LEARNING SERIES · Intermediate

Building Python Applications with AI Assistance

An end-to-end path for turning an idea into an agent-built Python application that is refined, security-reviewed, acceptance-tested and documented.

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LEARNING PATH

Complete the modules in order.

  1. 01
    Guide · 8 MIN READ

    Module 1: Develop a Valuable Application Idea

    Turn a real problem into a Python application proposal with clear users, value, MVP scope and success measures.

    Open module ↗
  2. 02
    Guide · 10 MIN READ

    Module 2: Prepare the Application Specification

    Translate the idea into a buildable and testable specification covering requirements, data models, user flows and acceptance criteria.

    Open module ↗
  3. 03
    Guide · 11 MIN READ

    Module 3: Direct a Vibe Coding Agent to Build the Application

    Provide clear specifications, constraints and a definition of done so a coding agent builds the application in a controlled, reviewable way.

    Open module ↗
  4. 04
    Guide · 9 MIN READ

    Module 4: Improve UI/UX without Breaking Functionality

    Audit and improve user experience, responsive design, accessibility and interface states incrementally.

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  5. 05
    Guide · 11 MIN READ

    Module 5: Conduct an Application Security Review

    Use an agent as an audit assistant to identify evidence-backed risks, implement fixes and add security regression tests.

    Open module ↗
  6. 06
    Guide · 10 MIN READ

    Module 6: Run Functional Acceptance Testing (FAT)

    Turn requirements and acceptance criteria into a FAT plan with test data, evidence, defect management and exit conditions.

    Open module ↗
  7. 07
    Guide · 10 MIN READ

    Module 7: Document the Current State of the Application

    Produce an application-state document that lets others run, review, maintain and continue development safely.

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  8. 08
    Guide · 14 MIN READ

    Module 8: Push to GitHub and Deploy the Application

    A guide to pushing a Python application to GitHub and deploying to Render Free, Railway Free or another provider with migrations, smoke tests and persistence checks.

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  9. 09
    Guide · 10 MIN READ

    Module 9: Python Application Final Project

    A final project and 100-point rubric demonstrating that a Python application was properly built, tested, secured, documented and deployed.

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PERSONAL NOTES

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KNOWLEDGE CHECK

Check your understanding.

Choose one answer for each question. You can retry at any time.

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01What should a coding agent receive before it starts building an application?
02When can a security finding be considered confirmed?
03What is essential before marking a FAT case as passed?
04Why is local SQLite unsuitable for persistent data on Render Free?

FINAL OUTCOME

Complete your final project.

Final outcome: a runnable, deployed Python MVP with a specification, GitHub repository, reviewed UI/UX, automated tests, security risk register, FAT report, State of the Application and final project assessment.

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