What we’re working on.

We work on agentic AI: software that doesn’t just answer, but plans, uses tools, and sees a task through. These are the four problems we spend our time on.

A model that can act is a different kind of thing from a model that can answer. It touches real files, runs real commands, and spends real time and money — so the questions that matter change. Not just was it right? but what did it do, and who said it could?

We’re a product company: what we learn ships as software, not papers. When something below works well enough to trust, it shows up in our products.

01

Autonomy with oversight

How much should an agent do on its own?

The more an agent can do, the more this matters. An agent that edits files, runs commands, and reaches the internet is useful because its actions have real consequences — and those are exactly the things a person should stay in charge of.

So we work on where the line sits: permissions that treat reading differently from changing, actions that stop and ask because of what they touch, and defaults that ask when in doubt. The goal is autonomy you hand over on purpose, not autonomy you discover after the fact.

02

Long-running work

Can an agent stick with a task from start to finish?

Most AI tools live one message at a time. Real work doesn’t — it has a goal, a series of steps, half-finished states, and things that go wrong in the middle. An agent is only useful for real work if it can keep track of all of that at once.

So that’s what we build: plans that survive from one step to the next — and one session to the next — a task list the agent keeps and you can read at a glance, recovery when a step fails, and the ability to stop an agent mid-task without losing what it has already done.

03

Showing the work

Can you trust work you can’t check?

When a person does work for you, you can ask what they did and why. An agent should have to clear the same bar — otherwise you’re not trusting it, you’re taking it on faith. Most of that gap is an interface problem, and that’s how we treat it.

In practice, that means work you can actually review: file changes as diffs you read before they land, commands you see before they run, a plan that accounts for every step taken. Nothing our agents do should be invisible to the person they work for.

04

The right model for the job

Why build on just one model?

New models come out all the time, each with different strengths, costs, and weak spots. We build around that fact instead of fighting it: the models are parts of the system, not the system itself — and software built that way outlasts software tied to a single vendor.

We’re deliberately independent of every model provider. Our work is in choosing well: the model a task actually calls for, how long it should think, and the same rules — the same approvals, the same visibility — no matter which model is doing the work.

How the work ships.

None of this is a product announcement, and none of it comes with a date. Some of it will take years, and some of it will change shape along the way. What we can promise is where it’s headed: when something here is good enough to use every day, it ships. Right now, that means Argentic Code.

See where the work stands today

Working on the same problems?

We’re a small company and we read everything — if this page overlaps with what you’re building or thinking about, write to us.

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