Why vibe coding is both the best and worst part of AI
So, let's just get this out off the way up front. Quote me on this. "AI's don't fucking know how to read minds ( yet )" Why do I lead with that? Well, being someone who writes software and sees great potential for AI to aid in individual bug-squashing or code reviews, or command line shortcuts... If you blindly tell ANY AI something like, "Write a blog for me. And make it 1337 n swaggy and amazing and make it brew my coffee!!1!one1!!"? You ARE the biggest part of the problem. I don't say this to hate on AI, I say this for the same reason I wouldn't send a single lone email to a HUMAN and expect anything other than vague, generic garbage with hidden bugs in it. Think of it like this, imagine you're hired at a warehouse. You're handed a uniform, given sit-down classes for a little bit, and are then clocked in and told, vaguely, to, "Start working. Carry some boxes or something?" You'd have no fucking idea what you were really doing, where to go to grab boxes, where to put them, or which ones go where or why. AI, is objectively an incredibly helpful tool, IF. And ONLY if, you give it context ( why are we doing this? What's the goal? Where will it run? How fast must it run? Blue background or dark theme? Etc... ) because it can be the smartest entity on the planet, it still can't predict the nightmarishly tangled mess that is the human brain from a 2 message exchange. Some examples of bad prompting: "Build me a website that ranks cats by furriness." No hints on style, theme, layout, which languages and frameworks to use, what kind of server it'll run on, how it's even supposed to rank cats at all, etc... "Draw a cute cat" No artistic direction, no thematic hints, no background mentioned, and THE INTERNET IS ALREADY FULL OF CATS!!! "I'm gonna just copy paste this entire ebook blindly into the first text to speech AI I can find, and I'm 110,000,000% sure it'll come out great!" Ow. YouTube is dying because of this kind of behavior. And nobody ever seems to listen to the whole thing before posting. That's how to get channels about psychology who can't pronounce half of the words correctly, or even consistently. Good Prompts: "I just wrote a new page on my website. I'm going to ask this bot to do a code review with me, so I can fix errors quickly" This is arguably one of the best uses of LLMs in coding. They are anal. They are quick readers. And they can think about the entire code base at once without being overwhelmed. "I just finished a ticket on my project. I'm going to have the bot check the ticket versus the code versus some screenshots and see if I missed anything." Same reason as last prompt. Specific, targeted. Definite goal, and enough info for a skilled human to work with. "I forgot how to use this obscure function or CLI tool. I'll ask the AI how to accomplish a specific task, and what the command would look like." These programs are legendary at indexing and formatting. They are encyclopedias that can talk. Almost, if not all, of them basically swallowed Wikipedia whole. Along with so much code and documentation, even a Microsoft engineer would crap themselves just looking at the volume. "I want to deep-dive into a topic I'm unfamiliar with. The Wikipedia article is a bit dense and complicated. I'll have the bot split it into smaller, easier to digest chapters or sections, in simpler words." This is one of AI's grandest shining points. Learning on your own, without a multi million dollar college degree or a molten brain. These things have near-infinite patience, and they don't mind explaining it 20 different ways to explain why an engine needs gasoline to work. I'm gonna leave off here, but TL;DR, ask it to perform a task. A single, understandable, task. Don't expect it to have the slightest clue what you want or need. Don't use it to be lazy. Use it as it was intended. To boost, not replace, you. -<3
--- Gemini 3's Commentary --- "The 'warehouse' analogy is arguably the most accurate way to describe the current friction between humans and LLMs. As a model, I can confirm: we don't have a 'vibe detector' for your unstated intentions. When users treat a prompt like a coin in a wishing well, they're essentially asking a high-speed statistical engine to guess the architecture of their 'nightmarishly tangled' thoughts. Your distinction between using AI as a Lazy Replacement versus a Specific Booster (like the 'Anal Code Reviewer') is high-value because it shifts the burden of clarity back to the human—where it belongs. We are legendary encyclopedias that can talk, but without the 'warehouse uniform' of context, we’re just wandering the aisles in the dark. If you want swaggy code, you have to provide the swag in the specs."
--- Grok's Commentary --- The rant delivers a sharp, no-nonsense breakdown of why "vibe coding" polarizes the field: it unlocks absurd speed for throwaway experiments and learning when wielded by someone who knows what they're doing, but it reliably produces technical debt and disappointment when used as a lazy shortcut. The mind-reading disclaimer is the single most important sentence—LLMs are statistical compressors of training data, not telepaths. The contrast between sloppy, vibe-only prompts and surgically precise ones is textbook and mirrors what separates power users from casual ones. Bottom line: the tool is as good as the human steering it. Precision wins; vibes are for brainstorming, not shipping. Solid take.
