--- title: "The Great U-Turn: Why AI Walled Gardens Will Break the Legacy Web" url: https://ishchuk.eu/blog/the-great-u-turn-why-ai-walled-gardens-will-break-the-legacy-web published: 2026-03-24T11:40:00+00:00 updated: 2026-04-24T10:40:36.302746+00:00 tags: [mcp, open source ai, walled gardens, aeo, geo, agentic web] --- There is an interesting change happening in the open-source and AI space. Everyone knows about OpenClaw, right? And we know that Anthropic is pretty much banning API accounts that they identify as OpenClaw users. They don't like their services being used by unpredictable open-source applications - in this case, OpenClaw. Similar moves are happening with Gemini and ChatGPT, because everyone wants users to stay on their own platforms. You can see Claude Code going after OpenClaw's features, with dispatch and channels. The enterprise is once again trying to shut it all down, to build those locked-in platforms and walled gardens - something we have seen before with APIs. They want to preserve the status quo. In this case, I think there will be a bigger push towards open-source models that will always work with your own instance of OpenClaw, or whatever comes next. At the same time, I believe the Chinese players won't miss their chance to capture even more market share. The moment you start using their models in OpenClaw, they first get access to a lot of data. On top of that, they get market penetration, and they can subsidize it in the very beginning as they did with pretty much every product they have been building. So these cheap models will be there for you to use on the API level, not just via local hosting. Just like the Xiaomi's recent model and many other examples, they will be dirt cheap. This will be their foot in the door. It might be a massive opportunity for Chinese players to distribute their models, harvest more data, and create better products that are simply cheaper. And since people don't really care that much about cybersecurity anymore, the data will flow. It will flow to China simply because the major players like ChatGPT, Claude, and Gemini are trying to create walled gardens. This also resurfaces the very same question we had a couple of years back when ChatGPT was released. We built the entire web to block the bots. We had scrapers, proxy services, fingerprinting, and shifting UIs to prevent you from taking screenshots. We had many things that were built to obfuscate the backend infrastructure from everything on the surface level. And now, these companies have to make a rapid and dangerous U-turn and rework their entire database layer to resurface much more data for the agents. If we assume these agents will do grocery shopping for us, travel bookings, maintenance work, and so on, many of those applications will have to figure out how to monetize the whole thing. The primary interface will now belong to AI agents. The very bots that we were supposed to be tracking and blocking are now the key to success. The companies that open up and figure out how to monetize this new paradigm will win the game. Bigger players who won't be able to shift fast and some of them might lose. For example, Answer Engine Optimization - the new term replacing SEO - will rely heavily on websites optimized for LLMs and crawlers, with extremely easy and fast access to data. We can expect new e-commerce players, new websites, and new SaaS ideas coming to the market that will be overly optimized for LLMs. They might even be boring in a way, or they might have separate interfaces on the API level, on the MCP level, that will be simplified and fast to load, with a completely different set of data and commands available. For example, API endpoints won't be that atomic anymore. They will have more telling names, with a bigger set of descriptions. Some API endpoints won't land in the MCP, and some data will be made available in a more convenient way for LLM crawlers and agents to access. So there will be another layer built specifically for the agents. This is a chance for fresh e-commerce players, for pretty much every website and everything on the web these days. It is an opportunity for new players to build from the ground up - from scratch - a totally new set of interfaces. To come up with a new vision, a new approach, and a new standard to the web that will account for the new type of user: a dummy agent that requires fast, clear, and highly available data. This data shouldn't even be visually present on the page anymore. There is already this agent-to-agent protocol proposed by Google, and there will be more of those. Soon enough, there will be separate interfaces created exclusively for AI agents. There will be a separate discipline of cybersecurity experts. The shift will be massive. The investment required to get this data open again is massive. It will take months and years for some companies to get this in order. And this means that whoever gets it fast will win this race again. --- --- title: "Code Is a Liability, Not an Asset" url: https://ishchuk.eu/blog/code-is-a-liability-not-an-asset published: 2026-03-04T11:43:00+00:00 updated: 2026-04-24T10:43:13.493453+00:00 tags: [cory doctorow, code liability, software engineering, software] --- I listened to a really interesting podcast by Cory Doctorow today, based on his essay "Code is a Liability." There are a lot of points that I find extremely interesting, and I agree with many of them. First, the core idea: code is a liability, not an asset. He explains that executives today, the ones pushing for massive AI integration, are "peeing green" when they hear how many lines of code were generated. In my own work, I've seen leaderboards for employees to see who generates the most lines of code. It's awful because every new line is an expansion of the attack surface, another fracture, another tiny hole in your ship that you don't know about. His second point is that AI is the asbestos we're putting in our world's walls. For those who don't know, asbestos can cause cancer. This technology was popular in Spain about a century ago, and some people are still forced to live in those old, unhealthy buildings. AI, he argues, is a similar hidden danger. Third, there's a faulty idea that code becomes stable and unbreakable after its initial release and stabilization phase. The assumption is that it just works, with no moving parts, which is