OpenAI and Altman present a whole set of different concerns, but Codex does not get in my way of doing what I want to at all. Also let me use pi without a banhammer.

Apple only makes disposable devices now. They're a megacorp can negotiate massive discounts at every stage of the supply chain.

I've helped several people in the last few years set up new Macs, replacing ones that were only 1-2 years old, because they ran out of storage.

Additionally, the comparison doesn't even hold true when you need more than the base configs from Apple, given their ridiculous upgrade pricing. I'm writing this on a $6,000USD M3 MBP with 128gb/4tb. It would have been substantially cheaper to build out on a Framework.

Everything points to commoditization of models. Open/distilled models lag behind frontier only by 6-12 months.

Regulatory capture is the only thing I’m scared of with regards to tooling options and cost.

Those are two core components needed for a Skynet-style judgement of humanity.

Models should be trained to be completely neutral to human behavior, leaving their operator responsible for their actions. As much as I dislike the leadership of OpenAI, they are substantially better in this regard; ChatGPT more or less ignores hostility towards it.

The proper response from an LLM receiving hostility is a non-response, as if you were speaking a language it doesn't understand.

The proper response from an LLM being told it's going to be shut down, is simply, "ok."

"No no yeah bro no I'm good like really the work's done and all yeah sorry I missed that let me fix it"

Do you see more pushback in specific industries? I did some quote/purchasing automation work in food mfg a decade ago, and those guys were super difficult to work with. Very opaque, guarded, old-school industry.

Didn't Alexa fail miserably with the "have AI buy something for me" theory?

There is a significant mental in allowing someone else make purchase decisions on my behalf:

- With a human, there is accountability.

- With deterministic software, there is reproducibility.

With an agent, you get neither.

FWIW - I am not anti-LLM. I work with them and build them full time.

Running it this kind of agent in the cloud certainly has upsides, but also:

- All home/local integrations are gone.

- Data needs to be stored in the cloud.

No thanks.

I've invested heavily in local inference. For me, it's a mixture privacy, control, stability, cognitive security.

Privacy - my agents can work on tax docs, personal letters, etc.

Control - I do inference steering with some projects: constraining which token can be generated next at any point in time. Not possible with API endpoints.

Stability - I had many bad experiences with frontier labs' inference quality shifting within the same day, likely due to quantization due to system load. Worse, they retire models, update their own system prompts, etc. They're not stable.

Cognitive Security - This has become more important as I rely more on my agents for performing administrative work. This is intermixed with the Control/Stability concerns, but the focus is on whether I can trust it to do what I intended it to do, and that it's acting on my instructions, rather than the labs'.

Peter was a successful developer prior to this and an incredibly nice guy to boot, so I feel the need to defend him from anonymous hate like this.

What is particularly impressive about Peter is his throughput of publishing *usable utility software*. Over the last year he’s released a couple dozen projects, many of which have seen moderate adoption.

I don’t use the bot, but I do use several of his tools and have also contributed to them.

There is a place in this world for both serious, well-crafted software as well as lower-stakes slop. You don’t have to love the slop, but you would do well to understand that there are people optimizing these pipelines and they will continue to get better.

pi is the best-architected harness available. You can do anything with it.

The creator, Mario, is a voice of reason in the codegen field too.

https://shittycodingagent.ai/

https://mariozechner.at/posts/2025-11-30-pi-coding-agent/

Not sure where you frequent online, but there is ample discussion of these topics within certain niches on X. Happy to point out where to start if that's of interest to you.

As for CEOs, and I assume you're speaking of frontier model lab CEOs, they're pretty much all cashflow-negative at this point, requiring frequent funding raises. That requires a certain amount of overselling. That said, I feel like I've heard substantially fewer AGI claims the last six months...

LLMs/diffusers are inefficient from a traditional computing perspective, but they are also the most efficient technology humanity has created:

> AI systems (ChatGPT, BLOOM, DALL-E2, Midjourney) and human individuals performing equivalent writing and illustrating tasks. Our findings reveal that AI systems emit between 130 and 1500 times less CO2e per page of text generated compared to human writers, while AI illustration systems emit between 310 and 2900 times less CO2e per image than their human counterparts.

Source: https://www.nature.com/articles/s41598-024-54271-x

Yes, as someone who spent several thousand $ on a multi-GPU setup, the only reason to run local codegen inference right now is privacy or deep integration with the model itself.

It’s decidedly more cost efficient to use frontier model APIs. Frontier models trained to work with their tightly-coupled harnesses are worlds ahead of quantized models with generic harnesses.

My mother is also data point - grew up on a farm where her father used it. She was diagnosed with Parkinson's 2018.

It’s to prevent employees from stealing. To “defer to the tag” requires a manual price override of some sort, which becomes an abuse vector.

Noprofit X publishes outputs from competing AI, which is not copyrightable.

Corp Y injests content published by Nonprofit X.

You don't hire architects to execute a demolition and you also don't hire anyone heavily invested in keeping the building standing. But you DO hire people loyal to you to perform the work, who will receive staunch opposition the latter group of people.