Design the product
Agents work from your goals and constraints to produce briefs, architecture options, and experience specs. Humans approve direction before heavy build.
Maple AI Agent Studio
How our AI agents design, build, and deliver your product—together with your team
Maple AI Agent Studio is our delivery framework: specialist agents, clear orchestration, and human checkpoints at every critical step. This page walks through the agents we operate, how they chain together, and how they make decisions you can audit and override.
Specialist agents
The agent roles we run inside Agent Studio
Each agent owns a slice of the lifecycle. They are not generic chatbots—they are specialised runners with tools, templates, and reviews wired to your project. Human experts step in for approvals, judgment calls, and client-specific nuance.
01
Discovery & alignment agent
Turns goals into a crisp product brief
Captures outcomes, constraints, and stakeholders; proposes scope slices, risks, and success metrics so engineering starts with a shared picture.
02
Architecture & technical design agent
Shapes systems that scale
Proposes services, data flows, APIs, and security boundaries; checks against your non-functional needs (latency, compliance, cost) and produces reviewable design artifacts.
03
Experience specification agent
Defines what users see and do
Translates requirements into flows, states, and component-level UI specs—aligned to your brand and accessibility expectations—so build work is unambiguous.
04
Build & integration agent
Ships incrementally
Generates and refactors application code, wires integrations, and opens PRs with tests; follows your repo conventions and tracks dependencies across workstreams.
05
Quality & reliability agent
Catches issues before users do
Runs static checks, tests, and exploratory scenarios; flags regressions, proposes fixes, and maintains traceability from requirement to verification.
06
Release & observability agent
Operates with signal
Supports deployment automation, feature flags, dashboards, and alert paths so production behaviour stays understandable and recoverable.
End-to-end delivery
How agents move your idea from definition to shipped software
Develop in iterations
Parallel streams implement slices of scope with continuous integration. Agents keep code, docs, and tickets aligned so progress stays auditable.
Deliver with confidence
Quality gates, stakeholder demos, and staged release strategies ensure what ships matches what was agreed—with observability ready from day one.
Orchestration
How agents are coordinated—not left to wander
Orchestration is what keeps many agents productive instead of chaotic. We treat your engagement as a managed graph of tasks: dependencies, inputs, outputs, and explicit review states.
1
Central coordination
A single orchestration graph sequences work: which agent runs when, what inputs each step requires, and where outputs must be validated before the next handoff.
2
Parallel workstreams
Independent tracks (for example, API work and UI polish) run concurrently when dependencies allow—then merge through shared contracts and integration checkpoints.
3
Human-in-the-loop gates
Reviews are first-class states. Escalation is automatic when confidence is low, policies trigger, or you explicitly designate an approval step. Nothing reaches production without the gates you define.
Intelligent decisions
How agents choose actions you can trust—and challenge
“Intelligence” here means structured reasoning over your context: retrieval, checks, scoring, and escalation—not opaque magic. The goal is speed with accountability.
- 1
Grounded context
Agents pull from approved sources—your brief, prior decisions, design system, and repository state—before proposing changes, reducing guesswork.
- 2
Policies & guardrails
Rules encode commercial, security, and brand constraints so proposals that violate them are blocked or routed for human judgment.
- 3
Evaluation & comparison
Multiple options can be scored against acceptance criteria, test suites, and cost or performance budgets so trade-offs are explicit.
- 4
Transparent rationale
Key outputs include why a path was chosen, what alternatives were considered, and what would change the recommendation—so your team stays in control.
Want this operating model on your product? We will map Agent Studio to your stack, compliance needs, and release culture in a discovery session.