Architecture
The control plane between intent and side effects.
Beecommit adds contract, policy, approvals, and replay between intent and side effects.
Beecommit accepts a contract, evaluates policy, coordinates agent work, pauses for approvals, and retains a replayable execution record across the full workflow.
System overview
A layered architecture for governed agent execution.
Beecommit sits between a request and the systems that carry side effects.
Open section
System overview
A layered architecture for governed agent execution.
Beecommit sits between a request and the systems that carry side effects.
Open section
System Overview
Architecture Layers
Layer 2 of 7
Contract layer
Intent becomes an explicit contract
The run begins with declared scope, expected outcome, allowed tools, and boundaries for side effects.
Objective and expected artifact
Scope, tools, and repositories
Runtime constraints and boundaries
Each layer answers a specific control question: what is allowed, what should run next, who must approve, and how the run can be inspected later.
System overview
A layered architecture for governed agent execution.
Beecommit sits between a request and the systems that carry side effects.
Beecommit sits between a request and the systems that carry side effects. It keeps contracts, policy, orchestration, approvals, and evidence attached to the workflow instead of scattering them across prompts and ad hoc scripts.
System Overview
Architecture Layers
Layer 2 of 7
Contract layer
Intent becomes an explicit contract
The run begins with declared scope, expected outcome, allowed tools, and boundaries for side effects.
Objective and expected artifact
Scope, tools, and repositories
Runtime constraints and boundaries
Each layer answers a specific control question: what is allowed, what should run next, who must approve, and how the run can be inspected later.
Lifecycle of a contract
A contract moves through explicit runtime states.
The run moves through explicit states instead of one opaque agent session.
Open section
Lifecycle of a contract
A contract moves through explicit runtime states.
The run moves through explicit states instead of one opaque agent session.
Open section
Draft
Draft
A request enters intake with intent, context, and a target outcome.
Validated
Validated
Contract shape, required inputs, and declared boundaries are checked.
Policy checked
Policy checked
Policy rules decide whether the run can proceed, must wait, or is blocked.
Scheduled
Scheduled
The orchestrator creates the managed execution plan and allocates work.
Running
Running
Agent steps and activities execute under tracked state and controlled handoffs.
Waiting approval
Waiting approval
High-risk transitions pause for a human decision before side effects continue.
Terminal states
Completed
Completed
A verified artifact and retained execution history are available for review.
Blocked
Blocked
The workflow stops when policy or governance rules reject the transition.
Failed
Failed
Execution fails with the state, evidence, and decision trail preserved.
Replayed
Replayed
An operator can re-run or inspect the workflow from retained execution context.
Primary flow
Draft
Draft
A request enters intake with intent, context, and a target outcome.
Validated
Validated
Contract shape, required inputs, and declared boundaries are checked.
Policy checked
Policy checked
Policy rules decide whether the run can proceed, must wait, or is blocked.
Scheduled
Scheduled
The orchestrator creates the managed execution plan and allocates work.
Running
Running
Agent steps and activities execute under tracked state and controlled handoffs.
Waiting approval
Waiting approval
High-risk transitions pause for a human decision before side effects continue.
Terminal states
Completed
Completed
Blocked
Blocked
Failed
Failed
Replayed
Replayed
The point of the lifecycle is to make control visible before and after side effects, not only after something has already happened.
Lifecycle of a contract
A contract moves through explicit runtime states.
The run moves through explicit states instead of one opaque agent session.
The run is not a single opaque session. Beecommit keeps state transitions visible so operators can see what was validated, what was blocked, where approval was required, and what artifact was produced.
Draft
Draft
A request enters intake with intent, context, and a target outcome.
Validated
Validated
Contract shape, required inputs, and declared boundaries are checked.
Policy checked
Policy checked
Policy rules decide whether the run can proceed, must wait, or is blocked.
Scheduled
Scheduled
The orchestrator creates the managed execution plan and allocates work.
Running
Running
Agent steps and activities execute under tracked state and controlled handoffs.
Waiting approval
Waiting approval
High-risk transitions pause for a human decision before side effects continue.
Terminal states
Completed
Completed
A verified artifact and retained execution history are available for review.
Blocked
Blocked
The workflow stops when policy or governance rules reject the transition.
Failed
Failed
Execution fails with the state, evidence, and decision trail preserved.
Replayed
Replayed
An operator can re-run or inspect the workflow from retained execution context.
