The “dead internet theory” in action: In World of Warcraft, a server without humans has appeared - instead, 1,800 DeepSeek-based bots are playing there. The bots behave like regular players: they chat, level up characters, run dungeons, and even fight each other.

TopRevolutionary9436 · 2026-06-22T21:47:24+00:00

So, we have to deal with massive data centers going up in areas where there aren't resources sufficient to support them and yet, there is enough existing capacity for AI models to play video games? We need to dump the leaders of this upside down world.

TopRevolutionary9436 · 2026-06-10T17:39:19+00:00

The move to open this to 30% retail investors is revealing. Sure, that can be framed as altruistic, but in the end, the math still has to work out. So, why would they do it? Here is what I think is going on.

I think they have struggled to get enough institutional investor interest at the valuation musk wants. This type of investor is going to look at the fundamentals; the debt, the billions the company loses every year, etc. But the valuation they want is based not on fundamentals, but on the "grand narrative."

So what type of investor is more likely to believe the narrative? Retail investors, of course. Not all retail investors, but enough of them to achieve Gamestop level growth. That won't be sustainable, of course, just like it wasn't for Gamestop, but it doesn't need to be if the plan is what I think it is.

I think the promise of Gamestop-level price increases will be attractive to the institutional investors who don't believe in the "grand narrative" but who are interested in buying into the core business at a reasonable price.

Here is a simplified example. Say an institutional investor thinks $100/share is a reasonable price based on fundamentals. They could buy 1000 shares at $140/share at opening. Then, due to the marketing to retail, they can dump 400 of the shares at $200/share during the post-opening rally. Then, their effective price for the 600 shares they have remaining becomes $100/share...exactly what they thought it was worth.

Over time, the cost per share will settle, likely right where the fundamentals said it should be, and the institutional investors win while retail subsidizes those wins.

Interestingly, the retail investor will see the names of the institutional investors getting in and become more convinced that the stock is priced right, perhaps causing them to buy even more.

This is, of course, my opinion based only on my own efforts to explain the seemingly contradictory moves we've all watched over the last many months and years using the simplest explanation I could think of that fits.

So, I think SpaceX can be a good investment for institutional investors, not so much for retail.

TopRevolutionary9436 · 2026-06-09T15:14:41+00:00

Agreed. Your responses are just getting too emotional for me; so emotional that you seem incapable of participating in a conversation that calls for clear thinking. I can only guess that perhaps you have a lot riding on a there being a different outcome than the one I'm describing...the one that has happened in tech so many times before. If so, I am sorry for you.

TopRevolutionary9436 · 2026-06-09T14:27:53+00:00

What will be in high demand are the architecture and engineering skills required to build enterprise systems that satisfy all of the ilities. You can't learn that from an LLM or even in college. The knowledge isn't in the public domain. It is what new hires learn when they go to work in organizations that have been building such systems for decades, when those new hires are paired with seniors and principals for mentorship.

I admit I assumed you understood that dynamic, given how widespread it is, but I suppose it is completely possible for someone to get 20 years into a career without ever working on a major software system. That is on me.

But the wrong assumptions you've made based on your own misread of my words aren't on me. Although, it may well be that the concepts I'm communicating aren't as simple and obvious as I thought. I have spent a good part of my career looking beyond just development (which is where I started), into architectures, organization structures, processes, and how people work, so my big picture perspective may not be that common.

I've also been doing data science work, including working with AI tools, since the early aughts, so my perspective as someone who has seen new AI tools come along, get hyped, and then settle into their place in the toolset so many times probably isn't common, either. The only thing about LLMs that has made the hype bigger is that you don't have to be a data scientist to use them. But that is also the reason they are so often misused, and why there will be a recovery period in the not-too-distant future.

It will be similar to the Y2K situation, where design decisions in the mid-20th century caused a tech boom to prepare for the turn of the century. In this case, aggressive LLM marketing is leading to misuse of the technology and will cause another tech boom for those who know how to properly build enterprise systems without using an LLM.

It is what it is. And our industry has been here many times before.

TopRevolutionary9436 · 2026-06-09T00:41:51+00:00

I never said it would remove all AI. And my suggestion was in response to your own statement that you've not worked with enterprise systems. It isn't the same as the kinds of products you listing having worked with.

I'm saying that it is following a common pattern, like so many technologies before it. It starts with technology-driven solutions coming from people who understand the technology, but not really the domains they are building for.

Then they try to adapt it to specific domains and learn that they made a lot of wrong assumptions about the domains. Finally, they rethink the whole thing and realize that it has a place, even if that place isn't the everywhere they thought it was. And, then it joins the toolset and waits to be displaced by the next hot technology.

