Durable state
Generation work is represented as records with explicit lifecycle states instead of transient in-memory prompts.
Agentic AI / workflow
Social Gen
An AI-powered social-content generation system designed as a durable workflow rather than a single prompt: work enters a queue, moves through explicit processing states, and produces structured copy and image-generation outputs.
Publication boundary Abstracted from this portfolio description. The private implementation, deployment configuration, and account details remain excluded.
- 01 · Storage boundaryDurable job state
Pending work and explicit lifecycle states.
- Consume pending work02 · Execution boundaryAsync worker
Consume pending work and run generation stages.
- Record staged results03 · Inspection boundaryOutputs or failure
Structured copy, image prompts, and inspectable intermediate results.
- Feedback: Outputs or failure → Durable job state
- Persist completion or failure for inspection / retry
Design questions: retries, observable failure states, and human inspection. Automatic publishing or specific safety checks are not claimed.
Public-summary abstraction reviewed ; not employer approval.Why it belongs in the portfolio
The useful signal is the system shape. Generative AI is treated as one stage inside an observable workflow, with persistent job state, asynchronous workers, failure states, and intermediate outputs that can be inspected or retried. That is closer to production agentic software than a thin chat wrapper.
Async execution
A worker consumes pending work and writes progress and outputs back to storage.
Staged generation
Copy, image prompts, completion, and failure are separate states, making the pipeline easier to observe and extend.