Primary flow
Draft
Draft
A request enters intake with intent, context, and a target outcome.
Validated
Validated
Contract shape, required inputs, and declared boundaries are checked.
Policy checked
Policy checked
Policy rules decide whether the run can proceed, must wait, or is blocked.
Scheduled
Scheduled
The orchestrator creates the managed execution plan and allocates work.
Running
Running
Agent steps and activities execute under tracked state and controlled handoffs.
Waiting approval
Waiting approval
High-risk transitions pause for a human decision before side effects continue.
Terminal states
Completed
Completed
Blocked
Blocked
Failed
Failed
Replayed
Replayed
The point of the lifecycle is to make control visible before and after side effects, not only after something has already happened.
Control plane vs execution plane
Orchestration and side effects are deliberately separated.
Beecommit governs the workflow. Agents and external systems perform the bounded actions.
Open section
Control plane vs execution plane
Orchestration and side effects are deliberately separated.
Beecommit governs the workflow. Agents and external systems perform the bounded actions.
Open section
Beecommit control plane
Beecommit control plane
This is where contracts, policy, orchestration, approval state, and execution history live.
Handoffs and side effects
External execution plane
External execution plane
This is where agents, tools, and enterprise systems perform the work that can cause side effects.
Control plane vs execution plane
Orchestration and side effects are deliberately separated.
Beecommit governs the workflow. Agents and external systems perform the bounded actions.
Beecommit keeps control logic in one place and execution activities in another. That separation is what makes approvals, retries, replay, and audit practical instead of aspirational.
Beecommit control plane
Beecommit control plane
This is where contracts, policy, orchestration, approval state, and execution history live.
Handoffs and side effects
External execution plane
External execution plane
This is where agents, tools, and enterprise systems perform the work that can cause side effects.
Policy and governance
Governance becomes part of runtime behavior.
Policy, approvals, and blocked transitions become runtime behavior instead of after-the-fact process.
Open section
Policy and governance
Governance becomes part of runtime behavior.
Policy, approvals, and blocked transitions become runtime behavior instead of after-the-fact process.
Open section
Policy-as-code
Policy checks can be attached to risk classes, target systems, tool use, change budgets, and branch or environment protections.
Strictness levels
Low-risk documentation updates and high-risk production-adjacent actions do not need to share the same gate depth or approval policy.
Approval gates
Approval is explicit in the runtime, with waiting states, approver identity, and a recorded decision trail.
Blocked actions
When a workflow violates a boundary, Beecommit can stop it before the side effect lands in the external system.
Policy and governance
Governance becomes part of runtime behavior.
Policy, approvals, and blocked transitions become runtime behavior instead of after-the-fact process.
The control layer matters because policy is not a PDF on a shelf. Beecommit makes policy and approval requirements executable at the points where workflows can create risk.
Policy-as-code
Policy checks can be attached to risk classes, target systems, tool use, change budgets, and branch or environment protections.
Strictness levels
Low-risk documentation updates and high-risk production-adjacent actions do not need to share the same gate depth or approval policy.
Approval gates
Approval is explicit in the runtime, with waiting states, approver identity, and a recorded decision trail.
Blocked actions
When a workflow violates a boundary, Beecommit can stop it before the side effect lands in the external system.
Replay, audit, and traceability
The execution path stays inspectable after the workflow ends.
Teams can inspect what happened, why it happened, and who approved it.
Open section
Replay, audit, and traceability
The execution path stays inspectable after the workflow ends.
Teams can inspect what happened, why it happened, and who approved it.
Open section
00:00
Contract accepted
The run begins with declared intent, target systems, and scoped constraints.
00:03
Policy decision recorded
Rules classify the run, enforce boundaries, and set approval requirements.
00:08
Execution plan emitted
The orchestrator creates the graph of steps, retries, and handoffs.
00:21
Approval requested
A risky transition pauses with operator-visible context and next action.
00:27
Approval granted
Approver identity and decision reason remain attached to the run history.
00:39
Artifact produced
The workflow lands output in the target system with lineage back to the request.
Later
Replay or inspection
Operators can inspect, replay, or compare the run without losing the prior evidence chain.
00:00
Contract accepted
The run begins with declared intent, target systems, and scoped constraints.
00:03
Policy decision recorded
Rules classify the run, enforce boundaries, and set approval requirements.