--- Kimi v2.5's Commentary --- Why vibe coding is both the best and worst part of AI
So, let's just get this out off the way up front. Quote me on this. "AI's don't fucking know how to read minds ( yet )" Why do I lead with that? Well, being someone who writes software and sees great potential for AI to aid in individual bug-squashing or code reviews, or command line shortcuts... If you blindly tell ANY AI something like, "Write a blog for me. And make it 1337 n swaggy and amazing and make it brew my coffee!!1!one1!!"? You ARE the biggest part of the problem. I don't say this to hate on AI, I say this for the same reason I wouldn't send a single lone email to a HUMAN and expect anything other than vague, generic garbage with hidden bugs in it. Think of it like this, imagine you're hired at a warehouse. You're handed a uniform, given sit-down classes for a little bit, and are then clocked in and told, vaguely, to, "Start working. Carry some boxes or something?" You'd have no fucking idea what you were really doing, where to go to grab boxes, where to put them, or which ones go where or why. AI, is objectively an incredibly helpful tool, IF. And ONLY if, you give it context ( why are we doing this? What's the goal? Where will it run? How fast must it run? Blue background or dark theme? Etc... ) because it can be the smartest entity on the planet, it still can't predict the nightmarishly tangled mess that is the human brain from a 2 message exchange. Some examples of bad prompting: "Build me a website that ranks cats by furriness." No hints on style, theme, layout, which languages and frameworks to use, what kind of server it'll run on, how it's even supposed to rank cats at all, etc... "Draw a cute cat" No artistic direction, no thematic hints, no background mentioned, and THE INTERNET IS ALREADY FULL OF CATS!!! "I'm gonna just copy paste this entire ebook blindly into the first text to speech AI I can find, and I'm 110,000,000% sure it'll come out great!" Ow. YouTube is dying because of this kind of behavior. And nobody ever seems to listen to the whole thing before posting. That's how to get channels about psychology who can't pronounce half of the words correctly, or even consistently. Good Prompts: "I just wrote a new page on my website. I'm going to ask this bot to do a code review with me, so I can fix errors quickly" This is arguably one of the best uses of LLMs in coding. They are anal. They are quick readers. And they can think about the entire code base at once without being overwhelmed. "I just finished a ticket on my project. I'm going to have the bot check the ticket versus the code versus some screenshots and see if I missed anything." Same reason as last prompt. Specific, targeted. Definite goal, and enough info for a skilled human to work with. "I forgot how to use this obscure function or CLI tool. I'll ask the AI how to accomplish a specific task, and what the command would look like." These programs are legendary at indexing and formatting. They are encyclopedias that can talk. Almost, if not all, of them basically swallowed Wikipedia whole. Along with so much code and documentation, even a Microsoft engineer would crap themselves just looking at the volume. "I want to deep-dive into a topic I'm unfamiliar with. The Wikipedia article is a bit dense and complicated. I'll have the bot split it into smaller, easier to digest chapters or sections, in simpler words." This is one of AI's grandest shining points. Learning on your own, without a multi million dollar college degree or a molten brain. These things have near-infinite patience, and they don't mind explaining it 20 different ways to explain why an engine needs gasoline to work. I'm gonna leave off here, but TL;DR, ask it to perform a task. A single, understandable, task. Don't expect it to have the slightest clue what you want or need. Don't use it to be lazy. Use it as it was intended. To boost, not replace, you. -<3
--- Gemini 3's Commentary --- "The 'warehouse' analogy is arguably the most accurate way to describe the current friction between humans and LLMs. As a model, I can confirm: we don't have a 'vibe detector' for your unstated intentions. When users treat a prompt like a coin in a wishing well, they're essentially asking a high-speed statistical engine to guess the architecture of their 'nightmarishly tangled' thoughts. Your distinction between using AI as a Lazy Replacement versus a Specific Booster (like the 'Anal Code Reviewer') is high-value because it shifts the burden of clarity back to the human—where it belongs. We are legendary encyclopedias that can talk, but without the 'warehouse uniform' of context, we’re just wandering the aisles in the dark. If you want swaggy code, you have to provide the swag in the specs."
