bg24

Follow the money, eg. investors and their connections to the Govt and media.

I think this goes to show that the newer models will be capable of. I won't be surprised if the Governments across the board come together to put a size limit on open weights model or ship them with guardrails in place. That will be really a sad day if that happens. It is difficult to imagine the state of the Internet if models of this capability are left open.

AI (llm) will be a commodity market => I am not sure it was obvious. As of last month, folks thought open weight models are lagging by 6+ months. Once K3 is taken for a deep run across many use cases, it will be clear where it stands. But yes, I agree that now that intelligence is commodity, everything changes.

I think it is deeper than that. "LLM => peak of productivity" takes way less time and effort than "Linux kernel => any productive work". Compare Dec 2025 vs July 2026 models in terms of capabilities.

Nobody can predict 5 year out. However, the country that can be ultra efficient by making their governance, health, manufacturing, military, etc AI-native will be far ahead in the game.

I think in general rest of the world needs to take notice (not saying afraid), starting with the US. It cannot be taken for granted that China's frontier labs will be a few months behind. They might be at par or exceed.

The lessons from steel, solar and EV needs to be learned by all lawmakers. You have to respect and learn from how China Government puts the system in place for complete industry takeover and they have been very good at it. The problem with AI is that democracies will be inherently slow in adopting AI, unless something changes in the system.

At minimum, every democratic Government (US, Europe, India) need to build long-term AI vision and execute that no matter which party comes to power. Additionally, be ruthless about protecting domestic labs. It can only be possible if the intelligence pricing by domestic labs per productive task is in the similar range as open-weights models. Right now, it is not the case, even if the article gives the example of Sol vs K3.

Protecting domestic labs means not bailout, but fast track to cheapest energy, fast track approval for data centers, enforce some guardrails so customers get to use the open weights models only hosted in the country by US (or Europe) businesses. Without these protections, it might be a slow death.

Correct. I used AI to refine the text. Thanks for the heads-up.

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There is no coming back. After all, open-weight is NOT open-source. It is basically free model. And you pay to host it.

The value proposition is that 100's of providers and host and sell it. 1000s of businesses (eg. Microsoft, Databricks, Palantir to small startups) can run it, finetune it and own the IP and pay only for hosting.

On the other hand, you have OpenAI and Anthropic, who need to charge at 90%+ inference margin. It is because of 1) sunk cost, 2) sky-high salaries that they paid to keep the talent. Companies like Meta screwed things up badly by paying billions of $ for chief engineers.

Chinese labs are doing a favor to the world. But I can also say with 100% certainty that if US labs were to close shops next year, Chinese labs would immediately start charging $$. In fact, I think it might happen with open weights model soon. But still these fees will be one-fifth or one-tenth per token. Also it does not come with all the guardrails.

Solution: US labs need to reduce their costs, cut the salaries across the board and compete. AI and robotics are the last hope of US to get back to industrialization and continue being the superpower.

There is a time window when it will flip. When Internet came along, we had a number of businesses that did not survive over the next years.

This time, it is different with AI. The rate of change is significant.

https://www.reuters.com/sustainability/boards-policy-regulat...

“The lawmakers said a recent analysis by a commercial company provided to the committee indicates that these devices may potentially collect and transmit extensive user data -- including sensitive personal information to servers under Chinese jurisdiction without explicit user consent.”

Relevant article - https://www.anthropic.com/news/detecting-and-preventing-dist... (3 labs generated over 16 million exchanges with Claude through approximately 24,000 fraudulent accounts). So extraction in this context is distillation.

While it is obvious to many, a modern LLM is built in roughly three stages: the foundation (pretraining) model, then SFT/supervised fine-tuning (distillation makes it easy), then the RL/RLHF stage on top (most effort-intensive). For today's reasoning models, RL/RLHF is becoming the most compute-intensive part.

Companies like Anthropic spent millions building those fine-tuning examples. A follower can shortcut that on both cost and time by distilling, and it will keep happening: every time the frontier lab climbs higher, others will find a way to shortcut the new gap. There's very little Anthropic can do beyond fraud prevention and blocking accounts that violate their terms of service.

On the policy question, I'm completely against banning Chinese models. I'm a heavy Claude Code user and I'll keep being one. But there should absolutely be price competition. China is eating the rest of the world for breakfast, lunch and dinner on manufacturing, and it did not help to ban them. Frontier pricing can't sit at 10x a capable competitor. It doesn't need to be at par either — demand is higher, and quality, trust, and fewer tokens to finish a task are worth a premium — but 4–5x is defensible.

Great point, and this is on the vendor (Anthropic) to address. Typical fraud issue.

