One Agent Can't Hold a Whole Mobile Product in Its Head

The demos all show one assistant, one repository, one clean task. Real client work is a multiplatform product with native iOS integrations, Android UI lifecycles, a shared data layer, and an API contract binding them together. Point a single general-purpose agent at that and the failure isn't that it writes bad code. It's that it writes plausible code in the wrong layer, patching a Jetpack Compose UI state when the real issue is how the shared network client in commonMain parses the JSON contract, or "fixing" a mismatch by quietly changing the side that was correct.

The problem isn't model capability. It's scope. An agent given the whole product has no reason to believe any part of it is off-limits, and no structural signal telling it where a change belongs. Everything is one flat pile of files.

So we stopped trying to make one agent smarter and started making each agent smaller.

Give every agent exactly one lane

We partition every project into lanes along the architectural boundaries that already exist: commonMain for shared business logic and Ktor networking, androidMain for Jetpack Compose, and iosMain for Apple-specific integrations. Each lane has one specialist agent that owns it and cannot write outside it. Not "shouldn't", cannot, because its tool access is scoped that way.

This buys three things immediately:

• Blast radius is bounded. An agent working on the Compose UI cannot reach into the shared database logic, so a misunderstanding stays a UI misunderstanding. You debug one lane, not a product.
• Context stays relevant. A specialist loads its lane's conventions and nothing else. It isn't spending its window parsing Swift macros when it needs to write Kotlin.
• Review is tractable. A diff that touches exactly one lane is a diff a human can actually read.

The orchestrator is deliberately ignorant

Above the specialists sits a coordinator whose only job is routing: read the request, work out which lane owns it, hand off. It doesn't know one language from another. It doesn't need to.

That ignorance is the feature. Because routing depends only on where the work belongs and never on how that lane is built, the coordinator survives every stack change underneath it. Swap the navigation library, add a WebAssembly target, replace a native sensor API, the routing logic is untouched. The layer that changes most often is the one we made the coordinator blind to.

Plan first, and let a human read the plan

The most expensive mistakes we've seen from AI agents aren't syntax errors. They're a well-executed solution to a slightly wrong problem, discovered three hours in.

So multi-step work goes through a planning step before any code is written. A dedicated planning role reads the product brief, the relevant contracts, and the code, settles on an approach, sequences the work by lane, and writes a plan file. It is advisory by construction, it can read anything and write nothing except the plan.

Then a human reads that plan before a single builder is dispatched. A bad plan approved quickly costs a day of very confident, very wrong implementation. Reviewing intent is orders of magnitude cheaper than reviewing outcome.

Contracts, not conventions, between lanes

Lanes have to talk to each other, and that's where multi-agent setups usually rot.

We treat every cross-lane interface as a contract. The change lands on the owning side first, for instance the expect declaration in commonMain. Then only a summary of the diff is handed to the consuming native lanes, which update their actual implementations to match. Never a silent one-sided change.

The same discipline covers the design system. A stack-neutral token file is the single source of truth; the UI agents then translate a token change into their own MaterialTheme code in Compose or SwiftUI views by hand. It means a design change is always a visible, reviewable event in both native lanes.

Instructions bias behavior. Only enforcement enforces.

Written instructions, "always do X", influence an agent. They do not constrain it. Under enough pressure, a model will reason its way past a guideline it read ten thousand tokens ago.

So we enforce in three layers that don't depend on the model cooperating:

• Tool access. A review agent gets read tools and nothing else. Capability, not instruction.
• Permissions. Certain actions require explicit human approval every time.
• Hooks that fire at the moment of action. Automated checks inspect the actual operation and block it before it ever reaches a pull request. A commit is refused if the branch name and commit scope don't identify which lane the work belongs to. These hooks protect the client's codebase from AI hallucinations natively.

Project handling: history that explains itself

Finished work goes through two separate review passes. First: does this match what was actually asked for, the spec, the contract, the approved plan? Second, and only after that: is this good code? Collapsing them into one review reliably produces well-written code that solves the wrong problem.

And nothing is called done without evidence. An agent asserting success is not the same as success, and the gap between those two things is where most AI-assisted work quietly goes wrong.

What it costs

Honest accounting, because this isn't free:

• There's a size threshold. On a tiny, single-screen app, this is pure overhead. The structure earns its keep when a product scales to multiple modules and complex state management, and not before.
• Routing and planning add latency. A change goes through a plan and a handoff. It is slower to start and considerably faster to finish correctly, but the first part is what you feel.

Our Approach

This disciplined, multi-agent architecture is how we build mobile products at TRIUUM. We don't let a generic AI guess at your architecture, and we don't pay the hallucination tax. By enforcing strict boundaries across our cross-platform codebases, we deliver robust, scalable applications at a pace that traditional workflows can't match.

If you want a mobile application built fast, without compromising on engineering rigor, let's talk.