INERTIAL LOGIC INDEPENDENT AI LAB

ATLAS </> FORGE / SOFTWARE INTELLIGENCE

Build at the speed
of understanding.

Every codebase is a record of decisions, most of them never written down. Forge reads that record, builds on it, and checks its own work before anyone has to.

Precision titanium modules aligning around illuminated connection surfaces.
ATLAS FORGE / FROM INDEPENDENT PARTS TO A COHERENT WHOLE

A command line.
A wider intelligence.

Argo 2.2 is the coding model at the center of Atlas Forge, and it lives in the terminal. It is built to hold an entire repository in view at once, with a target context of a million tokens, so it can see what a change touches before it makes one.

It is meant to work across many languages. Give it a vague request and an unfamiliar codebase and it should find its way through, work out what the original authors intended, and come back with a small change you can review.

You type a short instruction. Behind it, Argo reads, plans, writes, runs the checks, argues with itself, and reports what it did along with what it is still unsure about.

ARGO 2.2 / FORGE CLI CODER

Precision is
the whole point.

Anyone can produce a patch that looks right. Argo is built for the harder part: getting from that patch to a change you would ship.

Parameter profile
96B
Target context tokens
1M
Language-family design scope
32
Evidence gates
4

PROOFWEIGHT

Weight the evidence.

A proprietary method that lets test results, interface constraints and review comments shape what Argo writes. When the evidence changes, so should its answer.

SEMANTIC ANCHORS

Keep the system intact.

A context method that keeps the important things in view through a long edit: what a public interface promises, which odd behavior is deliberate, and what the change is supposed to achieve.

COUNTERPATH REVIEW

Doubt the first answer.

Argo is asked to build a competing solution on purpose. The second attempt often exposes an assumption the first one quietly depended on.

THE ARGO STANDARD

The patch is
only part of
the answer.

A good result shows its reasoning. What changed? What still holds? What was tested? Where does the confidence run out?

ARGO / CHANGE RECORDEXAMPLE

Make the boundary explicit.

A sample task: change how a service handles requests without breaking what its callers rely on.

INTENT

Maintain public behavior across the change.

CONSTRUCTION

Implementation scoped to the affected boundary.

CHALLENGE

Review identifies a cancellation edge case.

REVISION

Correct the behavior; refresh the affected checks.

DELIVERY

The change, the test record, and what is still open.

EVIDENCE BELONGS TO THE REVISION THAT PRODUCED IT.

HYDRA / MULTI-ENGINE CODE SYSTEM

More minds.
A higher burden of proof.

Hydra puts several engines on the same job and does not trust any of them by default. Nothing it produces is accepted until it has stood up to independent checks. It is the most demanding code system we are building, and it is built to be hard to impress.

Explore Hydra

From change request
to evidence package.

Forge hands back more than a patch. You get a short account of what changed, why, what was tested, and what is still uncertain.

A passing test run proves what the tests cover and nothing beyond that. If review turns up a problem, the work reopens. If Forge could not settle an assumption, it says so plainly instead of writing around it.

Argo, ProofWeight and the figures on this page are internal research profiles. There is no public release, no benchmark results, and no implementation details to share.