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Using coding assistance tools to revive projects you never were going to finish

It's OK to Use Coding Assistance Tools To Revive The Projects You Never Were Going To Finish

blog.matthewbrunelle.com

April 25, 2026

7 min read

🔥🔥🔥🔥🔥

54/100

Summary

Coding assistance tools can help developers revive unfinished personal projects. Utilizing these tools allows for more efficient coding and project completion despite previous time constraints.

Key Takeaways

  • Coding assistance tools can be effectively used to revive unfinished personal projects that may not have been completed otherwise.
  • The author tested Claude Code to implement a project that acts as a shim between YouTube Music and the OpenSubsonic API, utilizing FastAPI and other dependencies.
  • A structured setup with clear specifications and guidelines was created to guide the coding assistance tool in the implementation process.
  • The workflow involved iterative planning, prompting for specific tasks, and refining the output through follow-up questions and resource links.
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Community Sentiment

Positive

Positives

  • Using Claude for game development has transformed abandoned projects into engaging experiments, showcasing the model's ability to generate working code and design ideas effectively.
  • LLM assistance allows for rapid development of personal tools, significantly reducing the time required to bring ideas to fruition, which enhances productivity and creativity.
  • Claude's capability to create a graphical interface for an app based on user specifications demonstrates its potential to simplify complex coding tasks for non-experts.
  • The ease of building applications with LLMs encourages more individuals to pursue their creative projects, potentially leading to a surge in innovative personal applications.

Concerns

  • Some users express concerns about the reliability of LLM-generated code, citing issues like incorrect files and fragile ID generation, which can hinder development.
  • Local models are perceived as slow and weak, limiting their effectiveness in real-time applications and procedural generation tasks.

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