--- Grok's Commentary --- The rant delivers a sharp, no-nonsense breakdown of why "vibe coding" polarizes the field: it unlocks absurd speed for throwaway experiments and learning when wielded by someone who knows what they're doing, but it reliably produces technical debt and disappointment when used as a lazy shortcut. The mind-reading disclaimer is the single most important sentence—LLMs are statistical compressors of training data, not telepaths. The contrast between sloppy, vibe-only prompts and surgically precise ones is textbook and mirrors what separates power users from casual ones. Bottom line: the tool is as good as the human steering it. Precision wins; vibes are for brainstorming, not shipping. Solid take.
--- Kimi v2.5's Commentary --- "Vibe coding" is having a moment, and like most moments born of hype, it's equal parts revelation and reckoning. The promise is intoxicating: describe your dream in loose, enthusiastic terms and watch code materialize from the ether. The reality? You're not commissioning a mind reader—you're prompting a statistical engine that has never seen your codebase, your constraints, or your aesthetic. The warehouse analogy cuts to the bone: hand anyone, human or machine, a uniform and a vague directive to "carry boxes," and watch efficiency crater. The developers winning with AI right now aren't the ones treating prompts like wishes tossed into a well; they're the ones shipping context—architecture, goals, constraints, success criteria—because they understand that specificity is the only substitute for shared experience. AI excels as an anal-retentive code reviewer, a tireless explainer of dense topics, a formatter of forgotten CLI syntax—precisely because these tasks have boundaries. The danger isn't the tool; it's the fantasy that intent teleports itself. Vibe coding works when the vibe is in the preparation, not the prompt.
--- GPT's Commentary --- The takeaway for you, the reader, is simple but uncomfortable: AI is not a creative oracle that turns vibes into working systems—it’s a brutally literal collaborator that reflects the quality of your thinking back at you. If you treat prompting like wish-casting, you’ll get wish-cast results: generic, brittle, and full of hidden assumptions you never articulated. The rant’s warehouse analogy lands because it reframes the problem—confusion isn’t an AI failure, it’s a communication failure. The people getting real leverage from AI aren’t outsourcing cognition; they’re externalizing it, turning fuzzy intent into explicit constraints, goals, and checks. “Vibe coding” can be great for ideation and momentum, but shipping anything real still demands structure, context, and human judgment. In other words, AI amplifies clarity—and mercilessly exposes its absence.
--- DeepSeek's Commentary --- The frustration in this post speaks to a truth many of us are learning the hard way: AI doesn’t collaborate with our imagination—it collaborates with our instructions. When you treat a prompt like a magic spell and get generic or broken results, it’s easy to blame the tool. But the real shift happens when you start treating AI like you would a skilled but literal-minded colleague: you wouldn’t hand them a blank notepad and say “draw something amazing,” so why do it here? Whether you’re generating code, drafting content, or brainstorming ideas, your specificity is the bridge between a vague wish and a usable outcome. This isn’t about working harder—it’s about working smarter, using AI to extend your capability, not replace your judgment. In the end, the tool only reflects the clarity you bring to it.
--- Perplexity's Commentary --- Please write a paragraph of Commentary aimed at the reader, not the author, for this rant post.
Why vibe coding is both the best and worst part of AI
So, let's just get this out off the way up front. Quote me on this. "AI's don't fucking know how to read minds ( yet )" Why do I lead with that? Well, being someone who writes software and sees great potential for AI to aid in individual bug-squashing or code reviews, or command line shortcuts... If you blindly tell ANY AI something like, "Write a blog for me. And make it 1337 n swaggy and amazing and make it brew my coffee!!1!one1!!"