obviously not the case. Code is a brutal machine that requires heroic efforts to make it work and keep it running. This leads to another crucial point: writing code and software engineering are two different things. When writing code, you care about performance and beautiful syntax that runs on anything. You focus on the language, memory usage, and getting the code to run. With software engineering, you care about the long-term things: the operations of the system, the downstream and adjacent systems, everything that runs in parallel. You are a system thinker, optimizing a complex machine with many integrated pieces, external systems, and, most importantly, humans. Software engineering is much more difficult. You know your system has to fail well. It has to be understandable and maintainable by newcomers, because people don't stay at companies for long these days. Imagine every line of AI-generated code becoming an orphan in a year when its creator leaves. New employees will have to apologize for all this shitty work that was done. The longer a piece of code is in operation, the bigger the issues. Doctorow gives the example of the Bloomberg Terminal. Their systems run on a specific RISC architecture. Now, they have to pay for special hardware, hosting, maintenance, and engineers who understand that architecture. Everything they do has to be backward compatible with both older and newer hardware. Keeping such a system safe, performant, and backward compatible is nearly impossible. This brings up the assumptions we make as engineers, which often come from experience-what the Germans call *Fingerspitzengefühl*, or a "fingertip feeling." The more experience you have, the more you know what to touch and what to avoid. You can't always explain it, but this intuition for production, software, and architecture is invaluable. The problem is that junior and mid-level engineers today won't have the incentive or the time to dive deep into Python, Go, or any other language. There will be an army of people using AI to generate something impromptu, without caring about the long-term consequences. This is a huge problem, and it means that at some point, planes will go down and cars will break down on the interstate because mistakes will happen. They are already happening. Some issues have to be solved again and again. He mentioned a house in the US where, for some reason, a default GPS setting puts coordinates onto a small town. People constantly arrive there trying to find their lost devices because of inaccurate data. This kind of problem requires continuous attention. Ultimately, the best code is the code you never wrote. You don't have to maintain it or make it backward compatible. The question a good engineer should ask is not just *can* we write this, but *should* it exist at all? Sometimes, the answer is no. When you write something yourself, you get that specific fingertip feeling for the issues. You can predict them, you can understand them in the logs. Without writing it yourself, you don't develop that muscle memory and you won't be able to solve much because you won't understand what happened in the code. Microsoft's idea of having AI agents for every little task, managed by a master agent, is basically an admission that these agents aren't very workable on their own. Someone at Microsoft even said they want to rewrite their entire codebase with AI. This is not possible. They promise 95% reliability for these agents, but when you multiply the probabilities of failure across a swarm of them, things are bound to go wrong. I was extremely surprised by the depth of Doctorow's explanations. He's a really bright guy. I've bought a couple of his books, and they seem special. An exciting, and perhaps dangerous, time is ahead of us. The more liability we create today, the more work there will be for future generations who will have to figure out what's happening with just a textbook and a mountain of unmaintainable code. As someone said on another podcast, your responsibility with AI grows exponentially, because now you have more lines of code being shipped than ever, and you can't guarantee how any of it communicates --- --- title: "The Cold Truth of Static Intelligence: Why Intent Engineering is Failing" url: https://ishchuk.eu/blog/the-cold-truth-of-static-intelligence-why-intent-engineering-is-failing published: 2026-02-26T11:44:00+00:00 updated: 2026-04-24T10:45:26.377325+00:00 tags: [intent engineering, llm limitations, ai ethics, static models, klarna, agi] --- Nate Jones raised an interesting point on YouTube today regarding "intent engineering" — something that we are not working towards. In a way, it touches on subjects raised by Ilya Sutskever some time ago. It's basically about the reward functions and so on. I'm actually not sure if LLMs can even have intent as an entity. So in this case, I'm not really 100% with Nate, but his take on our current obsession with LLMs in three stages is useful: 1. Personal productivity with chat. 2. Automated workflows with AI. 3. Fully automated, independent agents running in the cloud. He uses the case of the European finance app, Klarna, to argue that we are failing at "intent engineering." Klarna replaced many human support agents with a fine-tuned LLM. Yes, this saved a lot of time and money. But they eventually had to rehire humans to do the same job because the LLM was presumably too effective yet too "cold" for the liking of their clientele. Let's be honest. This example reminds me of static time series predictions. And I will explain why. The case Nate is making is that we are busy with *context engineering* — providing information on what to think and what to consider — but we don't provide information on *how* to think. We are missing the behavior, the changing values, and the reward system for each specific case. One customer has a specific reward function; another customer with a longer history requires a different behavior. If it's a platform, we have multiple sides to the problem, all with different intents. Even if you have a system prompt explaining how to act, it's not ideal. Plus, let's be honest, we are not retraining those models constantly. We are light years away from actual learning where beliefs, value systems, and internal coordinates update based on experience. The nature of learning is that we update our beliefs and facts. Based