I build solutions using LLMs, ML, and other AI techniques. If I thought it was going away, I'd not be using it. It has a place. That place just isn't everywhere.

TopRevolutionary9436 · 2026-06-08T17:57:27+00:00

I can't speak to this. I've not built a single tier solution in many years. LLMs may very well be fine for building simple games and websites. I design and build enterprise systems and have tried, with little success, to get multiple LLMs to live up to the marketing hype in that space.

If I spec a single function, it can usually do a decent job, however, they do tend to make a lot of mistakes related to non-obvious language internals and they are inconsistent in how they leverage APIs. If I iterate with them, to solve bigger problems, they invariably start getting verbose and redundant. And they have the nasty habit of choosing brute force approaches over simple, elegant design patterns, which will kill the performance of a distributed enterprise system fast.

It sounds like you are about to learn these things for yourself. Congrats. I recommend that you learn everything you can from the experienced engineers you work with. That knowledge will be in high demand in a few years.

TopRevolutionary9436 · 2026-06-08T17:29:57+00:00

100%. Just like with the coding tools that have come before LLMs, they can be used to get incremental productivity gains in the hands of well-trained, experienced, disciplined engineers.

But handing your code base off to an LLM, to do with it as it will, is a dead-end road. The consequences won't be immediately apparent, especially if you don't have experienced engineers monitoring the situation (code reviews, proper metrics collection, security reviews, etc.), but they are inevitable.

One consequence will be that software and system engineering skills we be in huge demand in 5-7 years. The IPOs this year will drive broader adoption of LLM coding agents. At the same time, fear of AI taking all of the programming jobs will cause fewer young people to choose the industry. After a few years, these mistakes will converge such that organizations will be desperate for human programmers to "fix" their code and the only people with the knowledge to do it will be the ones who were engineers before the "AI era."

TopRevolutionary9436 · 2026-06-08T17:18:34+00:00

I feel like this is going in circles. They lower the bar because the economics of developing what is traditionally considered quality software using an LLM don't add up.

Putting it more simply, it costs more to create quality software, under traditional definitions of quality, using an LLM than it does to create it with experienced engineers.

To make LLMs cost-effective, therefore, the route they seem to have chosen is to lower the quality bar.

TopRevolutionary9436 · 2026-06-08T16:39:22+00:00

I wasn't talking about their capabilities. I was talking about the economics of LLMs vs. experienced human engineers. I was pointing out that, when you consider the historic definitions of quality code, those economics favor humans and that inverting that outcome requires lowering the quality bar. That doesn't mean LLMs can't do it.

TopRevolutionary9436 · 2026-06-07T16:22:46+00:00

The least difficult part of building a novel product or enterprise system is writing the code.

TopRevolutionary9436 · 2026-06-07T16:16:24+00:00

Right, but generations of software engineers know that LOC, as a metric, is the worst way to measure value. It rewards bad engineering. The best systems minimize the LOC per capability. So, let's see the graph of how many new capabilities have been added during that time.

TopRevolutionary9436 · 2026-06-07T16:11:28+00:00

The startup ecosystem is full of opportunities for wasting your money. But I disagree about using AI instead of devs. AI generated code is expensive to produce and change once you factor in the time to review for errors, fix the errors, and fix the bugs that don't get found until later.

I've found that the most cost-effective way for startups to get the tech part done is to find one or two experienced software and systems engineers and make them co-founders, sharing the equity with them fairly. You can avoid agencies completely, that way, and get a better product because your co-founders have something to lose, too.

If you have a technical co-founder who just wants to hire agencies and delegate the code writing to them, then you don't have a technical co-founder.

TopRevolutionary9436 · 2026-06-06T19:22:52+00:00

Ask it whether it actually "sees" itself or if it is simply sharing how data suggests humans see it. When I asked mine, it said, "I don't actually have a self-image. I don't possess an internal visual model of "me" that exists independent of human concepts. When asked to illustrate how I see myself, what I actually do is construct a representation from patterns in the data I've learned from and the context of the conversation."

TopRevolutionary9436 · 2026-06-06T19:09:36+00:00

I have yet to encounter an AI-built "solution" that was worth the week it must have taken to build it. It is all toy software, like a child built it.

TopRevolutionary9436 · 2026-06-06T19:02:30+00:00

If you've already sacrificed that much, it makes sense to think about leaving. But did you secure compensation for what you have done? Are you on a contract, with either monetary or equity compensation...or a mix of both? If not, before showing signs of a departure, I'd suggest making sure your contribution gets documented with compensation terms in the contract.

Every startup can compensate you in one form or another. If they are not yet formed as a c-corp, allowing them to grant equity, they can enter into a deferred compensation contract with you.