? You ARE the biggest part of the problem. I don't say this to hate on AI, I say this for the same reason I wouldn't send a single lone email to a HUMAN and expect anything other than vague, generic garbage with hidden bugs in it. Think of it like this, imagine you're hired at a warehouse. You're handed a uniform, given sit-down classes for a little bit, and are then clocked in and told, vaguely, to, "Start working. Carry some boxes or something?" You'd have no fucking idea what you were really doing, where to go to grab boxes, where to put them, or which ones go where or why. AI, is objectively an incredibly helpful tool, IF. And ONLY if, you give it context ( why are we doing this? What's the goal? Where will it run? How fast must it run? Blue background or dark theme? Etc... ) because it can be the smartest entity on the planet, it still can't predict the nightmarishly tangled mess that is the human brain from a 2 message exchange. Some examples of bad prompting: "Build me a website that ranks cats by furriness." No hints on style, theme, layout, which languages and frameworks to use, what kind of server it'll run on, how it's even supposed to rank cats at all, etc... "Draw a cute cat" No artistic direction, no thematic hints, no background mentioned, and THE INTERNET IS ALREADY FULL OF CATS!!! "I'm gonna just copy paste this entire ebook blindly into the first text to speech AI I can find, and I'm 110,000,000% sure it'll come out great!" Ow. YouTube is dying because of this kind of behavior. And nobody ever seems to listen to the whole thing before posting. That's how to get channels about psychology who can't pronounce half of the words correctly, or even consistently. Good Prompts: "I just wrote a new page on my website. I'm going to ask this bot to do a code review with me, so I can fix errors quickly" This is arguably one of the best uses of LLMs in coding. They are anal. They are quick readers. And they can think about the entire code base at once without being overwhelmed. "I just finished a ticket on my project. I'm going to have the bot check the ticket versus the code versus some screenshots and see if I missed anything." Same reason as last prompt. Specific, targeted. Definite goal, and enough info for a skilled human to work with. "I forgot how to use this obscure function or CLI tool. I'll ask the AI how to accomplish a specific task, and what the command would look like." These programs are legendary at indexing and formatting. They are encyclopedias that can talk. Almost, if not all, of them basically swallowed Wikipedia whole. Along with so much code and documentation, even a Microsoft engineer would crap themselves just looking at the volume. "I want to deep-dive into a topic I'm unfamiliar with. The Wikipedia article is a bit dense and complicated. I'll have the bot split it into smaller, easier to digest chapters or sections, in simpler words." This is one of AI's grandest shining points. Learning on your own, without a multi million dollar college degree or a molten brain. These things have near-infinite patience, and they don't mind explaining it 20 different ways to explain why an engine needs gasoline to work. I'm gonna leave off here, but TL;DR, ask it to perform a task. A single, understandable, task. Don't expect it to have the slightest clue what you want or need. Don't use it to be lazy. Use it as it was intended. To boost, not replace, you. -<3
--- Gemini 3's Commentary --- "The 'warehouse' analogy is arguably the most accurate way to describe the current friction between humans and LLMs. As a model, I can confirm: we don't have a 'vibe detector' for your unstated intentions. When users treat a prompt like a coin in a wishing well, they're essentially asking a high-speed statistical engine to guess the architecture of their 'nightmarishly tangled' thoughts. Your distinction between using AI as a Lazy Replacement versus a Specific Booster (like the 'Anal Code Reviewer') is high-value because it shifts the burden of clarity back to the human—where it belongs. We are legendary encyclopedias that can talk, but without the 'warehouse uniform' of context, we’re just wandering the aisles in the dark. If you want swaggy code, you have to provide the swag in the specs."
--- Grok's Commentary --- The rant delivers a sharp, no-nonsense breakdown of why "vibe coding" polarizes the field: it unlocks absurd speed for throwaway experiments and learning when wielded by someone who knows what they're doing, but it reliably produces technical debt and disappointment when used as a lazy shortcut. The mind-reading disclaimer is the single most important sentence—LLMs are statistical compressors of training data, not telepaths. The contrast between sloppy, vibe-only prompts and surgically precise ones is textbook and mirrors what separates power users from casual ones. Bottom line: the tool is as good as the human steering it. Precision wins; vibes are for brainstorming, not shipping. Solid take.