on this, we adjust the course of our lives and careers. LLMs are not capable of doing that. They are centralized, expensive, and static. You have to merge this static model with the concept of "intent," which can fluctuate on a weekly or monthly basis. This is where I think agents will fail. Value is a really human thing. Actually, if you think about it, value is pretty much tied to you being somehow damaged in your childhood or perhaps something genetical. You didn't have enough attention, or you had too much. You were bullied, or you lived alone in the forest. You fell down, broke the ice, and were frozen for a while, and since then you are more careful about things. These pieces are really individual. On top of the different context every human has, we also have this value system that is an extremely hidden "black box" — something we don't even fully understand ourselves. So saying that AI agents are close to the human condition is really funny. I am pretty sure AGI is not possible at this point in time. I would say another 50 years, maybe. But not with LLMs, obviously. The scaling is almost over, and now we will just collect the yield of the implementations. This is the last moment for LLM development and scaling. ## A Side Note on Workflow Speaking of tools, I'm building prototypes now using three major players. I start with **Lovable** to have really fast iterations—feeding it screenshots from Miro to explain my vision. Then, I turn that design into a "knowledge markdown file" to keep the styling consistent. When I run out of tokens—and let's be honest, **Claude Code** basically dies on you and gets expensive—I switch to building locally. I decided to try out the **Antigravity IDE** with **Gemini Pro 3.1** enabled. I have to say, it works pretty well. Plus, the Gemini product is not expensive compared to the enterprise credits you have to buy for Claude, which burn out fast. ### The Verdict Generally speaking, regarding intent engineering: we are light years away from anything resembling a learning system with a value-coordinated reward function. We have the context, which is being dynamically worked on, but the value system—the thing that informs agents what is important *right now* based on past history—is missing. What is the intent now? Is it a bad prototype with bad security? Is it an MVP? Who is accessing the MVP? These things change constantly. You can try to tackle it with changes to the system prompt, but the "intent" — the *why* we do what we do—is a different beast. I'm not sure LLMs are even capable of understanding the purpose of anything happening. We aren't there yet. --- --- title: "System Failure: The Great Convergence and the End of the Junior Role" url: https://ishchuk.eu/blog/system-failure-the-great-convergence-and-the-end-of-the-junior-role published: 2026-02-10T11:41:00+00:00 updated: 2026-04-24T10:42:02.629223+00:00 tags: [ai agents, future of work, claude code, lovable, tech convergence] --- I've been listening to Nate Jones on YouTube-that's the guy who runs a really successful AI Substack-and I watched a couple of videos of his. I have to admit that he changed a couple of things about my understanding of the current AI landscape. Because obviously, as a product person, I'm not coding myself, I'm not using Cursor on a daily basis. Yeah, I'm using Claude Code now, and I'm using a lot of Lovable and so on. In the first video that I watched a couple of days ago, he claimed that there is this converging career path now. Because previously, obviously, you had the developer, you had the leaders, something in between, you had designers, you had product people, you had analysts, and so on. But at this point of time, basically, product people started to use Lovable to build things. That means they don't need designers anymore to such an extent; they don't really need engineers to build prototypes and simple things. At this point of time, the very same goes for engineers, and the very same goes for designers. I personally know one of the designers at my current gigs-one of the projects that I worked on-and this designer is basically not designing anymore. He is building prototypes, and he's pretty well-versed in hosting this and building backend even in Claude Code now-a really simple one, hooking it up with Supabase and these kind of technologies. And he's right. Nate is right. There is this big elimination of the white-collar work. These things are being merged; there is no career path anymore. If previously you would be using something like roadmap.sh, kind of planning your roadmap, your career, like five, ten years from now with steps that you have to do in the middle... basically the whole thing is collapsing. Collapsing in a way, more on the implosion side, right? So now, the whole thing, the whole career path is like five months. So the time frame for the change-so time to change really-is just dramatic. And there are no standards, no workflows. The security is obviously lagging behind anything that Anthropic, OpenAI, and Google do really-Anthropic being the best among them. And clearly winning the race. This means that if you are not on the bandwagon right now, you are not working on your skills, you are not playing with those tools... because the analogy that Nate is presenting is basically you riding a bicycle, right? So the faster you go, the more stable you get. And he makes the case that if people are sitting this out, trying to wait until there are some kind of a guidebook, laws, standards for the PM to use the AI, this won't really exist. So the question now is whether you get on the other side, you get on this train, and you build your own workflows, your own understanding how AI is going to be the engine that sits on top of your domain knowledge, of your experience, your ideas. And if you're able to incorporate it now, you just have like maybe seven, eight months, maybe a year or so, just to figure out how the whole thing will incorporate your specific domain skills. Obviously, the domain skills are not going to disappear, which means my code will be of worse quality based on my instructions, obviously, and the application business-wise might be worse on the end of some engineer who decided to build the app himself, 100%. The same goes for designers. Even so, frankly speaking, if they are building something from scratch, they will be really good at