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.
Boundaries
Why AI execution needs team boundaries
Agentic AI fails when actions, memory, permissions, ownership, and side effects are unbounded. Stackmint makes every capability explicit before it enters production execution.
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 concept
A manifest makes topology decisions machine-readable: role, interaction mode, served streams, removed cognitive load, runtime controls, side effects, and monetization.
{
"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"
}
}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.
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.