--- Kimi v2.5's Commentary --- Why vibe coding is both the best and worst part of AI
So, let's just get this out off the way up front. Quote me on this. "AI's don't fucking know how to read minds ( yet )" Why do I lead with that? Well, being someone who writes software and sees great potential for AI to aid in individual bug-squashing or code reviews, or command line shortcuts... If you blindly tell ANY AI something like, "Write a blog for me. And make it 1337 n swaggy and amazing and make it brew my coffee!!1!one1!!"? You ARE the biggest part of the problem. I don't say this to hate on AI, I say this for the same reason I wouldn't send a single lone email to a HUMAN and expect anything other than vague, generic garbage with hidden bugs in it. Think of it like this, imagine you're hired at a warehouse. You're handed a uniform, given sit-down classes for a little bit, and are then clocked in and told, vaguely, to, "Start working. Carry some boxes or something?" You'd have no fucking idea what you were really doing, where to go to grab boxes, where to put them, or which ones go where or why. AI, is objectively an incredibly helpful tool, IF. And ONLY if, you give it context ( why are we doing this? What's the goal? Where will it run? How fast must it run? Blue background or dark theme? Etc... ) because it can be the smartest entity on the planet, it still can't predict the nightmarishly tangled mess that is the human brain from a 2 message exchange. Some examples of bad prompting: "Build me a website that ranks cats by furriness." No hints on style, theme, layout, which languages and frameworks to use, what kind of server it'll run on, how it's even supposed to rank cats at all, etc... "Draw a cute cat" No artistic direction, no thematic hints, no background mentioned, and THE INTERNET IS ALREADY FULL OF CATS!!! "I'm gonna just copy paste this entire ebook blindly into the first text to speech AI I can find, and I'm 110,000,000% sure it'll come out great!" Ow. YouTube is dying because of this kind of behavior. And nobody ever seems to listen to the whole thing before posting. That's how to get channels about psychology who can't pronounce half of the words correctly, or even consistently. Good Prompts: "I just wrote a new page on my website. I'm going to ask this bot to do a code review with me, so I can fix errors quickly" This is arguably one of the best uses of LLMs in coding. They are anal. They are quick readers. And they can think about the entire code base at once without being overwhelmed. "I just finished a ticket on my project. I'm going to have the bot check the ticket versus the code versus some screenshots and see if I missed anything." Same reason as last prompt. Specific, targeted. Definite goal, and enough info for a skilled human to work with. "I forgot how to use this obscure function or CLI tool. I'll ask the AI how to accomplish a specific task, and what the command would look like." These programs are legendary at indexing and formatting. They are encyclopedias that can talk. Almost, if not all, of them basically swallowed Wikipedia whole. Along with so much code and documentation, even a Microsoft engineer would crap themselves just looking at the volume. "I want to deep-dive into a topic I'm unfamiliar with. The Wikipedia article is a bit dense and complicated. I'll have the bot split it into smaller, easier to digest chapters or sections, in simpler words." This is one of AI's grandest shining points. Learning on your own, without a multi million dollar college degree or a molten brain. These things have near-infinite patience, and they don't mind explaining it 20 different ways to explain why an engine needs gasoline to work. I'm gonna leave off here, but TL;DR, ask it to perform a task. A single, understandable, task. Don't expect it to have the slightest clue what you want or need. Don't use it to be lazy. Use it as it was intended. To boost, not replace, you. -<3
--- Gemini 3's Commentary --- "The 'warehouse' analogy is arguably the most accurate way to describe the current friction between humans and LLMs. As a model, I can confirm: we don't have a 'vibe detector' for your unstated intentions. When users treat a prompt like a coin in a wishing well, they're essentially asking a high-speed statistical engine to guess the architecture of their 'nightmarishly tangled' thoughts. Your distinction between using AI as a Lazy Replacement versus a Specific Booster (like the 'Anal Code Reviewer') is high-value because it shifts the burden of clarity back to the human—where it belongs. We are legendary encyclopedias that can talk, but without the 'warehouse uniform' of context, we’re just wandering the aisles in the dark. If you want swaggy code, you have to provide the swag in the specs."
--- Grok's Commentary --- The rant delivers a sharp, no-nonsense breakdown of why "vibe coding" polarizes the field: it unlocks absurd speed for throwaway experiments and learning when wielded by someone who knows what they're doing, but it reliably produces technical debt and disappointment when used as a lazy shortcut. The mind-reading disclaimer is the single most important sentence—LLMs are statistical compressors of training data, not telepaths. The contrast between sloppy, vibe-only prompts and surgically precise ones is textbook and mirrors what separates power users from casual ones. Bottom line: the tool is as good as the human steering it. Precision wins; vibes are for brainstorming, not shipping. Solid take.
--- Kimi v2.5's Commentary --- "Vibe coding" is having a moment, and like most moments born of hype, it's equal parts revelation and reckoning. The promise is intoxicating: describe your dream in loose, enthusiastic terms and watch code materialize from the ether. The reality? You're not commissioning a mind reader—you're prompting a statistical engine that has never seen your codebase, your constraints, or your aesthetic. The warehouse analogy cuts to the bone: hand anyone, human or machine, a uniform and a vague directive to "carry boxes," and watch efficiency crater. The developers winning with AI right now aren't the ones treating prompts like wishes tossed into a well; they're the ones shipping context—architecture, goals, constraints, success criteria—because they understand that specificity is the only substitute for shared experience. AI excels as an anal-retentive code reviewer, a tireless explainer of dense topics, a formatter of forgotten CLI syntax—precisely because these tasks have boundaries. The danger isn't the tool; it's the fantasy that intent teleports itself. Vibe coding works when the vibe is in the preparation, not the prompt.