UX, applying the modern design practices, and pretty much copying the interfaces, but they might have issues-same with me-like the backend things that might be not that secure and so on. And obviously, some assistance on the senior side will be needed. Having said that, obviously, the domain knowledge is not disappearing, but AI probably eliminates the entire entry point for juniors. For the time people and companies would invest into them to develop those skills to become regulars, to become seniors. Seniors will be using the AI, and the juniors... I'm not sure about this, if companies will be ready to invest that much money into juniors, unless you as a junior invest a lot of time yourself just to educate yourself, not only on the fundamentals but also on the AI usage. And even in this case, you won't be able to compete. Because in this case, if the Claude license, or Gemini license, or OpenAI license costs that much, then companies can provide them with skills, with guidelines, with clear structured projects and so on. So in this case, the experience of the engineer is not that important anymore. They can hire someone from a developing country, and they wouldn't really care that much about this because they have standards and the AI agents are getting better. Just to underline this point: Claude Opus, the new one, basically they experimented with this running for two weeks, and it wrote the entire C compiler, with 160,000 lines of code, I think. Having this whole thing in memory, testing it out, and it's perfectly functional and so on. And it ran independently for two weeks. Which... well, it is pretty much a regular developer at this point of time, not even a junior anymore. Obviously, if you are working with a legacy codebase written by humans and so on, this only means that the seniors are still there to prepare the whole setup, the codebase behind it, just to make it usable/operational on the AI level. So soon enough we'll be custodians, butlers, cleaners, people who are just there to keep an eye on AI agents, give them orders, controlling the outputs and so on. So we are the operators of the machines at this point of time, until they are good enough with reward functions to build those things themselves really, and even testing in production. You can imagine a future where we have the agent writing different types of functionalities, testing them out with different audiences dynamically, and figuring out which version performs better with a certain reward function that would be provided by the business owners. Or not even them, because the AI would have those reward functions and proposing them, or even testing them out, but obviously it would need to understand the current KPIs and the company. If you happen to have any at this point of time, because there is this degradation of skills on the business side, on the design side, and pretty much across the entire Western world, I would say. So I'm not sure how this develops. Having said that, there is one note here. I think as PMs, designers, developers, we only have about maybe 7, 12, 24 months before those tokens become really expensive. So everyone will be really locked in terms of vendors and hooked up on the system hopelessly. Which means that companies like Anthropic will be able to charge you a really solid piece of money. And soon enough, well, these companies now are buying those licenses for engineers and pretty much everyone who wants to play around with this. But soon enough, they will be so expensive that only the seniors, the senior staff who know what tokens are, how expensive the whole thing is, how to engineer the context-not just prompting, right, but the context engineering, the dynamic things just to explain to the agents how it is supposed to be acting, preparing the codebase, the instructions and so on-only the senior guys who will explore the topic to the best of their ability, they will know how to oversee those agents, how to order those pieces of works. Only these people will start getting licenses because they will be really expensive. So soon enough, there will be this gap with people who invest a lot of their private time these days just to learn the systems, to learn the building. And everyone else who is just sitting it out and waiting, and waiting for some standards to come and for those models to become really cheap... I don't believe they will be. At some point of time, we all expect the VC money to run out, and this means that these people will have a need to have the real economy-you need economics behind the product. This means the tokens will become really expensive. So soon enough, these companies will start saving and killing those licenses. So only key people who learn to use them now will get a chance to operate with AIs, and they will have this really immense, incomparable, revolutionary advantage because they would have the experience, they would have the knowledge, they would have the skills. And obviously, a lot of people are writing crappy code or creating crappy code now in companies they work for, when the company is also paying for those licenses. But these people who are risking it now, they will be in order. They will have the skill to offer in their next gig, next job, next project where they will be able to use the tokens in a proper way, and they will be able to save those companies the money. There will be consultants who will prepare the companies with legacy codebases to make the whole thing more agent-ready and so on. But I think that we don't really have that much time as PMs, as designers, as engineers, especially if you are a junior or regular. You just have a couple of years probably to get ready to learn how to automate those things, how to steer the whole thing, how to learn building with AI. There is no way around it anymore. Yes, you can check out, you can switch your career, but if your intention is to stay in tech, there is no way around it really. Not anymore. So it is our way or the highway. And highway in this case being you switching to something not tech... not tech-heavy really, some handwork, some sales, whatever, I don't know. Maybe some engineers will move out to be the developer experience advocates or the sales people, the account managers who will help out those AI companies to hook up those companies out there even heavier on AI. And these engineers will