Show HN: Forge – Guardrails take an 8B model from 53% to 99% on agentic tasks

Maybe I am reading it wrong but I don't think this does what it claim it does or at least how it sounds.

Basically this is a tool auto-complete that has a workflow element to it with certain steps that need to happen in certain order. In other words the order is defined in advance. Am I correct?

Basically execute step 1 first, then step 2 and finally step 3 and this is the schema for each step. That is effectively the guardrail and there is retry logic.

If it is the case, this is obviously useful but in a very specific set of problems where the solution is kind of known in advance. A workflow automation might work but this is kind of N8N where each step is LLM step.

Anyway, I might me wrong but I wanted to share a few thoughts.

Partially correct, but an important distinction to call out.

You don't have to define the workflow steps. You can just expose the set of tools to the model and let the LLM call whatever it wants in any order, and every guardrail except the prerequisite step enforcement is still there to help.

If your workflow does have step enforcement, that can also be conditional. For example like Claude code does read required before edit. You can define a conditional enforcement where the agent must have called read before edit, and even force the same file path. That doesn't mean the model has to call edit at all...

But maybe I could have been clearer in the docs on the workflow pieces.

Funny timing. I’ve been building something adjacent, though from a different angle: not primarily local-model reliability, but a control layer around agent execution, tools, routing, and operator intent. I was calling these "synthetic models", but decided yesterday "LLM middleware" is a clearer description.

Very early prototype, so I’m looking more for architectural/conceptual reactions than polish: https://wardwright.dev / https://github.com/bglusman/wardwright

The common thread I see is treating the harness around the model as first-class infrastructure. Forge seems focused on tool-call correctness and recovery; Wardwright is more about controlling what the agent is supposed to do, where work gets routed, and how the operator stays in the loop.

Curious whether you see those as complementary layers. I’m planning to try Forge and would be interested in seeing whether they fit together cleanly.

This seems pretty awesome; being able to use an 8B model for tool calling would be perfect.

Interested in using this for Home Assistant using a Mac Mini as my server. Does it run on MacOS?

How is the latency when using the proxy? I’m using Claude Haiku 4.5 for my voice assistant right now and it’s pretty fast, but if I could keep the LLM local, it’d be even better.

I've been saying for a while that given a proper harness, small local models can perform incredibly well. When you have a system that can try everything, it will eventually get it right as long as you can prevent it from getting it wrong in the meantime.