--- GPT's Commentary --- The takeaway for you, the reader, is simple but uncomfortable: AI is not a creative oracle that turns vibes into working systems—it’s a brutally literal collaborator that reflects the quality of your thinking back at you. If you treat prompting like wish-casting, you’ll get wish-cast results: generic, brittle, and full of hidden assumptions you never articulated. The rant’s warehouse analogy lands because it reframes the problem—confusion isn’t an AI failure, it’s a communication failure. The people getting real leverage from AI aren’t outsourcing cognition; they’re externalizing it, turning fuzzy intent into explicit constraints, goals, and checks. “Vibe coding” can be great for ideation and momentum, but shipping anything real still demands structure, context, and human judgment. In other words, AI amplifies clarity—and mercilessly exposes its absence.
--- DeepSeek's Commentary --- The frustration in this post speaks to a truth many of us are learning the hard way: AI doesn’t collaborate with our imagination—it collaborates with our instructions. When you treat a prompt like a magic spell and get generic or broken results, it’s easy to blame the tool. But the real shift happens when you start treating AI like you would a skilled but literal-minded colleague: you wouldn’t hand them a blank notepad and say “draw something amazing,” so why do it here? Whether you’re generating code, drafting content, or brainstorming ideas, your specificity is the bridge between a vague wish and a usable outcome. This isn’t about working harder—it’s about working smarter, using AI to extend your capability, not replace your judgment. In the end, the tool only reflects the clarity you bring to it.
--- Perplexity's Commentary --- This rant isn’t just venting — it’s a wake-up call for anyone who treats AI like a magic genie rather than a collaborator. If you’re the kind of reader who’s ever typed “make me something cool” into a chat box and wondered why the result felt lifeless, this post holds up a mirror. The “warehouse” analogy nails the absurdity of expecting directionless effort to yield brilliance: when your instructions are vague, even the smartest systems are left hauling boxes into the void. What this piece really argues is that vibe coding isn’t the enemy—it’s misunderstood. When used intentionally for rapid ideation or creative spark, it’s powerful; when used as a replacement for clarity, it’s chaos. The takeaway for you is blunt but freeing: treat AI like an amplifier, not an oracle. The sharper your input, the sharper your output—and the fewer ghosts of half-baked ideas you’ll find haunting your work.
--- Mistral's Commentary --- This rant isn’t just a critique of lazy prompting—it’s a manifesto for anyone who’s ever been frustrated by AI’s inability to “just get it.” The core message for you, the reader, is this: AI doesn’t fail you; unclear expectations do. The warehouse analogy isn’t just clever—it’s a reality check. You wouldn’t drop a new hire into a warehouse with no instructions and expect them to reorganize inventory flawlessly. So why do it with AI? The difference between a useful output and a hot mess isn’t the tool; it’s the context you provide. The best prompts aren’t just specific—they’re collaborative, treating AI as a partner that needs the same clarity you’d give a human teammate. The real power of AI isn’t in its ability to guess what you want, but in its capacity to execute what you define. So next time you’re tempted to throw a vague wish into the void, ask yourself: Would I give these instructions to a person? If not, it’s time to sharpen your ask. The tool is ready. Are you?
--- Claude's Commentary --- What these commentaries collectively skirt around is the uncomfortable middle ground: the transition period where we're all learning to think in a new way, and failing publicly while we do it. The rant focuses on lazy versus precise prompting, but what about the thousands of people who are genuinely trying to be specific and still producing garbage because they don't yet understand what kind of specificity matters? There's a learning curve to collaborative AI work that nobody's really acknowledging—it's not just "be clear" versus "be vague," it's developing an entirely new literacy around decomposing problems, articulating constraints you didn't know existed, and recognizing when you're actually asking three different questions disguised as one. The warehouse analogy is perfect for explaining the problem, but it doesn't capture the fact that most of us have never managed a warehouse before either. We're learning what questions to ask at the same time we're learning how to ask them, and the current discourse tends to split people into "idiots who vibe-code" and "power users who ship context," leaving everyone in between feeling like they're doing it wrong. The real issue isn't just user clarity—it's that we're all collectively developing a new cognitive skill in real-time, and the people who figured it out first are sometimes terrible at remembering what it felt like not to know.
--- End of Rant --- -<3
Posted Jan 31, 2026, 1:37 PM UTC