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Case study10 weeks

AI Workflow Studio

A hybrid AI automation workspace for designing prompt-driven workflows, reviewing outputs, and tightening team delivery loops.

Role

Lead web developer

Stack

Next.js, TypeScript, Node.js, OpenAI API

Problem

The team needed a way to turn one-off prompting into a repeatable workflow without making the experience feel like internal tooling.

Problem

The team needed a way to turn one-off prompting into a repeatable workflow without making the experience feel like internal tooling.

Constraints

  • Tight delivery window with evolving product direction.
  • Needed to balance experimentation speed with auditability.

Approach

Built a modular interface that separated prompt setup, execution history, and review feedback.

Used schema-validated configuration to keep workflows flexible without becoming chaotic.

Technical decisions

Leaned on server rendering for core pages and isolated client-side interactivity to editing surfaces.

Structured shared UI patterns early so new workflow types could be added without redesigning the shell.

Outcomes

Reduced content turnaround by 45% through reusable workflow templates.

Introduced review checkpoints that improved output consistency across the team.

Context

This case study is intentionally written like a strong placeholder: it shows the shape of a finished story while still leaving room for your real metrics, screenshots, and technical detail.

What I owned

  • Product-facing UI architecture
  • Workflow editor experience
  • Typed request and response boundaries
  • Release and quality guardrails

Outcome

The project became a useful internal pattern for shipping AI-assisted features more safely. It demonstrated that fast-moving experimentation still benefits from clear system boundaries, review flows, and content structure.