I have a harness for my harnesses now. My Hermes manages Codex, CC or Cursor now and interact with me via Slack and PRs on GitHub.
It's nice because I can keep going from anywhere, other team members can see and interject in my Slack threads, and Hermes auto updates its skills with any adjustments that we make so we don't have to ask twice.
At this point I'd rather try to invest effort and usage in a harness that is FOSS and is actually steered by a non-profit. Goose comes to mind and to be honest I haven't tried it beyond installing and giving it a prompt or two.
Comiong to harnesses, even Pi seems like a weird choice. I mean Pi, until it's "your own customised Pi", is pretty useless and pointless. Besides they are also starting to have their own models/infra business (or is it mostly proxy like OpenCode?).
I have also given up on Herdr and came back to Tmux (and doing a bit of customisation slowly, as I need it). I wanted to try dsh but somehow couldn't brave it. Maybe once I have a good container/vm setup is ready. I know I am biased/discriminatory here, but there are things about which I'd be better safe than sorry.
As for OpenCode: I used V1 a lot and I am struggling with V2 currently. Yes, it just doesn't feel right. It's neither here, nor there. I am not a harness reviewer, so I won't be able to put that into industry accepted words and tests but it doesn't feel useful and right to me. At least Pi is completely stripped (it might be changing though) and then you can make it as you want it. Even Claude Code is better than OpenCode and that's saying something. I find Codex to be quite effective but it doesn't feel familiar. I am still in the middle of some work so I am using OpenCode v2 a lot (and then there's OpenCode Go and I won't want to play around a lot with it) but I will move away. Where? I am not sure yet.
What I feel will work for me? I guess a harness of my own! Forked something smaller/similar? I don't know. No, really! Just like I have never found the "my" notes app and journal app yet, I don't think I should use any of these harnesses if it doesn't work for me, especially now that I can kinda make one (hail LLM/vibe coding :P). It doesn't even have to be a TS/Node monsters most of these harnesses are. More I am reading about, digging deeper (haven't been quite far yet), how models and the "local setup" interact, the more I end up scratching my head – why all this drama and why all these 5 billion GitHub star "harnesses" with trillions of lines of code! Why? It doesn't make sense!
Personally I've found Zed's agent to be much superior to OpenCode. IDK why but it gets better results from the same model on the same task. Using with GLM 5.3 and DeepSeek 4.1.
You should do that. I am also summoning the motivation to start on my own. I guess the worse will be that I fail. Might as well fork sth more basic, or build on top of sth SDK/library like.
I don't know if you'll be interested, but there is an excellent book on the topic: Build an AI Agent (From Scratch), by Jungjun Hur and Younghee Song (Manning Publication).
By chapter four you have a minimal working codebase in python. Later chapters add out features like tool calling, planning, and reflection.
I am thinking about it but I think forking will miss the point. I'd rather do in a way when there is a prevalence of various types of agentic/harness SDKs for people to make their own apps (aka harnesses) from.
That’s what pi.dev exist for but I’m not touching it because like all of the other harnesses it’s built in JS and they’re all terrible when it comes to cpu and memory use. Maki is the only one I found the be the most efficient harness. It uses 1% cpu idle vs 20-30%.
A few bucks will realistically last you forever.
I also bought a DGX Spark at launch. I've learned a ton. but it's not usually my daily driver. I do run overnight tasks on it, like "read this book and write up notes on each chapter..."
In retrospect, given the dirt cheap prices of apis and or renting hardware, buying hardware for inference was likely a mistake (but not enough of a mistake to sell it now).
I think building a OpenAI compatible RAG-pipeline that also perhaps includes the anthropic sdk let's you have the best of both worlds. You can build it in a way that a local agent can escalate to a frontier model when needed and also substitute prompts data that you want to hide from being "public". For example. I think that is meant by harness here.
And with some smart feedback loops, you will see that for home assistant type tasks local AI can pretty quickly fulfil all requirements. For quick responses or voice analysis you might want to start with an external provider.
Otherwise, I think for complex home automation around 24-32gb vram are a realistic house number, but more experienced users will probably need less here.
People say that tools are called by the model. That isn't entirely correct. The caller calls the tools, the model just formulates the syntax for it. So the model part can be externalised without you needing to compromise you system fully (just to the degree the tools would allow anyway)
For me, I used Zed Agent with Codex as it has native integration with Zed's ACP so it's pretty convenient.
However, Anthropic is pickier about the harnesses you can use with Claude Code and I noticed discrepancies when using Zed's External Agent feature with Claude Code, so I just use the Claude app. It's fine.
I actually thought the article could be more explicit about that, but in fairness I think the author figured readers were familiar with the app and that it would be obvious there’s no tarot functionality.
Under international law, countries have complete and exclusive sovereignty over this airspace, just as they do over their land. They aren’t “taking someone else’s rain” because the clouds they’re seeding are effectively theirs anyway
reply