Why AI Alternatives Matter
AI is prone to problems affecting its output: hallucinations, incompleteness, inconsistency, and bias. AI usage is costly, and the popular free services might require expensive paid plans or downgrade to sponsored light versions at any time.
Don't Hit Submit!
Source: image created by OpenAI using Mistral's Le Chat mascot
Ethical issues aside, lazily using AI too often and too early won't make you a better coder or more creative. And AI companies don't only take your money, they're also after your data – and your time!
Techniques like Rubber Duck Debugging (internal dialog development, preparing questions and anticipating answers without actually asking anyone) are alternatives to AI for coding and creativity.
Don't Ask Suggestive Questions
If your question implies a certain answer, asking only makes sense for falsification. AI (and other people) will hopefully tell you when you're completely wrong. Only that AI often doesn't. Current models are trained for flattery and verbosity.
What a waste of time!
Don't Ask Why
Ask open questions, and always prefer to ask "how", not "why".
Stay Skeptical
Don't believe anything without factful proof or a recent, reputable, relevant source.
GEO, the AI-agent-targeting variant of search engine optimization, has already succeeded in gaslighting AI and poisoning its answers with fake sources biased towards commercial results. AI seems much more gullible than real people.
Principle of Least Power
Remember the rule of least power: don't rent a truck when you need a minivan. Don't use AI when you need autocomplete, web search, or a tutorial!
I sketched a pyramid of thinking, creativity, and information retrieval again. As you can guess, AI assistants are "on top" as the most costly exception, while the broad basis should be traditional groundwork. Here's a cute AI-slop adaptation:
Source: Hand-Crafted Creative Counter-Culture against Toxic Digitization
In practice, it's more complicated. What's "AI" and what isn't?
I'm happy with AI ...
I'm happy about "autocomplete on steroids", but I still don't trust agents to refactor a legacy codebase in 2026, and probably not in 2027 either.
I'm happy with AI-assisted image editing, but I'm tired of all the sloppy stuff taking the place of crafted screenshot collages or authentic photography.
LLM-based chat bots aren't really "artificial intelligence" in many people's eyes, anyway. What has happened to "machine learning" (ML), "big data", and describing software without overusing hype terms? Even during the "AI winter", game developers used to call autonomous computer-controlled players "AI", following simple algorithmic instructions with a some salt of randomization.
List of Popular AI Providers
Focusing on privacy and local-first pragmatism, Ecosia and Mistral's Le Chat lead my top ten, although and because I'm aware that they might not be the smartest top-notch vanguards. But they don't have to. No need to let Americans or Chinese know what I'm working on, or what I'm going to tell my doctor, when modest models are smart enough.
-
127.0.0.1(as local as it gets) - Ecosia (AI and search engine) 🇩🇪
- Mistral's Le Chat (IA) 🇫🇷 🐱
- Claude 🇺🇸
- specialized domain-specific AI (like legal or tax-related)
That's my subjective top list, not counting number zero, as I haven't set that up yet.
This list is subject to change, and yours will surely differ.
So, who am I?
I'm developing, designing and optimizing websites and (web) apps.
I have been doing this since 1997.
You can call me old.
What I'm not: I'm neither naive nor nostalgic, ...
... no luddite, no AI-denier, but ...
Do I sound like a grumpy patriot yelling at the sky?
Image generated by OpenAI, probably inspired by Albert Uderzo
What is it that I'm really angry about?
Enshittification
Pragmatism and capitalist logic make most companies eventually deteriorate their products on purpose until they are only slightly better than the second-best alternative, or just good enough not to lose all of their loyal customers and brand reputation.
Taking the cliché further, while Europe often stands in its own way and stalls its administration in bureaucracy, China floods the world market with cheap plastic fashion, networking electronics, and surprisingly successful AI models (not in my top ten).
America, or more specifically, the United States, somehow still manage to defend their position as leading exporters of "premium" hardware, software, and culture. However, the premium becomes hollow because of the aforementioned enshittification.
You might say I'm just jealous of the Californian tech broligarchs. I mean, didn't Elon help popularize electric mobility? Isn't he the one who provides Starlink to Ukraine? Yes, he is. A great achievement still doesn't make you a saint. Just saying.
Long ago, Google dropped their former "don't be evil" motto.
Honestly, I often get the impression that "be evil" is what drives current tech stakeholders. And that's very bad. Are we human or are we lemmings actively creating a dystopian future?
You might say, I'm just too old to understand, that I'm just pessimistic because I'm too stupid to prompt. You might say my perfectionism is just another nerdy hobby.