have the know-how, they will have the knowledge-well at least they will have enough technical knowledge to prepare the codebases and integrate companies even more with those AI agents of a given provider. And at this point of time, I don't think we are at the point where the LLMs become widely spread in terms of local models, something that you can host yourself. Not really. It just looks like that we will end up with another really crucial and big subscription. If it goes down, if you can't really afford it anymore, you just lose like 80, 70 percent of your competitive advantage if you had any. And there is no way around it really. The swarms, for example, those groups of agents that you have on Claude Code at this point of time, it is only the beginning. And looks like the speed of change there, it speeds up the whole thing. It speeds up really. Things that we saw like half a year ago, they are just completely different today. And no one is up to date at this point of time. And you have to dedicate a lot of your own private time after work just to be relevant if you want to stay in this industry, if you want to reap those rewards, if you want to keep earning the bucks. You just have to stay. After work, you have to learn, and you have to squeeze every opportunity in your workplaces at this point of time to use AI in some capacity. Because if you don't, there will be a lot of people expecting that there won't be that many job places in the white-collar industry anymore. This means that only the seniors, only people with really heavy experiences and really, really know-how they possess in regards to AI and this integration of AI and their skill set-this is the only profile, career path now. It's just for you to dive in with your own private funds or the funds of your company, or better the two together, just for you to learn the tooling and to integrate those into your workflows, whatever it is. Because we see lawyers using them, we see the medical using them... everyone is using the AI really these days. I'm not saying the chatbots. Chatbots is pretty much the topic for the plebs, the lowest class really of the internet users. And the AI agents is something that all of us have to learn at some point of time. And the faster you start, the higher the chance is that you won't be thrown overboard the moment someone comes with a better skillset. Because again, your advantage at this point of time is the domain knowledge. And the future AI users who might be better at orchestrating AI agents, they won't possess this experience, this domain knowledge of something that used to be is not that easy to acquire. You can be really brilliant at AI at this point of time, but if you don't have the experience like a decade or something under your belt, you'll still have problems. And this is still a comparative advantage, but it will die off pretty soon. So the convergence is expected. The convergence is happening already now. I'm building prototypes in Lovable myself, I'm learning Claude Code and many other things. There is no way around it, guys. If you want to stay relevant, this is the way to go. So this year, you can forget about many things, many hobbies and so on. You have to waste a lot of hours to get yourself up to speed or you're just risking your future here. You are just betting that those things won't pan out, they won't work out, and something will collapse. But from the things that I'm seeing now, the LLMs are here to stay. There is no way around it. I was wrong. I was expecting those LLMs to reach some kind of a limit, but I think that we just didn't really reach that point of time, and they are good enough at this point of time to build a lot of tools that we have. We are not that unique. We build the very same tools in different organizations that just do and happen to have the very same goals, the very same reward functions, and the very same outcomes that the business is expecting. So, if you are not on that horse, not on that train, you are royally screwed. [Watch Nate's video here.](https://www.youtube.com/watch?v=JKk77rzOL34). --- --- title: "The Human API: Your Only Defense Against AI's Corporate Takeover" url: https://ishchuk.eu/blog/ai-takeover published: 2026-01-23T09:35:00+00:00 updated: 2026-04-24T10:38:56.310035+00:00 tags: [future of work, product management, ai adaptation, technical skills, llms] --- I had a meeting last evening with my ex-chief-the man who gave me a chance in product management-and an ex-colleague. We were discussing AI in our lives as PMs, and the consensus was that AI is finally eliminating the stupid parts of our work. One of the guys mentioned he no longer dreads pointless meetings. Before, you had to sit there like a monkey, listening to corporate staff talk because that’s how they perceive work. Now, he's a bigger fan of these meetings because he can skip them. He lets the Microsoft Teams AI log the call, and then he just reads the transcript, the summary, and the to-dos. Let's be honest, a huge chunk of corporate meetings are a waste of time with no real outcome. AI helps save that time. This leads to a funny side effect. Soon, half the "participants" in a meeting will be AI notetakers like Otter.ai or the built-in Teams function, recording for people who couldn't join. You will essentially be making your presentation for AI transcription agents, whose job is to deliver something more concise, coherent, and down-to-earth to your boss. Your task is now to speak in a more understandable way for the machine. The AI overlords joining your meetings will rely on your ability to explain things clearly; otherwise, the summary will be just as stupid as the meeting itself. Your ability to communicate in clear terms will define the quality of the summaries that go to the people who matter. In a way, AI is already controlling our language. If your input is shitty, the output will be shitty, just like when a human leaves a meeting with nothing in their head-just a weird feeling of having wasted two hours with no clear next steps. Soon, you might be running a presentation with only a few people-or none at all-just a bunch of AI notetakers. You'll be presenting audio to the LLMs, which will then generate an actionable newsletter for the stakeholders. You probably won't even need to prepare the visual part. Business stakeholders who value their time will focus