We make AI agents stick inside your company

• Nobody knows who uses which tool, or how much. It was never approved, and everyone is already using it.
• Agent-authored changes either merge without review, or nobody dares put them near production. There is no middle.
• The output survives, the reasoning does not. When someone leaves, the next person starts from scratch.
• You learn which team spent what on AI when the invoice arrives. There is nothing to budget from.
• Nobody inside the org can assemble what a security review asks for, so the review never even starts.

Usually it is. Claude Code and Codex are good tools, and for one task at a time they are plenty. We use them the same way.

It breaks when one becomes two, and two becomes five. Past that point, keeping track of the agents takes longer than running them. Here is where it actually breaks.

You can only watch one at a time

More terminal windows means more agents. But from the third one on, you no longer know which window finished what. You did not add capacity, you added things to miss.

MARBLO

Everything lands on one screen. You read state, not a chat log.

They step on each other's files

Two agents in one repository overwrite each other. You end up running them one after another anyway, which defeats the point of parallel.

MARBLO

Each ticket gets its own git worktree. They physically cannot touch each other's files.

Nothing stops a merge

Review depends on someone remembering. When it gets busy, it gets skipped. A written policy is a document, not a flow.

MARBLO

Work has to pass REVIEW before it merges. The flow enforces the policy, not a document.

You cannot pick a model per task

Claude Code is Claude. Even when Codex fits this ticket and Grok fits that one, changing the model means changing the tool. You end up tied to one vendor.

MARBLO

Assign a model per ticket. One vendor wobbling does not stop the work.

You find out the cost from the invoice

There is no way to see who spent how many tokens on what, as it happens. You cannot budget, and you cannot catch an overrun.

MARBLO

Usage and spend land in the workspace by vendor, model, and agent — down to which model each agent actually ran.

The reasoning disappears

The code survives; why it was done that way leaves with the chat window. Months later you re-derive it from scratch.

MARBLO

An append-only record per ticket. You can retrace which agent changed what, and on what grounds.

Agents are cheap to start. Knowing what the fleet is doing is the hard part.

Marblo official repository

Isolated execution

Each agent runs in its own git worktree. Parallel work never overwrites another agent's changes, and a conflict surfaces as a conflict instead of being quietly flattened.

Approval gate

Finished work moves to REVIEW, and nothing merges until a person approves. Not "we agreed to review" — there is no next step without it.

Audit log

Who opened what, and when a role changed, is recorded per ticket. The evidence a security review asks for accumulates without anyone assembling it.

Cost tracking

Subscription and AI usage are separate, and consumption shows up per model and per agent. You budget from real numbers.

Split one goal into branches, hand each branch to a model with different strengths, and have a person merge the result. That way of working has nothing to do with code.

Marketing execution, data analysis, GA4 implementation, planning documents — all run on the same structure. Which means an organization without an engineering team can use it too.

1. 01

   Fit assessment

   We separate what can move to agents from what should not. A half-day workshop and a report.

2. 02

   Team training

   Directing agents is a different skill from coding. Task decomposition, approval criteria, failure handling — practiced, not lectured.

3. 03

   PoC

   Pick one workflow and actually run it. If it does not pay off, stopping here is correct. That judgment is part of the assessment.

4. 04

   Team rollout

   Internal manual, approval criteria, operating rules — written down so it survives people leaving.

5. 05

   Company-wide

   On-prem, SSO, audit logs, SLA. What security and procurement will ask for.

The biggest worry in adopting a tool is not performance, it is whether you can leave. Pile your process inside one tool and you cannot walk away when it gets expensive or changes direction.

173 skills, MCP servers, agents, workflows, and knowledge packs are published MIT in the official repository. They are plain files that run in the CLI you already have, so the assets remain even if you stop using the app. That includes 22 built for Korean work — DART filings, real-estate prices, case-law search, HWP editing.

Companies

If you are evaluating adoption, start with a fit assessment. The first 30 minutes are free.

Individual developers

If you want to try it first, start with the Marblo Founders beta.

Resellers and partners

If you already pitch AI agents to your clients, there is a way to work together.