Problem
Automation systems become brittle when routing, validation, retries, and human override are scattered across prompts, background jobs, and ad hoc glue code.
R&D case study
DGM
Workflow orchestration layer in active development for managing state, decision flow, and human review inside StormIQ.
At a glance
Context
R&D
Current state
Active Build
Role
Sole architect and engineer building the orchestration layer
Screenshot placeholder
DGM
Actual screenshots are not included in this repository yet. This placeholder avoids inventing visuals while reserving space for dashboard, terminal, or demo evidence.
Solution / What I Built
DGM is being built as the orchestration backbone that will coordinate StormIQ workflows. The current direction is a graph-driven execution model that can move work through deterministic steps, agent-assisted branches, validation checks, and human review without losing system state or hiding decisions inside one opaque process.
Results
Execution model is defined for graph-driven workflow state, validation boundaries, and human review seams; implementation is in progress
Architecture
The pipeline is shown as explicit stages so the system boundary is inspectable.
Key system pieces
Graph-based execution model for multi-step workflow state.
Validation seams between agent output, business rules, and human review.
Retry-safe orchestration intended to keep workflow state inspectable.
Core constraint
State integrity: orchestration has to keep workflow state, validation, and human intervention inspectable instead of letting decisions disappear inside one agent loop
Technical Stack
PythonFastAPIWorkflow GraphsQueue-backed JobsValidation Layers
Applied Relevance
Where the pattern matters
- Workflow analysis
- Operational software design
- Prototype planning
- System architecture review
Proof Surfaces
Available artifacts are labeled directly. Missing visuals stay as placeholders until real screenshots are added.
System Walkthrough (to be added)
In progressA walkthrough will be added when the orchestration loop is stable enough to demonstrate real state transitions instead of mocked steps.
- Walkthrough to be added once graph execution can be shown with durable state transitions.
- Current state: the execution model is defined, but the public walkthrough would still be too early.
Architecture / Flow
Available nowThe architecture direction is already concrete: stateful orchestration, controlled branches, and explicit review seams.
- Graph-driven workflow state as the core execution model.
- Agent-assisted branches bounded by validation and deterministic rules.
- Human review seam built into the orchestration path rather than bolted on later.
Operational Surfaces
Available nowThe system is being designed for real operator visibility instead of hidden background automation.
- Workflow state inspection for checking where a task is and why.
- Validation checkpoints for high-risk or ambiguous transitions.
- Retry and recovery boundaries so failed steps do not corrupt the whole workflow.
Artifacts & Evidence (to be added)
In progressProof is being staged honestly: no fake screenshots, no fake outcomes, and no premature claims.
- Execution graph artifact in progress.
- State transition examples to be added when durable runs are available.
- Operator review surface screenshots to be added once the UI stabilizes.
Limitations
What this does not claim
- This page describes the current proof available for the project.
- Additional screenshots, logs, or usage artifacts should be added before making stronger claims.
Next Improvements
Reasonable next steps
- Add stronger screenshots or walkthrough artifacts.
- Document validation checks and edge cases more completely.
- Tighten public write-up as the system matures.
Related Case Studies
More portfolio context.
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Broader lead-automation direction being built on top of WeatherForge and DGM rather than treated as a finished standalone system.
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WeatherForge
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