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The rise of Large Language Models (LLMs) in coding has highlighted key software development practices that benefit both humans and AI. These practices include:
- Small steps: Breaking tasks into manageable chunks.
- Simpler codebases: Reducing complexity for easier comprehension.
- Fast feedback loops: Automated testing and CI/CD pipelines.
- Clear documentation: Making code more interpretable.
Ironically, the push for these practices is now stronger due to LLMs than it ever was for human collaboration alone.
You Should Know:
1. Automating Tests for Fast Feedback
Use these commands to set up automated testing in Linux:
Install pytest for Python testing pip install pytest Run all tests in a directory pytest tests/ Generate a coverage report pytest --cov=my_project tests/
2. Simplifying Codebases
Use `cloc` to measure code complexity:
Count lines of code cloc . Analyze cyclomatic complexity (Python) pip install radon radon cc my_script.py -a
3. Automating Builds & Deployments
Example GitHub Actions workflow (`.github/workflows/deploy.yml`):
name: CI/CD Pipeline on: [bash] jobs: build: runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - run: make test - run: make deploy
4. Improving Documentation
Generate docs using `Sphinx`:
pip install sphinx sphinx-quickstart docs/ cd docs && make html
What Undercode Say:
The shift toward LLM-friendly development is accelerating best practices that were long overdue. Expect:
– More AI-driven refactoring tools (autopep8, SonarQube).
– Increased adoption of self-documenting code.
– Tighter integration between AI pair programmers (GitHub Copilot) and CI/CD.
Linux/Windows Commands to Adopt Now:
Linux: Monitor system performance during builds htop Windows: Check running processes tasklist Linux: Find large files slowing deployments find / -type f -size +100M Windows: Clean temporary files del /q/f/s %TEMP%\
Prediction:
AI will soon enforce coding standards, making poorly structured codebases obsolete. Companies resisting automation will lag behind.
Expected Output:
A streamlined, AI-assisted development workflow with faster iterations and fewer human-introduced errors.
URLs for Further Learning:
References:
Reported By: Benjiweber Its – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
