Architecture guide

Team Topologies for AI Execution

From team boundaries to bounded AI capabilities.

Team Topologies helps organizations design sociotechnical boundaries for fast flow. Stackmint makes those boundaries executable through typed Bud contracts, governed Branch workflows, scoped memory, token controls, approval gates, audit logs, deterministic replay, and marketplace distribution.

Map your first governed AI capabilityRead the semantic standard

Why AI execution needs team boundaries

Boundaries

Agentic AI fails when actions, memory, permissions, ownership, and side effects are unbounded. Stackmint makes every capability explicit before it enters production execution.

  • What it can do
  • What context it can access
  • What side effects it can create
  • Who owns it
  • How it is audited
  • How it creates value

The mapping

From team interaction modes to governed execution primitives

  • Stream-aligned teams

    Branches and Capabilities

    Branches represent executable value streams. Capabilities package outcomes for a customer, client, team, or business domain.

  • Platform teams

    Stackmint Runtime

    The runtime provides self-service execution infrastructure: memory scope, token vaults, audit logs, retries, streaming, budget controls, versioning, and rollback.

  • Enabling teams

    Templates, manifests, and governance patterns

    Stackmint can encode good patterns as templates, examples, policies, and attestations that help teams adopt agentic execution safely.

  • Complicated-subsystem teams

    Expert Buds

    Specialized logic such as compliance, pricing, eligibility, legal review, scoring, or model evaluation can be packaged behind typed Bud contracts.

  • Team APIs

    Bud contracts

    Buds expose a stable, machine-readable interface: inputs, outputs, side effects, dependencies, permissions, and version history.

  • X-as-a-Service

    Marketplace

    Buds, Branches, and Capabilities can be distributed, reused, licensed, subscribed to, or monetized by usage.

  • Facilitation

    Guided adoption

    Templates, playbooks, topology manifests, reviews, and examples help teams move from ad hoc prompts to governed execution.

  • Collaboration

    Design sprints and co-created Branches

    Teams can jointly model a workflow, then encode it as an inspectable Branch that becomes reusable infrastructure.

Bounded agency at runtime

Stackmint turns agency into an execution contract. The model can reason, but the runtime decides what is allowed, what must be reviewed, and what gets recorded.

  • Buds are stateless, typed, isolated units of logic.
  • Branches declare execution graphs, allowed actions, data scope, policy constraints, approval gates, audit guarantees, and economic attribution.
  • Memory is namespaced by org, user, and Branch.
  • Tokens are scoped and revocable.
  • Side effects require declared permissions and, where needed, human review.
  • Execution is deterministic, logged, and replayable.

Topology Manifest

Topology Manifest concept

A manifest makes topology decisions machine-readable: role, interaction mode, served streams, removed cognitive load, runtime controls, side effects, and monetization.

topology.manifest.jsonBud
{
  "asset_type": "Bud",
  "topology_role": "complicated_subsystem",
  "interaction_mode": "x_as_a_service",
  "served_streams": ["RevOps Capability", "CRM Cleanup Capability"],
  "cognitive_load_removed": [
    "lead scoring logic",
    "data normalization rules",
    "routing heuristics"
  ],
  "side_effects": [],
  "runtime_controls": {
    "memory_scope": "workspace",
    "token_scope": "none",
    "audit_required": true,
    "replayable": true
  },
  "monetization": {
    "model": "usage_based",
    "unit": "run"
  }
}

Context

Why this matters

Stackmint is not just an AI app builder. It is a protocol and runtime for turning expertise, prompts, and workflows into bounded, auditable, reusable, and monetizable execution.

Stackmint is an independent product. This page describes how Stackmint maps to sociotechnical design concepts such as Team Topologies; it does not imply endorsement, certification, or partnership with Team Topologies, Matthew Skelton, or any related organization.

In a Stackmint operating system

Each specialist works inside its team’s boundaries.

In an AI operating system built on Stackmint, each AI specialist is an agent (a Dendrite) that works inside the boundaries of its team. It runs workflows (Branches) made of typed steps (Buds), stops at approval gates where your people decide, and every run is recorded in the audit logs.

SpecialistDendriteWorkflowBranchStepBud
See the platformHow it works

Architecture guide

Map the first bounded AI capability.

Start with one workflow, one owner, one memory scope, and one approval boundary. Then turn that capability into reusable operating infrastructure.

Map your first governed AI capabilityRead the semantic standard