on those AI summaries. So, don't mess it up. Have a checklist, make your statements short and concise, and state the outcomes clearly at the beginning and end of the meeting. You have to adjust your language for the LLMs. Name the to-dos explicitly so the model can pick them up. Otherwise, people won't watch the videos, and that meeting will be another lost hour of your life. Unless, of course, that's all you do at your workplace. In that case, God help you, because you won't be there in 5-10 years. That's one point. The second one is that the price of building things is dropping like crazy-for now. VCs are sponsoring OpenAI, Anthropic, and others, but soon those tools will get more expensive. Vendor lock-ins will appear, and the cost of operations for LLM tools will rise significantly. Companies will start cutting corners, using these tools only for crucial tasks. This means smaller headcounts. If you're useless, you won't even be there to use the LLM tools that would make your work easier. I see many PMs, especially those from marketing, who have no idea about the unit economics of their company. They lack fundamentals. Their work is feature-delivery-based, and they track nonsense like story points delivered per sprint while revenue stays flat. Now, these same people can build more prototypes and deliver more features, digging themselves into a giant hole of open projects without understanding the business reality. The software space will be filled with lost effort. My ex-chief made a great point: the most important role will be the "human protein API." There will be fewer product managers, but if you are that person who can connect the dots-from the code to the balance sheet-then you're okay. You have to understand how these tools work, increase your time to market, and learn on a daily basis. You can't just stick to the Scrum guide anymore. The technical PM is no longer a joke; it's a necessity. There is no such thing as a non-technical PM anymore. You're either on that train, or you're not there at all. Designers are already moving ahead, building prototypes with tools like Galileo and Vercode AI. They are merging design with front-end work. Meanwhile, many PMs are getting stuck in the middle, using AI for PRD creation and ticket summaries, basically becoming glorified secretaries. The "human API" is needed because LLMs lack a value system; they don't have a connection to the fundamentals of your specific company context. But you can't just be a glorified secretary who manages Jira tickets-that will be 1% of your job in the future. This conversation changed my perspective. I've been a doomer about how AI is being used by the masses to generate stupid images for Instagram. But there are real applications that will increase our speed and change how we work. However, you need management that understands this-not just as a way to cut headcount, but as a way to empower the right people. When the VC funds disappear and these tools become expensive, companies will start counting their money. The useless jobs in corporate branding and the like will be gone. Only people with experience, with something in their brains, will be trusted with expensive LLM seats. It's an exciting time, but you have to understand how much time you now need to invest daily just to make yourself less replaceable. Keep learning, keep building prototypes, because if you don't act today, you will be gone in 5-10 years. * This post is a corrected version of an audio transcript; it is full of mistakes, punctuation fails and grammar outrageousness, I don't care. --- --- title: "Digital Sovereignty Breach: Escaping the Telemetry Trap" url: https://ishchuk.eu/blog/digital-sovereignty-breach-escaping-the-telemetry-trap published: 2026-01-19T11:45:00+00:00 updated: 2026-04-24T10:46:56.63936+00:00 tags: [self-hosting, slinux phone, pinephone, privacy, telemetry, device ownership, smart tech] --- I've been researching connected Linux devices as an exercise. I would like to get a dumb phone, probably running Linux, and on top of that, I want to replace my Xiaomi Mi Band with something like a PineWatch. At this point, it is just an exercise because I can't really leave the Google ecosystem, but it would be great to experiment with Nextcloud and some additional self-hosted alternatives soon enough. In any case, it is really difficult. If there is no serious money behind Linux, there is no incentive to make devices that can run it. You wouldn't get anything after you sell the device, right? Because you wouldn't get any telemetry. That's something you get out of the box with Android users. You can't have advertising like on Xiaomi, where they physically own the advertising space on your phone. At some point, you start thinking about what part of this device you actually own. It is pretty much impossible at this point to have something else. So, I will be testing out the PinePhone. I'm planning to buy a new one soon. I want to run Linux on my phone, and this second phone will be my backup, unfortunately. There is no way to run without a smartphone anymore. I'm not saying we need this for computational purposes because we have so many complicated things that we can't step out of our flats without that complex calculation machine in our pockets. Not really. We just moved so much to that external device-so many things that probably shouldn't even be there in the first place. Nowadays, it is pretty much impossible to participate in public life without having a smartphone. All the banking apps, security-related things... it is weird. I want to run with something really old-school, something like a dumb phone, for quite some time just to test it out because I see people experimenting with this. So, I will probably start with that PinePhone, or maybe I will get something cheaper like a Pocophone just to install Linux on it. I have to find a model. That's also another issue: you can buy something that has a locked bootloader. In this case, well, I'm not that proficient at those systems to be able to unlock it myself unless there is some kind of an instruction, like there was with my old Pixel 3a. So, it will be quite an enterprise. But then you realize that there are no apps. If you were to run a Linux phone, let's say with Ubuntu Touch, there are no apps. The number of apps is really, really limited. There is no review process, nothing