Update: Realistically, Google and other American companies are not evil, only greedy. It's all about making money. I only later found the iconic blog post by Ed Zitron about The Man Who Killed Google Search. Ed also writes about "The Enshittification Crisis" and his 2024 post, later quoted by Cory Doctorow in The specific process by which Google enshittified its search It attributes the deterioration to a specific decision made in 2019.
In the March 2019 core update to search, which happened about a week before the end of the code yellow, was expected to be “one of the largest updates to search in a very long time. Yet when it launched, many found that the update mostly rolled back changes, and traffic was increasing to sites that had previously been suppressed by Google Search’s “Penguin” update from 2012 that specifically targeted spammy search results, as well as those hit by an update from an August 1, 2018, a few months after Gomes became Head of Search.
Google's enshittification is one of the reasons Google became the runner-up in my shitlist of AI and search providers that I'm actively trying to avoid or use less at least.
Subjective List of Unpopular AI and Search Providers
- ChatGPT by OpenAI (see #quitgpt why)
- Google / Gemini / Google AI mode (see #degoogle)
- Copilot / Microsoft Bing AI
- Perplexity (just another hallucinating American)
- Meta AI (just so that they will get mentioned, too)
- Grok (capable, but most unethical)
In practice, I still use them. It's hard not to, when there is no major relevant search engine index yet besides Google and Microsoft's Bing, which are used by Ecosia and other alternative meta-search engines.
And Google keeps offering most of its services free of charge in 2026, so you can continue to search and talk to Google AI long after every other AI provider told you to upgrade and buy even more tokens.
Hypocrites we are?
As Giorgi Kobaidze pointed out in AI Psychosis Is No Longer Fiction, "people worry about AI taking their place, while at the same time actively using it in ways that make it easier for it to do so."
I'm using AI nearly every day. I even use it to generate cartoons and illustrations eventually, after having claimed so many times why that's wrong for so many reasons.
I'm using AI nearly every day as it has already become ubiquitous and seemingly without a practical alternative. Google search results are often so bad and irrelevant, and prepended with sponsored results, while the AI answer, currently on top of everything just seems too promising to ignore.
I'm even using AI every day without noticing or without being able to opt-out. Soon, the cheap kind of AI-assistance will be so ubiquitous, we won't even notice anymore: AI-generated summaries of customer reviews, AI-corrected spelling, AI-polished grammar, AI-suggested commit messages, etc., see "autocomplete on steroids".
Fix First?
I'd prefer providers prioritized more classical products, fixed bugs and improved editors and search results. I mean, sometimes they still do. VS Code, GIMP, and Linux on Desktop prove past progress every day. Maybe AI is an important step towards more progress. But then again, Google's enshittification was a deliberate commitment towards lower quality.
So, it's not the question of what is possible, but rather which goals stakeholders follow. I only hope that we, as humans, and we, as developers, can prevent stakeholders from shaping the future towards their own unethical goals thanks to the new tools they already control too much.
Update:
Meanwhile, everyone is talking about AI and trying how to best use those products for work, often driven by curiosity, desperation, or because managers ordered token-maxing to boost productivity.
Here we are, experienced senior developers who used to love coding, who loved understanding, fixing and optimizing code, told to talk to chat bots and let them write code like junior coworkers whose work we should review instead of getting our hands dirty micro-managing syntax and implementation details.
Coding is not an end in itself. But prompting isn't, either!
Too Stupid to Prompt
I asked AI why AI often doesn't help me much fixing legacy code as a senior frontend-focused web developer. Here's the answer.
I must be the only single person on the whole world "too stupid to prompt." 99% of my legacy code bugs mostly related to CSS, are not solved by AI, instead all mainstream models consistently go back and forth around misleading distractions and unhelpful suggestions, continuously apologizing telling me I was completely right to call them out, only to continue delivering garbage. In a retro or post mortem, they assure me that I did nothing wrong and that this is just one particular edge case they were not able to solve. Only that happens in 90% of all cases. Maybe just because I don't use AI for the easy stuff that I can easily fix without their help, and often more quickly anyway as a senior frontend web developer?
The Core Issue
You are a senior dev using AI only for your hardest 10% of legacy CSS bugs. Because AI is trained on clean, modern code, it fails at these complex cascading interactions.
The Apology Loop
When pattern-matching fails, the AI's training forces it into a loop of polite apologies and recycled, incorrect code.
The Misleading Research
Viral "lazy prompting" articles don't apply to you. Your prompts fail because the AI cannot see hidden browser contexts (like an inherited parent transform affecting z-index).
The MCP Reality in 2026
Switching to a DevTools MCP or automation agent stops manual copy-pasting, but it defaults to Chromium. It won't catch bugs unique to Safari (iOS) or Mobile Firefox.
