My reading of that isn't that the harness matters so much as the overall platform environment that agents operate in and the approach taken by the team.
> Before Blitzy starts any work on code generation, the platform launches collaborative agents to deeply analyze the repository – mapping dependencies, understanding conventions, and capturing domain logic. This documentation process can take hours or days. When prompted to add a feature, refactor code or fix bugs, Blitzy replies with a highly detailed technical specification.
The same approach could be taken with any harness with a skill to perform this step first before starting work.
What exactly are you pointing out? I read the link and the linked thread and it's not clear what position is being presented.
I don't see evidence that the harness -- rather than the approach to information indexing and agent tooling -- makes much of a difference.
You can make a case "this harness bakes X in" (or in the case of pi "this harness bakes nothing in; you choose your own adventure"), but at the end of the day, skills are just markdown files and CLIs and shell scripts can be used by any harness; they are portable. CC allows override of the system prompt[0] and I would guess most harnesses have similar facilities. I don't see how the harness is going to be the bigger impact versus the configured tooling (skills, scripts, plugins).
The extraordinary claim here is that if I configured pi and CC, Codex, etc. with the same system prompt, same tools, same skills, that pi would outperform CC, Codex. That's what it means to say the harness matters. That just doesn't seem right; rather its the configuration of tools, skills, and default prompt that matters.
My point is pi-coding-agent [1] is a very well designed and implemented open source project that we all can learn from as software engineers. His blog post about his decision making [2] is also very well written.
I should've given original links instead of noisy HN threads.
You can have an opinion about a tool as a user, without ever having ability to create such a tool yourself, that's literally what every tech and auto reviewer does.
This, at best bullet talking points were fed to the prompt and given and output length restriction, it's padded to fit the space diluting the message to the point only an LLM can
Ditto, I don't see myself upgrading in the near future, the 64GB M1 Max I paid 2499 at the end of 2023 still feels like a new machine, nothing I do can slow it down. Apple kept OS updated for around 6 years in Intel times, I don't see how they can drop support for this one tbh. I'm still paying for apple care since I depend on it so much
To replace Kubernetes, you inevitably have to reinvent Kubernetes. By the time you build in canaries, blue/green deployments, and rolling updates with precise availability controls, you've just built a bespoke version of k8s. I'll take the industry standard over a homegrown orchestration tool any day.
It used be Google Deployment Manager but that's dead soon so terraform.
To roll back you tell GCE to use the previous image. It does all the rolling over for you.
Our deployment process looks like this:
- Jenkins: build the code to debian packages hosted on JFrog
- Jenkins: build a machine image with ansible and packer
- Jenkins: deploy the new image either to test or prod.
Test deployments create a new Instance Group that isn't automatically attached to any load balancer. You do that manually once you've confirmed everything has started ok.
I've moved my SaaS I'm developing to SeaweedFS, it was rather painless to do it. I should also move away from minio-go SDK to just use the generic AWS one, one day. No hard feelings from my side to MinIO team though.
I honestly feel like people are brainwashed by anthropic propaganda when it comes to claude, I think codex is just way better and kimi 2.5 (and I think glm 5 now) are perfectly fine for a claude replacement.
I would say that’s more certain than just a “probably“. I would bet that some of the ridiculous fear mongering about language models trying to escape their server, blackmail their developers, or spontaneously participating in a social network are all clandestine marketing campaigns. The technology is certainly amazing and very useful, but I don’t think any of these terminator stories were boosted by the algorithms on their own.
Was this text run through LLM before posting? I recognize that writing style honestly; or did we simply speak to machines enough to now speak like machines?
Yes. This is absolutely chatgpt-speak. I see it everywhere now. It's inescapable.
At least this appears to be largely human authored and have some substance, which is generally not the case when I see these LLM-isms.
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