The advances in the Claude Code harness have been more around workflow automation rather than capability improvements, and truthfully workflows are very user-dependent, so an opinionated harness is only ever going to be "right" for a narrow segment of users, and it's going to annoy a lot of others. This is happening now, but the sub subsidy washes out a lot of the discontent.
Shouldnt there be dedicated youtubers showibg us thwir skillz?
This coding agent is minimal, and it completely changed how I used models and Claude's cli now feels like extremely slow bloat.
I'd not be surprised if you're right in that this is companies / management will prefer to "pay for a complete package" approach for a long while, but power-users should not care for the model providers.
I have like 100 lines of code to get me a tmux controls & semaphore_wait extension in the pi harness. That gave me a better orchestration scheme a month ago when I adopted it, than Claude has right now.
As far as I can tell, the more you try to train your model on your harness, the worse they get. Bitter lesson #2932.
I mean I suspect for corporate usage Microsoft already has this wrapped up with Microsoft & GitHub Co-Pilots.
The reason these LLM tools being good is they can "just do stuff." Anthropic bans third party subscription auth? I'll just have my other tool use Claude Code in tmux. If third party agents can be banned from doing stuff (some advanced always on spyware or whatever), then a large chunk of the promise of AI is dead.
Amp just announced today they are dumping IDE integration. Models seem to run better on bare-bones software like Pi, and you can add or remove stuff on the fly because the whole things open source. The software writes itself. Is Microsoft just trying to cram a whole new paradigm in to an old package? Kind of like a computer printer. It will be a big business, but it isn't the future.
At scale, the end provider ultimately has to serve the inference -- they need the hardware, data centers & the electricity to power those data centers. Someone like Microsoft can also provide a SLA and price such appropriately. I'll avoid a $200/month customer acquisition cost rant, but one user, running a bunch of sub agents, can spend a ton of money. If you don't own a business or funding source, the way state of the art LLMs are being used today is totally uneconomical (easy $200+ an hour at API prices.)
36+ months out, if they overbuild the data centers and the revenue doesn't come in like OpenAI & Anthropic are forecasting, there will be a glut of hardware. If that's the case I'd expect local model usage will scale up too and it will get more difficult for enterprise providers.
(Nothing is certain but some things have become a bit more obvious than they were 6 months ago.)
Bloated apps are a material disadvantage. If I'm in a competitive industry that slow down alone can mean failure. The only thing Claude Code has going for it now is the loss making $200 month subsidy. Is there any conceivable GUI overlay that Anthropic or OpenAI can add to make their software better than the current terminal apps? Sure, for certain edge cases, but then why isn't the user building those themselves? 24 months ago we could have said that's too hard, but that isn't the case in 2026.
Microsoft added all of this stuff in to Windows, and it's a 5 alarm fire. Stuff that used to be usable is a mess and really slow. Running linux with Claude Code, Codex, or Pi is clearly superior to having a Windows device with neither (if it wasn't possible to run these in Windows; just a hypothetical.)
From the business/enterprise perspective - there is no single most important thing, but having an environment that is reliable and predictable is high up there. Monday morning, an the Anthropic API endpoint is down, uh oh! In the longer term, businesses will really want to control both the model and the software that interfaces with it.
If the end game is just the same as talking to the Star Trek computer, and competitors are narrowing gaps rather than widening them (e.g. Anthropic and OpenAI releases models minutes from each other now, Chinese frontier models getting closer in capability not further), then it is really hard to see how either company achieves a vertical lock down.
We could actually move down the stack, and then the real problem for OpenAI and Anthropic is nVidia. 2030, the data center expansion is bust, nVidia starts selling all of these cards to consumers directly and has a huge financial incentive to make sure the performant local models exist. Everyone in the semiconductor supply chain below nvidia only cares about keeping sales going, so it stops with them.
Maybe nvidia is the real winner?
Also is it just me or does it now feel like hn comments are just talking to a future LLM?
When I first tried, the created code was garbage. Now that I slowly built my memory, several thousands of manually written examples and guidance, it can generate quite reliably, when it doesn’t need literally anything outside of those…
That being said, most of the vibe coded codebases (in reality every single one which I saw) use garbage memory, and consequently have garbage output.
So the same thing is terrible and great at the same time. People who give time, and people who is fine producing garbage (huge majority) says it’s great. People who just tried it out, and don’t have the luxury to potentially waste days and weeks, say that it’s bad. All of these are true at once.
I think Github Co-Pilot is most annoying from what I've tried... it's great for finishing off a task that's half done where the structure is laid out, as long as you put blinders keeping it focused on it. OpenAI and Google's options seem to get things mostly right, but do some really goofy wrong things from my own experiences.
They all seem to have trouble using state of the art and current libraries by default, even when you explicitly request them.
Is the problem you observed true regardless of the model you picked?
If the default option isn't at least arguably the best option I can't really speak to that. I would suggest that maybe metrics on a given set of technologies be done and that based on the project in use, that it should choose the best option dynamically by default. Such as C#+MS-SQL vs Node+Postgres vs Python+Matlab+DuckDB.