281–290 of 408 posts
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Could you share some of your hardware details for Qwen 3.6? And are you using the dense or MoE variant?
Sure, I have a 64G MBP with an M1 Ultra. The best model for me by far has been the 35B A3B, in particular the 8Q_KL unslouth variant. The dense model works but it's much slower, and I don't really see a difference in quality with a good harness.
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The more recent Chinese models are no longer heavily limited by context size. It can easily fit in RAM on a prosumer laptop. (You can also use swap space to extemd that, since context is only written to once per inference, thus a relatively mild wear-and-tear concern.)
Claude has 1M context window for the enterprise. 128k feels like a toy in comparison.
The problem with outsourcing, as opposed to remote developers, is that it takes a really good manager and tech lead to make it work. My experience is that you have to write extremely detailed design documents and work specifications in order to get effective results. These generally have to be as detailed as most effective prompts. Once you've written specs that detailed, why do you need outsourced developers and fro…
It's funny - the problem with outsourcing is the same problem as AI and it's all a huge callback to the early 2000s. Companies are astonished by just how much money can be saved without realizing the damage to their product. Some will have extremely fastidious oversight from strong product/project leads that will become the new generation of developers and some will buy the pitch and just fail when their software bec…
I would like to submit that the high-intricacy work congregates in Protocols themselves, and we start seeing the cycles of development and all the ways to direct AIs, programs, inter-person/inter-company interactions, etc etc all as types of protocol design - and studying those rules of interaction themselves becomes the new job of a programmer (systems architecture). What used to be hard rules and deterministic programs becomes soft self-governing tendencies and probabilistic behavior that can nonetheless be managed and bounded with the right system, but it's new and weird and more akin to management or herding cats than architecture. This is still very different from what most of us were working on before AI, but it's still familiar - especially to those who worked on internet protocols, or defensive UX design around users, physical engineering systems, or team management. Less programming languages, more - control theory, flows and throttles, quality control, design theory, etc. And clearly the field is still wide open as everyone seems to be experimenting with their own take on the AI orchestrator.
I think this misses the forest for the trees. Working with ChatGPT is eerily similar to working with offshore Indian devs back in my enterprise days. Productive if guided explicitly but if let run wild there's lots of WTF moments. LLMs are likely to replace outsourced devs because your employees that know the context can use LLMs to do what offshore devs did before.
There are developers outside of your country that are talented, speak your language competently, and willing to work for less pay. There are plenty of reasons to believe that such devs will increase in numbers.
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They can if it is a way to get individuals hooked on it to then introduce it at their workplaces, who pay enterprise rates.
Right, they can do it to sell enterprise plans, but they can't offer said plans to those enterprise customers indefinitely. So if your employer wants to spend $200/month on tokens, you're going to get however many tokens $200 buys you each month, not the order of magnitude more you can get with a consumer subscription.
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> The subscription token price is 10x-40x cheaper than API pricing This is a temporary phenomenon. Expect either drastic price increases or draconian throttling or both in the coming months. These companies are operating at huge loses and have hundreds of billions in liabilities and commitments. They need to turn on the money faucet sooner than later.
Even with increased prices, AI enables velocity both in development and bugs fixing. Would companies want that? If prices are biting the company, I think companies will route all development and bugs fixing requests through few superperfomer developers with complete knowledge of the different components within the company (they will be the Queen Bees holding the company on their head). The rest of the company will be…
I think this misses the forest for the trees. Working with ChatGPT is eerily similar to working with offshore Indian devs back in my enterprise days. Productive if guided explicitly but if let run wild there's lots of WTF moments. LLMs are likely to replace outsourced devs because your employees that know the context can use LLMs to do what offshore devs did before.
"offshore Indian devs" are no slouches. They have access to the same GPT models and likely cost a tenth of the median US salary. Businesses are always looking to lower marginal cost. They will hire 1 software architect in US to write specs and 10 software developers in India to babysit 100 agents.
I work for a global corporation. We have offices in India. For the technical professionals I deal with the wage differential is maybe 30-50% and is actually quite a bit less than the cost of living difference. My personal experience is that there is a tendency for them to massively inflate their qualifications and level of experience to a point that Americans would call fraud. The only kind of people who think this is a good idea are people like Larry Fink, and I would attribute his motives to greed and malice, probably an equal parts.
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I learned today that the Anthropic "Enterprise" plan - the one big companies use because they need governance features and audit logs and all of that jazz - is billed at API token rates (plus $20/seat/month). So large companies are getting billed a lot more than those discount subscription plans.
Governance and audit trail are incredibly valuable to large enterprise organizations, especially those working in regulated spaces. Companies will pay a premium if the security/privacy/compliance issues are handled effectively.
I have really been trying to get local models to work. I have tried different harnesses, tooling, skills, prompts, etc. But when I compare claude code with anthropic models or codex with gpt 5.5, vs qwen, glm or gemma and the same harnesses, the frontier models come out massively ahead. I am at the point where I just don't see the point of the non-frontier models, they waste more time than they save.
The point is to not indenture yourself to a corporation whose motives do not align with your own.