Six things I realised after Mythos disappeared

I Don’t Need Smarter AI. I Need More Bandwidth.

Once I heard that Anthropic releasing Mythos 5, and it will be temporary in subscription layer only for 3 weeks, my first action was to buy one more account to squeeze as much intelligence of it as possible. Feds removed it 3 days later, the rest is history.

Can’t say that my inner world has changed, as I naturally always try to imagine the worst case scenarios, but I defo not expected it so soon. It made me reflect on my current AI usage, both personal and business one to re-evaluate all the risks.

TLDR:

• Gains I get from Claude Code and Codex are unbelievable (LLM + tight harness), no true OSS alternative yet, and I ready to pay way more for it.

• I do not need more intelligence, current level is already amazing - I need more throughput.

• LLM costs for businesses killing margins, geo political risks create so much uncertainty, turbulence and even more fragmentation ahead. Those who own harness and tune products to avoid vendor lock-in will survive.

• Like any constraint, tuning your products for cheaper and dumber models, makes it better, and you become way more creative. And it scales much better as well.

1. My productivity is now limited by LLM throughput

First of all, I don’t regret buying the additional account. Actually, I already have at least five now: one on Codex, two on Claude, and also a couple of open-source or hosted models, and I pay like $700/m for it already. But that is not really the point.

My productivity is now basically measured by how much access I have to the capability of the language model. I am not limited by ideas. I am not limited by tasks. I am limited by how many high-quality model sessions I can run before I hit a limit.

As an individual person, of course, I cannot spend millions on this like a business. But I try to squeeze as much intelligence as I can from current subsidised AI market before it finish.

So yes, I got hooked to Codex and Claude Code and my output depends on them.

2. I don’t need more intelligence. I need more bandwidth.

The funny thing is that I don’t even feel I need some dramatically smarter model right now. Of course, everyone wants a better model, and if tomorrow something twice as smart appears, I will obviously try to burn it down with tokens immediately. But honestly, the current level of intelligence from Opus and Codex 5.5 is already enough for the majority of tasks I am doing.

It already does almost everything I wanted it to do. The problem is not that I am waiting for AGI to become productive. I am productive already. The problem is that I do not have enough throughput.

I am not really limited by intelligence anymore. I am limited by bandwidth, limits, price, speed, and access. If I had cheap, almost unlimited access to the current level of models, I could do a ridiculous amount of things. Not in the future, not with some theoretical next generation, but with what already exists now.

3. We got spoiled, and everything can be cut off

The second thing is that the risk is real. Everything can be cut off at any moment.

We have become spoiled by products like Claude Code and Codex. They are good in a dangerous way, because after using them it becomes painful to go back. You start expecting the model to understand the task, keep the context, follow the direction, and behave like something close to a useful engineering partner.

Then you try open-source models… In benchmarks, some of them look close to Opus, in real life, very nuanced. They have bugs, edge cases, harness not optimised for them, hard to steer in the process.

But this is also useful. They show where your system depends too much on the best model. If your workflow only works when the model is extremely smart, maybe the workflow is not good enough.

4. Weak models are annoying, but they make your system better

Limitations always enforce creativity. Weak models are annoying because they do not forgive you. They do not magically understand what you meant. They do not compensate for bad context, unclear prompts, or lazy workflow design. But this is exactly why they are useful.

When I made experiment on weaker models, they forced me to improve my own applications. Better prompting, better context, better task boundaries, better harness. A strong model can hide a lot of bad architecture. A weaker model exposes it immediately.

Of course I would prefer Opus level models, without rate limit, and very cheap, but we live in the real world.

Good news is that many business tasks tasks do not need the strongest model. If the task is clear, constrained, and repeatable, you can often use cheaper models, simpler models, or even deterministic tools. This is where the economics start to make sense.

So one lesson is simple: prepare for weaker models. Not because they are great, but because your system should not collapse without the best one.

5. If the model can disappear, the harness can disappear too

If it is so easy to cut access to a model, then it is also easy to cut access to the harness around it. Claude Code itself, Codex, OpenCode, or anything similar can change, disappear, become expensive, become limited, or move in a direction that does not work for you.

This is why depending on someone else’s harness in serious development is a mistake, especially if this is your business.

I think I made the right decision when I started building my own harness, my own workflow engine. Not because I want to rebuild everything for fun, although apparently I do enjoy making my life more complicated. But because I want independence.

I want to own how models are called. I want to own how context is prepared. I want to own routing, evals, constraints, tools, and the workflow itself. Even open-source harnesses can become someone else’s roadmap. That is fine for experiments. For business, I do not want my core workflow to be someone else’s pricing experiment.

Building your own harness is realistic, especially if you have a lot of real material to test on.

6. For individuals, this is a subscription. For business, it is unit economics.

For individual use, I am ready to pay even more for products like Claude Code or Codex. They are so good that even if they cost twice as much, I would probably still use them. As an top tier engineer, the economics work very well for me. If it increases my output, improves my loops, and lets me keep working, it is worth it.

But business economics are completely different. You do not want to build a business where your whole margin is eaten by the LLM. That simply does not work. Price and speed become key business components. If you can optimize your application for a model that is 10 or 100 times cheaper, and it still works well, that changes the game.

Some businesses may only become possible when this pricing vs intelligence problem is solved. Plan-based pricing is dying, and API-based pricing already changing how management looks to LLM costs.

There is also the regulatory part. Mythos was one signal. Manus and Meta was another. Governments will intervene more. Companies will want privacy and protection. Serious enterprise players will not want to depend on a model, a provider, a country, or a harness they do not control.

So the conclusion for me is very simple.

Be independent from the model. Optimize your application for weaker, not-so-smart models. Stop thinking about this as open-ended magic and start thinking about workflows.

And most importantly: own the harness.