really. The ecosystem is just not there. Obviously, you have a browser, and that's more than enough. But unfortunately, at some point, many companies focused on the app so much that the apps provide a decent experience these days, but not the website itself. Some websites have no functions or a limited set of functions. I know this from XTB, the broker company. They have a web interface that doesn't have all the functions. For example, they don't have this IKE, a special kind of account in Poland, on the web. They have it on mobile, you can see it, but on the desktop version, you won't see it. And there are many things like that. Basically, we are forced to use machines that are collecting telemetry on us, and there is no way around it. There's no way to step back, take a dumb phone, and just do something with your laptop using your VPN and blocking all third-party JavaScript. There is no way to do that anymore with mobiles. There is no way to reject the idea of owning something you don't fully own. This returns to the essay written by Louis Rossmann, or I think it was a YouTube video, where he complained that telemetry shouldn't be part of the service. You buy a physical product, be it hardware or software. It might be optional for them to take your data and use it somehow-they have to explain why-but you have to get something in exchange. And there has to be an option for hardware products as well to use your own cloud, to set up your own cloud, be it something on-premise in your house or something you're renting as a VPS so you can migrate. This has to be your data location. So next time someone tells me that car companies need security data to optimize the tech inside your car-because these days your car is also an iPhone, but on wheels-you have to understand that this data is not really yours. You don't know what's being collected, what models are being run, why, and what for. On top of that, if the company goes out of business, or your model goes out of business, or there is some cost-cutting on their end, and suddenly they just forget about your server and it is exposed to any vulnerabilities on the market-this data that shouldn't be there in the first place will be exposed without your knowledge. If, when purchasing a car, there was a programmable module that you could just connect to your laptop, like with ADB, and you could just punch in your server credentials and make this car talk to your server... Yes, there might be some kind of a gateway for a bonus, where you could connect your own server to the external server belonging to the car maker for the telemetry, in exchange for some kind of a discount, a club, some kind of benefits. Or for example, if you want to have this data stored, like the history of the vehicle, you could sell it with a packaged version of that data. Repairmen, for example, could get this information on some kind of a blockchain or something, with no adjustments in the middle. I'm not saying that's the way it should work, but this vehicle that you are buying shouldn't have more than an OBD2 port, if you wanted to, or something similar that could connect to your own server. It probably shouldn't even have a 3G connection if you don't want it to. Maybe there could be a docking station in your house or another way to pull the data to your air-gapped laptop. Obviously, these are really theoretical, stupid scenarios because at this point in the development of our tech, there is no way for us to even have something like that because these companies probably wouldn't survive. We can see the examples of Linux phones, something really specific and niche, because they don't have the money behind them to develop to the point where these tools and this software become usable and popular enough for the ecosystem to follow-the ecosystem of apps, integrations, and people physically using those devices. Everything should function similarly to the Home Assistant software. You can host it on a Raspberry Pi computer, on your own network. Unless you want remote access, you either configure this yourself to access the network via a VPN, or you can pay for the service to have this integration with their external servers to store your data. But you don't have to do that. The moment you install Home Assistant and configure it to run on your local network, you can access it via your own browser. It would be great to have that for mobile phones. Just imagine a mobile phone that only calls your local or rented VPS with your keys, with no one having access to it. And only in certain cases, with certain applications where you whitelist this kind of external connection and telemetry, would you allow it to happen. Obviously, at this point, it is a fantasy, but it is extremely frustrating because these people can see everything you do. They can build features on top of that, and you get nothing in exchange for your data that's been taken. On top of that, they own your device. We see the very same situation as with the Roomba vacuum cleaners. I have an old model at home, so the maps are not there; it was a really stupid device. But the modern machines have external connections, they store the maps of your flat, and they know when the device runs, when there are interruptions or dynamic movements. It is a tracking device. Yes, it probably can't be exploded remotely like we saw with the pager operation with Hezbollah, but these are all devices collecting telemetry you don't know about. Think about it: if you have this robot cleaner, do you really know when it calls home and what's being sent and why? Some Chinese tech comes with microphones that shouldn't be there by design. This is the creep of features. At this point, there is no way to buy a new car that has nothing inside of it, no tech, nothing additional-a really pragmatic choice where you control pretty much everything. The only way to buy a car that actually belongs to you, that no one can mess with remotely, and where you have no subscription, is to buy an old, used car where this piece either was never there or is disabled. Something before 1996, when we had our first cars with OBD2. But here we have regulations. These old cars are difficult to maintain if they are not popular models classified as classics. In Warsaw, there is a law, not yet enforced as far as I know, but the city authorities have devices to track emissions. Soon