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Sequential Pipeline Flow Runner

Intent

Coordinate multi-stage architectural verification, steering compilation, and agent analysis through a deterministic linear execution pipeline that propagates shared immutable context and terminates immediately upon critical governance violations.

Context

As autonomous agent workflows expand across continuous architecture steering flows, unstructured multi-agent loops introduce non-deterministic execution paths, unbounded execution cycles, and opaque debugging boundaries. Batch and CI/CD agent-driven architectural assessment and generation pipelines require predictable step sequencing, explicit gate checks, and state accumulation.

Agentic Profile

Constrains agent behavior to strictly ordered execution stages with declared step boundaries, passing immutable context payloads between stages and suppressing uncontrolled autonomous dynamic loops during continuous architecture steering.

Forces

Balances the flexibility of multi-stage agentic synthesis against organizational requirements for determinism, resource containment, and auditable verification.

Drivers

  • Need for deterministic, reproducible execution lifecycles across continuous architecture steering flows
  • Requirement to share and enrich context across distinct pipeline stages without state corruption
  • Auditability demands for inspectable stage transitions and linear execution logs in CI/CD environments

Constraints

  • Autonomous agent workflows must not loop indefinitely or alter evaluation stage ordering dynamically
  • Failures at critical gate checks must halt downstream execution immediately to avoid wasteful compute and token costs
  • Context mutations across step boundaries must remain explicit and strictly sequenced

Tradeoffs

  • Strict linear step execution introduces cumulative latency compared to unconstrained parallel stage execution
  • Reduced runtime autonomy prevents dynamic runtime task replanning in favor of deterministic reproducibility

Solution

Implement a centralized FlowRunner orchestrator that executes declared pipeline steps sequentially against a shared execution context. Each step receives the accumulated context from preceding steps, performs its specialized task, and enriches or passes forward state. If a step encounters a critical governance or validation failure, the runner terminates execution immediately with structured diagnostic results, preventing unauthorized mutations or runaway execution.

Operationalisation

Operationalise the sequential pipeline by registering discrete step handlers in a centralized step registry, binding CLI and CI/CD invocation entrypoints directly to the runner spine, and implementing early exit handlers on governance gate failures.

Workflow Implications

  • All continuous architecture steering flows must declare steps within the central registry
  • Pipeline steps must adhere to uniform context input and output contracts
  • CI/CD workflows must evaluate exit codes and diagnostic output emitted by the pipeline runner

Automation Opportunities

  • Automated step short-circuiting when pre-condition checks fail
  • Automated trace capture and telemetry emission at step execution boundaries
  • Selective DAG execution optimization for independent evaluation branches while preserving linear verification gates

Implementation Signals

Observed in core FlowRunner orchestration component, declared step registries, and CLI entrypoint boundaries coordinating continuous architecture execution.

Evidence

Demonstrated in production-ready orchestration components and verified CLI and CI/CD execution flows.

Signals

  • FlowRunner core component in src/cas_runner/runner.py
  • declared step orchestration mapped in src/cas_runner/steps/registry.py
  • current architecture state execution boundary in CLI entrypoint

Confidence Basis

Implemented as the core FlowRunner orchestrator in src/cas_runner/runner.py, with declared step registries in src/cas_runner/steps/registry.py and entrypoint boundaries verified in CLI commands.

Consequences

Guarantees deterministic execution and context integrity at the cost of cumulative step latency.

Benefits

  • Eliminates non-deterministic agent loop deviations and infinite loops
  • Bounds compute and token expenditure through strict sequential gating
  • Guarantees auditable and reproducible execution trails across CI/CD and CLI invocations
  • Provides predictable context propagation across distinct architectural analysis phases

Risks

  • Pipeline latency accumulation across long sequential step chains
  • Potential throughput bottleneck during heavy multi-stage evaluations

Governance Implications

  • Enforces deterministic stage progression and explicit gate checks across all architectural steering workflows
  • Blocks unauthorized artifact mutation by halting pipeline flow on verification failures
  • Provides machine-readable diagnostic outputs and auditable execution state transitions

Reuse Notes

Applicable universally across batch and CI/CD agent-driven architectural assessment, steering projection generation, and multi-stage verification pipelines. Can be adopted by any agentic subsystem requiring ordered step execution, early failure termination, and shared context propagation.

Confidence

High confidence backed by mature implementation in FlowRunner, active production CI/CD flows, and complete promotion criteria satisfaction.

Level: high

Rationale

Directly validated across FlowRunner core implementation in src/cas_runner/runner.py and registered flows in src/cas_runner/steps/registry.py, meeting significance, reusability, recurrence, evidence quality, governance maturity, and strategic alignment criteria.