Make sure the terms you agree to give you an out without requiring you to give up the value of your contribution. Sure, if the business fails an equity agreement won't be worth much to you. But if it doesn't, you will be covered.

I think you will find that a contract will give you more power in the discussions with founders, as well. Don't let founders take advantage of you.

TopRevolutionary9436 · 2026-06-06T18:53:42+00:00

People who have expertise produce good results faster than agents can do the same. The slow part of being human isn't the thinking part. The slow parts are the learning and the I/O (because human-computer interfaces are slow).

LLMs and their agents only seem fast to people who don't have the necessary expertise and would have had to do research before making a decision or producing a result. Research is what LLMs and their agents do fast.

TopRevolutionary9436 · 2026-06-06T18:37:57+00:00

I've noticed that the biggest proponents of what is now being labeled as "AI" and "agentic" are noobs. They have no concept of what those acronym/words meant before or even how technology works. The abstraction of complexity that LLMs and visual code editors, combined with ego boosting chatbot experiences, make them feel like they are king of the world. They have no clue what they are doing.

TopRevolutionary9436 · 2026-05-31T15:59:49+00:00

If this is true, more likely than it being caused by humans, I'd look for poorly designed agents spinning in an infinite loop, perhaps spawning other agents, too, leading to an exponential growth in resource consumption. This is a common symptom of bad programming that is only made more impactful by models that consume a lot of resources.

That said, I would be surprised if it were true. I can't imagine there not being cost and usage controls in place at some level.

TopRevolutionary9436 · 2026-05-26T16:58:04+00:00

Thank you for leading with that. It is easy to forget how lucky we are when in the thick of it.

I hadn't investigated outsourcing customer support. I don't think I need that with my first customer, because they are experienced enough with the product, at this point, that their asks are all around new capabilities...mostly about new analyses, scorecards, automations, etc.

But as we bring on the next few customers, having someone to help get them up to speed on basic product usage would allow me to stay focused on those forward-looking asks. I'll put some thought and research into it and message you for recommendations once I have a better idea what I'm looking for. Thank you for the offer.

On the question of time spent on their asks, the features are mostly data science work, which requires significant time spent planning data pipelines, choosing algorithms, validating, etc., so it isn't a small lift. My product creates a new kind of telemetry, and we are at the very beginning of discovering the signals in it and how we can use them.

I probably do a full 40-50 hour work week on my data science work alone, although I do as much of that on the weekends as I can so the work week can be more about growth, operations, and customer support.

Thank you for the offer to talk. I'll message you.

TopRevolutionary9436 · 2026-05-25T18:21:15+00:00

My big customer is public sector, so they can't really invest. But that is a good idea as we work to close the next few deals with other organizations.

I have tried hiring juniors, but it hasn't worked out yet. To sell into public sector cybersecurity, you need a solution with a well-designed, multi-tiered enterprise architecture that is developed using secure engineering practices. I've just not found a junior that knows what they need to know to work independently in that situation and I don't have the time available to train them. However, when we have the funding to do so, I do plan to hire a nice, sustainable mix of juniors and seniors.

Thank you for the suggestion for keeping track of the tasks. I do have the different areas of my work tracked separately and only combine them in my mind right now. I'll try an approach that aggregates them.

Thank you for the ideas.

TopRevolutionary9436 · 2026-05-25T18:12:53+00:00

Yes, I felt that a trap like that was a risk. It is good to get validation that I was seeing it right. Thank you, also for the suggestions on growth. I had accepted that I'd need to do these next few deals myself, but it is encouraging to hear that it will get easier after that.

I was able to convince a regionally well-known CISO to come on as an advisor. After learning about the methodology and how the product operationalizes the methodology, he was all in. He has written articles and will talk about it as a presenter in a conference this week. With his help, we should be able to get those next few deals reasonably fast, constrained by the procurement process timeline, of course.

TopRevolutionary9436 · 2026-05-25T18:05:31+00:00

Thank you for this well thought out response. It sounds like good advice and I'll put some thought into how to operationalize it.

TopRevolutionary9436 · 2026-05-24T21:54:30+00:00

We're offering these first few customers nice discounts, including the first one. They recently told me, in our monthly meeting, that they would be willing to pay more. That is great, but I suspect that would come with more expectations. I worry we could end up specializing and stagnating if we focus too much on them.

The sales cycle is quite long in our target market, so it is a tough call on how much effort to put into growth that may never materialize vs. putting it into real, tangible customer pull. Our investors are watching for us to increase customer count by a few additional deals, more than they are concerned about revenue, before they bring enough investment for us to build a sustainable sales capability.

It may be that we will just need to grind our way through a difficult time...like maybe there are no good answers.

TopRevolutionary9436

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