Can I vibecode Lindy?

Build a deliberately narrow personal substitute for Lindy, not a full clone.
Use exactly this stack: Next.js 15 + TypeScript + PostgreSQL + BullMQ.
Primary job: Build one explicit AI assistants + automation workflow with a trigger, validated steps, retries, logs, and a manual replay button.
Start from an empty folder and create the complete working project.

Functional Requirements:
- Workflow Definition: Hardcode a specific AI automation pipeline (e.g., Email received -> LLM summarizes -> Slack message sent). Do not build a generic visual workflow builder.
- Step Validation: Enforce strict schemas for the input and output of each step in the pipeline using Zod or similar.
- Background Execution: Use BullMQ to reliably process the workflow in the background, ensuring no tasks are dropped.
- Log Dashboard: Create a minimalistic Next.js dashboard to view execution logs, payload hashes, and error traces.
- Replay: Include a manual "replay" button to restart a failed job from the point of failure.

Architecture & State:
- Make the default mode single-user and private.
- Store user data and job state locally in PostgreSQL and Redis (for BullMQ).
- Do not add analytics, telemetry, ads, or third-party accounts.
- Put every secret (API keys for LLM and integrations) in .env and provide .env.example.

UI/UX & States:
- Implement the smallest polished interface that completes the core loop end to end.
- Include clear empty (no job runs), loading, validation, success, and failure states in the dashboard.
- Add an export button to download the job logs as CSV.
- Use accessible keyboard navigation, labels, focus states, and sensible contrast.

Security & Constraints:
- Validate untrusted input and never log secrets or private file contents.
- Deliberately exclude these paid-product advantages: schema drift handling; enterprise controls; sender reputation and deliverability management; hundreds of maintained connectors.
- Do not fake integrations, network effects, proprietary data, model quality, compliance, or security claims.

Testing & DevOps:
- Write focused unit tests for the data model, step validation logic, and the most important workflow.
- Add one end-to-end smoke test that proves the core loop works.
- Create a README with setup, permissions, architecture, data location, backup, and limitations.
- Add scripts for install, development, test, build, and a production-style local run using Docker Compose.
- Run the tests and build before finishing, then fix errors rather than merely describing them.