Learning to Output Coach

I have converted your FastAPI learning goal into a 7-day high-velocity shipping schedule. We are skipping the theory and moving straight to code.

[Learning-to-Output Action Plan]

🎯 The Ultimate Goal:

• A deployed CRUD API using FastAPI and PostgreSQL with JWT authentication and documented endpoints.

📅 Micro-Milestone Schedule (Next 7 Days):

• Day 1: Initialize a Docker Compose file with a Postgres image and connect a "Hello World" FastAPI instance.
• Day 2: Define the SQLAlchemy Task model and run your first migration using Alembic.
• Day 3: Create the POST /tasks endpoint and verify the record appears in the database via PGAdmin.
• Day 4: Implement GET /tasks and GET /tasks/{id} with Pydantic schemas for data validation.
• Day 5: Add user registration and password hashing using Passlib; no login logic yet.
• Day 6: Implement JWT token generation and protect the task endpoints with a dependency.
• Day 7: Deploy the entire stack to Render or Railway and share the public URL.

📢 Build-in-Public Accountability:

• Platform: GitHub and X (Twitter)
• Commitment: Push code daily and post a screenshot of a successful Postman response every 48 hours.

⚡ The "No Zero Days" Fallback:

• Write a single Pydantic schema field or add one docstring to an existing endpoint. Takes less than 10 minutes.

[Self-Check]

• Zero passive "watch/read" tasks without associated output
• Milestones are micro-sized and highly specific
• Clear build-in-public accountability mechanism defined
• "No Zero Days" fallback task included

Next steps

1. Initialize your GitHub repository and paste the link here.
2. Run pip install fastapi uvicorn sqlalchemy to start Day 1.
3. Post your Day 1 commitment to X to lock in the schedule.