00:08
Execution plan emitted
The orchestrator creates the graph of steps, retries, and handoffs.
00:21
Approval requested
A risky transition pauses with operator-visible context and next action.
00:27
Approval granted
Approver identity and decision reason remain attached to the run history.
00:39
Artifact produced
The workflow lands output in the target system with lineage back to the request.
Later
Replay or inspection
Operators can inspect, replay, or compare the run without losing the prior evidence chain.
Replay is useful because the system remembers both transitions and decisions, not just final output.
00:00
Contract accepted
The run begins with declared intent, target systems, and scoped constraints.
00:03
Policy decision recorded
Rules classify the run, enforce boundaries, and set approval requirements.
00:08
Execution plan emitted
The orchestrator creates the graph of steps, retries, and handoffs.
00:21
Approval requested
A risky transition pauses with operator-visible context and next action.
00:27
Approval granted
Approver identity and decision reason remain attached to the run history.
00:39
Artifact produced
The workflow lands output in the target system with lineage back to the request.
Later
Replay or inspection
Operators can inspect, replay, or compare the run without losing the prior evidence chain.
00:00
Contract accepted
The run begins with declared intent, target systems, and scoped constraints.
00:03
Policy decision recorded
Rules classify the run, enforce boundaries, and set approval requirements.
00:08
Execution plan emitted
The orchestrator creates the graph of steps, retries, and handoffs.
00:21
Approval requested
A risky transition pauses with operator-visible context and next action.
00:27
Approval granted
Approver identity and decision reason remain attached to the run history.
00:39
Artifact produced
The workflow lands output in the target system with lineage back to the request.
Later
Replay or inspection
Operators can inspect, replay, or compare the run without losing the prior evidence chain.
Replay is useful because the system remembers both transitions and decisions, not just final output.
Replay, audit, and traceability
The execution path stays inspectable after the workflow ends.
Teams can inspect what happened, why it happened, and who approved it.
Beecommit retains what happened, why it happened, who approved it, and which artifact or side effect followed. That gives platform and security teams a usable evidence path instead of a vague summary.
Integrations
Beecommit sits inside the engineering stack you already operate.
The control plane fits Git, CI, ticketing, and observability instead of living outside them.
Open section
Integrations
Beecommit sits inside the engineering stack you already operate.
The control plane fits Git, CI, ticketing, and observability instead of living outside them.
Open section
Source control and review
Repository integrations keep code changes reviewable and traceable rather than letting an agent mutate state in the dark.
CI/CD and delivery
Deployment-adjacent actions can remain gated and policy-aware instead of bypassing existing rollout controls.
Ticketing and planning
The contract can start from the same issue and approval context teams already use to track engineering work.
Observability and evidence export
Operational signals should feed the stack platform teams already use for runtime review and incident analysis.
Source control and review
Repository integrations keep code changes reviewable and traceable rather than letting an agent mutate state in the dark.
CI/CD and delivery
Deployment-adjacent actions can remain gated and policy-aware instead of bypassing existing rollout controls.
Beecommit
Control plane for governed execution
Contracts, policy, orchestration, approvals, replay, audit, observability.
Ticketing and planning
The contract can start from the same issue and approval context teams already use to track engineering work.
Observability and evidence export
Operational signals should feed the stack platform teams already use for runtime review and incident analysis.
Beecommit
Contracts, policy, orchestration, approvals, replay, audit, observability.
Source control and review
Repository integrations keep code changes reviewable and traceable rather than letting an agent mutate state in the dark.
CI/CD and delivery
Deployment-adjacent actions can remain gated and policy-aware instead of bypassing existing rollout controls.
Ticketing and planning
The contract can start from the same issue and approval context teams already use to track engineering work.
Observability and evidence export
Operational signals should feed the stack platform teams already use for runtime review and incident analysis.
Integrations
Beecommit sits inside the engineering stack you already operate.
The control plane fits Git, CI, ticketing, and observability instead of living outside them.
The control plane is useful only if it connects to the systems where work begins, lands, and gets reviewed. Beecommit is designed to integrate with enterprise engineering surfaces rather than replace them.
Source control and review
Repository integrations keep code changes reviewable and traceable rather than letting an agent mutate state in the dark.
CI/CD and delivery
Deployment-adjacent actions can remain gated and policy-aware instead of bypassing existing rollout controls.
Ticketing and planning
The contract can start from the same issue and approval context teams already use to track engineering work.
