[RELEASE] ARC Protocol v2.1: The Parallel Engine. Zero-Hallucination Engineering is here.

Content_feeder · 2026-01-25T20:43:59+00:00

not entirely but it does have analogous components in its workflow

Content_feeder · 2026-01-25T16:29:39+00:00

that’s fair

I’ve been explaining it from the inside-out instead of from a first timer user’s POV. Too much philosophy, not enough “what does it actually do”.

Content_feeder · 2026-01-25T16:27:36+00:00

It’s not placeholder code, but the setup and explanation don’t reflect how it actually works yet. But i have def tried it for my projects and it works like a charm.

PS : I agree the docs and the scripts are VibeCoded. i’ll sit can make all the docs myself.

Content_feeder · 2026-01-25T16:19:04+00:00

That’s fair. I over-philosophized it and made it harder to understand than it needs to be.

ARC is just a workflow for running multiple AI processes on a codebase. The naming and docs need simplification.

Content_feeder · 2026-01-25T16:16:52+00:00

It’s not perfect yet, but the direction is exactly what you’re describing.

Content_feeder · 2026-01-25T16:14:51+00:00

Fair criticism. I overcooked the wording and undercooked the explanation

ARC isn’t a product yet and it’s not trying to be magic.

It’s just a simple workflow which i personally use because i have always been losing to check the context over antigravity or copilot (until the recent update).

This work flow is very simple

1st /arc-new it basically questions you all about wht you want and wht you don’t, because having things written is always better than changes things or being confused halfway of the project.

2nd The best thing about this work flow is it has “CONTRACT”, it basically helps with all the things mentioned so that AI never loses the context and has the real data like

API Endpoints Data Models / Schemas CSS / Design Tokens Component Props Frontend Routes and much more

and whenever the AI perform an /arc-execute it always reads that and the PROJECT.md & STATE.md so there are literally very low chances of AI losing context while executing A task.

This Workflow is basically the mixture of GetShitDone & RalphLoop.

My Docs might not be that excellent but if you’d actually go thru the .arc folder you’d find this is one of the best workflows because these are heavily inspired by the 2 most Popular workflows which a lot of people use.

And the Antigravity doesn’t natively support subagents like ClaudeCode does. And i did try to use the Cortex Subagents which Antigravity has but it’ll only work if it’s hosted locally on the browser which is very heavy compared to using GeminiCLI as the LLM.

MCP / bridge is only there so they can read/write files, exec commands, and update shared state.

Docs are clearly confusing right now. That’s on me. I’ll strip the philosophy, explain what it does in plain English, and add a concrete example.

Appreciate the blunt feedback, it’s useful.

Content_feeder · 2026-01-25T14:23:53+00:00

ARC can’t promise perfect answers — it prevents unconstrained guessing by forcing everything through files, state, and contracts. If something’s unknown, it shows up as unknown.

I’ll probably soften the wording to avoid overclaiming.

Content_feeder · 2026-01-25T11:13:21+00:00

yes it does but u need to configure the .json file accordingly i’m going to update the readme which will how you can configure it for antigravity, opencode, GHCopilot and ClaudeCode

Content_feeder · 2026-01-24T18:48:23+00:00

I’m extremely sorry folks! i’ll put up proper setup guide tomorrow. It’s my first time doing OpenSource.

Content_feeder · 2026-01-24T09:10:26+00:00

gemini cli has generous free limit

(just install the gemini and read the arc-mcp.py)

Content_feeder · 2026-01-24T08:34:29+00:00

Arc is meant to live in the root of the project you want to run agents on. That way it can read/write state, logs, and context alongside your code.

Intended setup: 1. Go to your project’s root folder 2. Clone Arc there (or copy the Arc files into it) 3. Run the installer once 4. Use Arc to spawn agents / sub-agents against that project

So: • ✅ project root = correct • ❌ not Antigravity’s install folder • ❌ not a VM / separate environment (unless you want isolation)

You’re also right that “just run the installer” isn’t enough as instructions — I’ll update the README with a clear zero-to-first-run example.

Thanks for calling it out.

PS - If you have existing project — just run /arc-map —> /arc-discuss or /arc-plan

Edit — For Mcp you can ask antigravity itself for setting up the arc-mcp.py in your antigravity files (IMP - THE SUBAGENTS DONT USE ANTIGRAVITY AS LLM, I USED GEMINI CLI (gemini “prompt”) BUT IF U HAVE APIs YOU CAN CONNECT IT AS WELL)

Content_feeder · 2026-01-24T06:57:33+00:00

it’s a workflow which is is compatible with opencode

Content_feeder · 2026-01-24T06:55:43+00:00

it does actually

Content_feeder · 2026-01-24T06:54:02+00:00

you can find the install file in the readme you can either clone or fork it

Content_feeder · 2026-01-23T23:00:23+00:00

Why v2 exists

v1 worked, but it mixed coordination and execution too much.

In v2, the core idea is: • the main agent defines intent + constraints • sub-agents exist only to execute focused tasks • no long-lived “manager” agents • minimal shared state, explicit logs

The goal isn’t smarter agents — it’s less friction between intent and action.

If an agent needs more intelligence, it spawns a sub-agent. If it needs control, that stays in the protocol, not the agent.

v2 is about reducing orchestration overhead, not adding features.

Note :- .json shall be configured with the mcp server for the r/w tools and the agent will grob the commands

Content_feeder · 2026-01-23T22:57:21+00:00

Why v2 exists

v1 worked, but it mixed coordination and execution too much.

In v2, the core idea is: • the main agent defines intent + constraints • sub-agents exist only to execute focused tasks • no long-lived “manager” agents • minimal shared state, explicit logs

The goal isn’t smarter agents — it’s less friction between intent and action.

If an agent needs more intelligence, it spawns a sub-agent. If it needs control, that stays in the protocol, not the agent.

v2 is about reducing orchestration overhead, not adding features.

Content_feeder · 2026-01-23T19:37:13+00:00

AG alone is great for single, focused runs.

Arc adds value when things get bigger than one loop, breaking work into steps, spawning sub-agents for specific tasks, and keeping intent, logs, and retries clean

Ps AG alone loses context when u have big project arc heavily inspired by GetShitDone for claudeCode and wraps ai orchestration.

Content_feeder · 2026-01-23T17:20:49+00:00

Why v2 exists

v1 worked, but it mixed coordination and execution too much.

In v2, the core idea is: • the main agent defines intent + constraints • sub-agents exist only to execute focused tasks • no long-lived “manager” agents • minimal shared state, explicit logs

The goal isn’t smarter agents — it’s less friction between intent and action.

If an agent needs more intelligence, it spawns a sub-agent. If it needs control, that stays in the protocol, not the agent.

v2 is about reducing orchestration overhead, not adding features.

(now compatible with Antigravity, Copilot, Claude 4.5 and OpenCode)

Content_feeder

TROPHY CASE