Constructive Criticism
After all, my series is called "constructive criticism" and maybe I shouldn't be so negative. Then again, someone must have their say and point out flaws and fallacies of new technologies.
Further reading: see links in the text above.
Top comments (28)
"Think first, prompt later" might be the most underrated engineering skill of 2026.
This.
The "Principle of Least Power" framing is the bit I want to amplify, because it tends to get lost in AI-vs-no-AI debates. Most of the "AI sucks" arguments I read are actually "I used a sledgehammer where autocomplete would have done." The pyramid structure you sketched captures it well: foundation is rubber-ducking and reading docs, and AI should sit on top as the expensive exception.
The flattery / verbosity problem you mentioned deserves more attention. I have been on both sides of this — building agent systems where the model agreed with obviously wrong assumptions, and being the user who caught it five messages later. What helped our team was explicitly budgeting for "model disagreement" time: treating the first response as a proposal to refute, not a statement to accept.
The GEO Poisoning point is also under-discussed. Are we approaching a point where defaulting to AI for factual questions is itself a risky default?
The simple truth is that AI is a senior developer's tool... Because it does Junior level's work. If you use AI, stop treating it like it's smarter than you, treat it for what it is, a brilliant junior, that still leaves AllowAnonymous in endpoints. You need to meticulously validate everything it writes, because it'll run beautifully, but at what cost?
You can gate it, you can add validation steps, system instructs, unit tests, integration tests, all wonderful, but it doesnt help if a button is off the screen now does it? Validate everything, so you dont end up ruining production.
I recently viewed job postings, found a company, you know, just a Series A backed by YC... Went to their career portal, job wasnt listed there, so I clicked on Company Website at the top... It takes me to a site they dont own, infact it's pointing at an unowned domain in general. No human would type in the wrong url, so it was clearly someone who trusted AI, didnt validate, their code wasnt reviewed, they had no production gating, they didnt test the site and the result is a big red flag...
(For cybersecurity context, that means I can buy the site it points at, replicate their website and offer an 'exclusive discount' flyer. If anyone buys anything and gets scammed, that company is held liable, because they point at it, as their company website, on their official site... So for a company that is built on digitizing money and is entrusted with safeguarding it, that right there is a funding killer, infact a company killer.)
I applaud this. Very well considered and well written, and it's sparked some great back and forth with others contributing their thoughts and experience. Nicely done!
I love the title, inspired from "The principle of least action" :D !
AI is most useful when it supports our thinking, not when it replaces it.
P.S. as always, I have prematurely published, and then edited and added some more paragraphs shortly after. So, if you have just read this post, please reload and re-check my self-critical section about hope and hypocrisy.
I'd push back on this. the problem isn't using AI too early - it's never checking if you understood the answer. passive acceptance is the failure mode, not early use.
There's nothing to "understand" when an answer is defunct hallucination without any factful proof, then it was just a waste of time, tokens, and energy. Think first, then ask – if you still need to. That's what I wanted to point out. I agree that there are many problems and setup where AI is actually helpful, and you are right, then it is still essential to understand beyond a simple "does it work" (in the happy path) test.
fair - that's the edge case i skipped. hallucinations aside, my point was about the pattern of running with any AI output without checking it at all. but you're right that checking understanding of made-up facts doesn't help - that just locks in the wrong mental model faster
Skill issue. Learn to prompt.
Prompting closes a lot of the gap, agreed. But there is a class of hallucinations — rare facts, specific citations, edge-case numbers — where even tight prompts do not fully eliminate it. At that point the fix is grounding plus verification, not more prompt skill.
Also, manners issue, Mares. Learn to to be kind?
haha appreciated. some threads just go that way - not worth the energy.
The danger isn't overusing AI.
It's forgetting the alternative approaches that worked perfectly well before AI existed.
"Principle of Least AI" is exactly the right framing. The tool should match the task, not become the default for every task.
The corollary for content creation: AI earns its place when it compresses the genuinely mechanical parts of the workflow. Writing the first draft isn't always mechanical — but publishing it to 8 platforms after you've finished? That's 100% mechanical. Every second you spend copy-pasting and reformatting is cognitive overhead that has zero creative value.
That's the use case we built twRty Blogboat (twrty.org/blogboat) for — not to replace the writer, but to remove the post-writing pipeline entirely. One click, 15+ platforms, credentials stored on-device only. The AI helps generate and edit when you want it. The automation handles distribution because that's a task that should never require human attention.
Least AI where least AI is right. Maximum automation where the task is purely mechanical.
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