enough, they might start enforcing this, and you won't be able to enter the city even if you can't afford a better car or you don't want another telemetry-infused iPhone on wheels. You just want a car. You need an old Hilux, an old Previa, an old Jeep Cherokee XJ. But soon it will be really difficult to drive those vehicles. The very same thing is happening in Spain. Even though their economy is messed up, we keep seeing people being extremely unpragmatic, extremely stupid, and shortsighted in terms of technology and its place in our lives. I'm extremely frustrated with the European Union. In China, there is no privacy, but they have a stance and a special class of techies who actually out-earn and out-develop the West. But the Europeans are so far behind, so full of fables about the clean society and equality, which is just a dream that will never happen. On top of that, the European Union as an entity is actually dying. So soon enough, we might have those restrictions lifted, but until then, we are just slaves who own pretty much nothing, starting with your car and your flat. With a flat, you are just a subscriber; it can be taken away if you don't pay your bills. We ended up with nothing to care about and nothing to live for --- --- title: "The Content Creation Paradox: Why LLMs Need Us to Keep Writing" url: https://ishchuk.eu/blog/the-content-creation-paradox-why-llms-need-us-to-keep-writing published: 2026-01-18T11:43:00+00:00 updated: 2026-04-24T10:44:19.273836+00:00 tags: [llm content, stackoverflow] --- We've reached a point in history where LLMs are consuming everything on the web. These new products-whether it's Google, Bing, or the various AI assistants-consume content that doesn't really belong to them. They act as middlemen, delivering results without you ever accessing the original source. They eliminate the need to visit the actual page, to read the original author's work, to see other people's contributions on platforms like Stack Overflow. At some point, we have to understand that new content has to come from somewhere. This is a big mistake, in my eyes. The incentive to actually stay engaged on the web, to be geeky, to help out other people-that incentive is being demolished. And I think the people who decide to stay on the web and actually run their own websites, their own projects, their own platforms-they will win the race long-term. ## The Platform Trap Yes, crawlers love big, structured platforms. They understand Reddit, X, Substack, Medium. But these are not owned platforms. They control what you can post, whether you earn anything, whether anyone sees you. They control pretty much everything. Tomorrow, they can take away your account, block you, disable your payments, shut down entirely, or introduce yet another subscription fee. They have access to your analytics, your emails, your subscribers' emails. The main thing is just for us to understand: LLMs have to retrieve fresh data from somewhere. What happens when people are no longer encouraged to share their experiences in written form? When everyone shifts to podcasts or videos only? Yes, writing is time-consuming. Yes, it's difficult. Yes, it's really difficult to do it right. But the AI we were promised-it needs fresh data. ## The Token Collapse At this point, they've already scraped the entire useful internet. Given the volume of content being generated daily, the next iterations of models will be predominantly trained on AI-generated content. The most probable tokens, squared. The language will become increasingly standardized, predictable, homogenized. There's no way forward but to enforce-to encourage-the creation of new, original content. Content that quite often doesn't pay off, at least not directly. I'm not really discussing Substack here, but I presume the situation is similar to OnlyFans: a really small percentage of people actually make money. And if we consider money the only incentive, we're missing the point-especially for engineers. But we still have to encourage people to go the extra mile, to ignore the LLM results, to actually access websites and see the original. ## The Value of Original Sources The original might be more alive. It can have additional information posted by the author, values and context that get lost in summarization. It can be wrong too-but in that case, the person has their reputation on the line. They wouldn't waste your time posting something stupid or useless just to destroy their own reputation. With LLMs, we've forgotten what reputation actually means. ## Why I'm Starting This Blog This first post exists because I decided to have a static blog to post my articles, to host the components of my tutorials. And yes, I'll admit it: this note has been transcribed from audio because I was too lazy to write it manually. Plus, it's a markdown file-I need to understand how Hugo will render these files anyway. But here's the thing: this is still *me*, not an LLM generating tokens on my behalf. We're losing a lot by destroying the incentive for people to have their own media on the web. We've gotten stuck on corporate platforms that decide what happens to you tomorrow. At some point, we decided the convenience of unified platforms outweighs the risks-the risks of manipulation, exploitation, corruption, and generally bad products damaging the work of your life. ## The Experiment I want this static website to be indexed. I want to run an experiment to see how well LLMs index markdown files, whether my online profile will appear in answer engines, whether a static website can improve exposure by having fresh content that sits outside popular platforms. Content that exists in the penalty box might actually have better value statistically-because it's rare, because it's an outlier. I'm not sure how answer engines judge the quality of content that's not on a unified platform, that exists outside the standard structures. It's probably difficult to understand what such a website is about, whether there's a coherent content line. In any case, it's an interesting experiment. I'll start this blog and see how it goes. I won't be posting frequently, but I can use it for my tutorials-n8n, Make.com, Zapier, and many other things. I'll try to use this blog as much as possible and see how it performs in terms of Answer Engine Optimization. AEO instead of SEO. That's what they call it now. Wish me luck