Observability and evidence export
Operational signals should feed the stack platform teams already use for runtime review and incident analysis.
Source control and review
Repository integrations keep code changes reviewable and traceable rather than letting an agent mutate state in the dark.
CI/CD and delivery
Deployment-adjacent actions can remain gated and policy-aware instead of bypassing existing rollout controls.
Beecommit
Control plane for governed execution
Contracts, policy, orchestration, approvals, replay, audit, observability.
Ticketing and planning
The contract can start from the same issue and approval context teams already use to track engineering work.
Observability and evidence export
Operational signals should feed the stack platform teams already use for runtime review and incident analysis.
Beecommit
Contracts, policy, orchestration, approvals, replay, audit, observability.
Source control and review
Repository integrations keep code changes reviewable and traceable rather than letting an agent mutate state in the dark.
CI/CD and delivery
Deployment-adjacent actions can remain gated and policy-aware instead of bypassing existing rollout controls.
Ticketing and planning
The contract can start from the same issue and approval context teams already use to track engineering work.
Observability and evidence export
Operational signals should feed the stack platform teams already use for runtime review and incident analysis.
Operator experience
Humans stay in control because the workflow remains legible.
Operators can see status, approvals, lineage, and replay context while the run is active or finished.
Open section
Operator experience
Humans stay in control because the workflow remains legible.
Operators can see status, approvals, lineage, and replay context while the run is active or finished.
Open section
Operator console
Workflow state stays visible while the run is live.
Live status
Running
Current state, active step, policy class, and elapsed time stay visible while the run is in progress.
Approval queue
Waiting approval
High-risk transitions are surfaced with context, affected systems, and the next possible action.
Lineage
Issue → Contract → PR
Request origin and produced artifacts stay connected so teams can browse the full path.
Replay
Ready
Operators can inspect prior decisions and decide whether replay, retry, or closure is the right action.
Operator outcomes
Operator experience
Humans stay in control because the workflow remains legible.
Operators can see status, approvals, lineage, and replay context while the run is active or finished.
Operators need more than a success or failure badge. They need visibility into current state, pending approvals, lineage, and replay context while the run is active and after it finishes.
Operator console
Workflow state stays visible while the run is live.
Live status
Running
Current state, active step, policy class, and elapsed time stay visible while the run is in progress.
Approval queue
Waiting approval
High-risk transitions are surfaced with context, affected systems, and the next possible action.
Lineage
Issue → Contract → PR
Request origin and produced artifacts stay connected so teams can browse the full path.
Replay
Ready
Operators can inspect prior decisions and decide whether replay, retry, or closure is the right action.
Operator outcomes
Deployment and enterprise readiness
Designed for controlled rollout inside real engineering organizations.
Evaluate Beecommit like platform infrastructure: scope, integrations, and governance model first.
Open section
Deployment and enterprise readiness
Designed for controlled rollout inside real engineering organizations.
Evaluate Beecommit like platform infrastructure: scope, integrations, and governance model first.
Open section
The operating model assumes multiple projects, teams, workflows, and approval paths rather than a single isolated sandbox.
Requesters, operators, and approvers are separate roles in the runtime model, even when a first pilot starts small.
Execution evidence, approvals, and artifacts remain reviewable after the run instead of disappearing into chat history.
The control plane is most useful when it fits existing Git, CI, ticketing, and observability systems.
The product is well suited to narrow pilots that prove governance on one workflow before broader rollout.
Deployment and enterprise readiness
Designed for controlled rollout inside real engineering organizations.
Evaluate Beecommit like platform infrastructure: scope, integrations, and governance model first.
Beecommit should be evaluated like platform infrastructure: how it scopes control, how it integrates with existing systems, and how it supports different teams without collapsing governance.
The operating model assumes multiple projects, teams, workflows, and approval paths rather than a single isolated sandbox.
Requesters, operators, and approvers are separate roles in the runtime model, even when a first pilot starts small.
Execution evidence, approvals, and artifacts remain reviewable after the run instead of disappearing into chat history.
The control plane is most useful when it fits existing Git, CI, ticketing, and observability systems.
The product is well suited to narrow pilots that prove governance on one workflow before broader rollout.
Next step
Review one workflow end to end before you expand the surface area.
The right starting point is a bounded workflow with real controls, real approvals, and a clear artifact path. That gives your platform and engineering teams something concrete to evaluate.