also just means that theres an amount of luck and percieved randomness in a tool.
Imagine you want a piece of software written but you're hiring it out, like a lot of corporations do. You write up a loose specification and hand it to two different dev shops and you'll get two wildly different results. The tighter the spec, the closer the results will be.
It's not much different from that.
Indeed. I agree that it's not a tool, but a type of outsourcing.
Following my analogy with the archer, promting the right way is like accounting for wind. And again, no matter how much the best archers in the world account for wind, they do sometimes miss. Still very impressive how high their skill is, even with randomness involved. And with agentic coding, one can always shoot twice.