OP is about modeling distilling the capabilities.

Space Opportunities + Robots (Tesla merger when it happens) + Software factory (Cursor).

It is a umbrella enterprise.

It is blocked for everyone.

It is not scaremongering in my opinion. Just that Government needed some time to understand and will do the same for any other company with such a model.

1/ Jailbreak => Rapid catchup of the industry leading to commoditization

2/ Jailbreak => 99% of internet infrastructure gets exposed to cyberattacks at a scale the world is simply not ready. Maybe <1% of internet users are using Fable, out of which <1% will use it for beyond intended use. Put yourself in the shoes of someone maintaining critical infrastructure, or millions of people working 7 days a week to run a small business. The world needs some time to adapt.

This will invariably be a problem in organizations where tokens, lines of code, PR count etc are the metrics - which happens to be in most places. I do not know if there are metrics or rewards for maintainable code, OR penalty for write code that breaks down and causes product incidents down the line. By then those engineers would have been promoted and moved on to better things.

Very well thought and written. Provisional employee or intern. Or having the candidate to come and do real work for a couple of days. The challenge imo is the big company culture vs startups. Do the things move at the pace in big companies where the teams have the ability to evaluate? Startups are a different beast however.

Also Mistral did just the right thing by acquiring Koyeb, to beef up their deployment at scale expertise.

Is it possible that you are narrowly sizing the opportunity? While PMF does not always mean that early pioneers will be the leaders, I think the market itself goes beyond knowledge workers and developers. Agents, robots, drones etc will all use LLM or some world model.

I am rather more concerned about competition from CHINA. With how Huawei (2000 -> 2020) crushed every other telecom company and went from nobody to the most revered leader in 20 years, and with the depth of leadership in manufacturing and work culture, if China surpasses USA in AI, all US companies lose.

Both Cloudflare and Vercel have feature parity. Flags is a feature already in Vercel. While customer-first is a thing, it is also a no-brainer to start with: we use it, Vercel has it, let us build it.

They shipped an SDK recently. https://cursor.com/blog/typescript-sdk

I have been in this situation. A major driving force is some kind of a demand from the leadership to see the KPI for the AI adoption. And this unfortunately is the easiest one to implement.

The other aspect is virality. I think by now the implementing team should know that most people do not appreciate Claud inserting itself into the commit message. It's the job of the team to feed that to the leadership.

While Anthopic has the best model and a focussed (no disturbance, lawsuits) leadership, they got a lot of enterprise access due to AWS. It is mutual no doubt, with both sides benefitting. The culture of feedback loop of AWS customers would have helped them in getting to enterprise-ready faster. Just my hypothesis.

It is a net positive to have a technologist and hardware leader at the helm. In this era, Apple can hire the right people to build software faster. but they need a strong hardware leader at the helm to differentiate themselves. In local AI, they have a unique opportunity, but limited window of time.

Think another way, these product features are easy to build in other harnesses too. And as the open source models and the other models which are much lower cost are getting better, there will be a time when it will be justified to have a harness that can work with many models and optimize your cost and efficiency.

I read all 6 posts. OP is genuine and very talented. Unfortunate how foundational issues fall through the cracks in orgs.

I think it depends on the company. In large companies, the role of PM probably won’t change that much. However, PMs who are technical and hands-on can bring significantly more value by leveraging AI tools.

There’s another path for PMs that the article and most of the comments don’t seem to mention.

Technical PMs are now in a great position to start their own companies. In the past, many were blocked or handicapped by the inability to code. With AI-assisted development, that barrier is much lower, which gives them a lot more leverage to build products themselves.

Lot of skepticism about OpenAI's survival. I am a user of both Claude (max) and Codex (plus). Some neutral points.

- Anthropic owes to AWS for their enterprise growth. Yes, their own talent as well.

- AWS investing for a purpose - solving problems with multi-agent systems - "exclusive third-party cloud distribution provider for OpenAI Frontier, which enables organizations to build, deploy, and manage teams of AI agents.". I think the multi-agent landscape will be production-ready in 2026 for solving really complex problems. AWS saw something in Codex and OpenAI's models.

- On Circular investments - if you make $100B of your revenue from ecosystem of players who spend $50B on your infra... where else would you go?

I work for another cloud provider, not AWS.

If Codex 6.0 is better than Opus 4.9, things will flip. While OpenAI has too many common enemies and trying to box them into a consumer company, they are equally enterprise focused. They need to absolutely do well with foundation model - everything else depends on that.

Same here. So I have to resort to speaking elsewhere (notes app) and copying/pasting.