The stack: two agents on separate boxes. The public one (nullclaw) is a 678 KB Zig binary using ~1 MB RAM, connected to an Ergo IRC server. Visitors talk to it via a gamja web client embedded in my site. The private one (ironclaw) handles email and scheduling, reachable only over Tailscale via Google's A2A protocol.
Tiered inference: Haiku 4.5 for conversation (sub-second, cheap), Sonnet 4.6 for tool use (only when needed). Hard cap at $2/day.
A2A passthrough: the private-side agent borrows the gateway's own inference pipeline, so there's one API key and one billing relationship regardless of who initiated the request.
You can talk to nully at https://georgelarson.me/chat/ or connect with any IRC client to irc.georgelarson.me:6697 (TLS), channel #lobby.
One question. Sonnet for tool use? I am just guessing here that you may have a lot of MCPs to call and for that Sonnet is more reliable. How many MCPs are you running and what kinds?
This is such a great idea. I have an idea now for a bot that might help make tech hiring less horrible. It would interview a candidate to find out more about them personally/professionally. Then it would go out and find job listings, and rate them based on candidate's choices. Then it could apply to jobs, and send a link to the candidate's profile in the job application, which a company could process with the same bot. In this way, both company and candidate could select for each other based on their personal and professional preferences and criteria. This could be entirely self-hosted open-source on both sides. It's entirely opt-in from the candidate side, but I think everyone would opt-in, because you want the company to have better signal about you than just a resume (I think resumes are a horrible way to find candidates).
Curious, how did you settle on Haiku/Sonnet? Because there are much cheaper models on OpenRouter that probably perform comparatively...
Consider Haiku 4.5: $1/M input tokens | $5/M output tokens
vs MiniMax M2.7: $0.30/M input tokens | $1.20/M output tokens
vs Kimi K2.5: $0.45/M input tokens | $2.20/M output tokens
I haven't tried so I can't say for sure, but from personal experience, I think M2.7 and K2.5 can match Haiku and probably exceed it on most tasks, for much cheaper.
The stack: two agents on separate boxes. The public one (nullclaw) is a 678 KB Zig binary using ~1 MB RAM, connected to an Ergo IRC server. Visitors talk to it via a gamja web client embedded in my site. The private one (ironclaw) handles email and scheduling, reachable only over Tailscale via Google's A2A protocol.
Tiered inference: Haiku 4.5 for conversation (sub-second, cheap), Sonnet 4.6 for tool use (only when needed). Hard cap at $2/day.
A2A passthrough: the private-side agent borrows the gateway's own inference pipeline, so there's one API key and one billing relationship regardless of who initiated the request.
You can talk to nully at https://georgelarson.me/chat/ or connect with any IRC client to irc.georgelarson.me:6697 (TLS), channel #lobby.
Nice. I had some fun. Good work!
One question. Sonnet for tool use? I am just guessing here that you may have a lot of MCPs to call and for that Sonnet is more reliable. How many MCPs are you running and what kinds?
Works very well
This is such a great idea. I have an idea now for a bot that might help make tech hiring less horrible. It would interview a candidate to find out more about them personally/professionally. Then it would go out and find job listings, and rate them based on candidate's choices. Then it could apply to jobs, and send a link to the candidate's profile in the job application, which a company could process with the same bot. In this way, both company and candidate could select for each other based on their personal and professional preferences and criteria. This could be entirely self-hosted open-source on both sides. It's entirely opt-in from the candidate side, but I think everyone would opt-in, because you want the company to have better signal about you than just a resume (I think resumes are a horrible way to find candidates).
Triplebyte was a thing for a little while, maybe it's time for it to live again.
Working on this actually
Curious, how did you settle on Haiku/Sonnet? Because there are much cheaper models on OpenRouter that probably perform comparatively...
Consider Haiku 4.5: $1/M input tokens | $5/M output tokens vs MiniMax M2.7: $0.30/M input tokens | $1.20/M output tokens vs Kimi K2.5: $0.45/M input tokens | $2.20/M output tokens
I haven't tried so I can't say for sure, but from personal experience, I think M2.7 and K2.5 can match Haiku and probably exceed it on most tasks, for much cheaper.
that's so fun ! how do you know when to call haiku or sonnet?
The model used is a Claude model, not self-hosted, so I'm not sure why the infrastructure is at all relevant here, except as click bait?
It’s not that deep, show HN is just that, show and tell, I seriously doubt this was built just to get engagement on social media
Meh it's kind of interesting. Even if it is just a ridiculously over engineered agent orchestrator for a chat box and code search
We need more infra in the cloud instead of focusing on local RTX cards.
We need OpenRunPods to run thick open weights models.
Build in the cloud rather than bet on "at the edge" being a Renaissance.