How Hack AI-Assisted Coding Boosts Productivity Without Replacing Developers

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In the latest podcast episode, Microsoft’s Scott Hanselman and Mark Russinovich explored AI-assisted coding and vibe coding, demonstrating how these techniques enhance software development efficiency. While AI tools like GitHub Copilot and ChatGPT accelerate coding workflows, the duo argues that traditional programming skills remain irreplaceable due to AI’s limitations in complex problem-solving and creativity.

Watch the full discussion here:

EPISODE 15 – Scott & Mark Learn To… Vibe Coding (Part 2)

You Should Know: Practical AI Coding & Cyber Commands

1. AI-Assisted Coding Tools

  • GitHub Copilot Integration (VS Code):
    Install Copilot via VS Code Extensions
    code --install-extension GitHub.copilot
    
  • ChatGPT for Scripting:
    Generate a Python script via ChatGPT (example: directory scanner)
    echo "Write a Python script to list all files in /var/log" | chatgpt-cli
    

2. Automating Repetitive Tasks

  • Bash Automation:
    Auto-commit Git changes using AI-generated messages
    git add . && git commit -m "$(curl -s https://ai-commit-message-generator.com/api)"
    
  • PowerShell for Windows:
    Use AI to parse event logs (fake API for demo)
    Invoke-RestMethod -Uri "https://ai-log-analyzer.com/api" -Method Post -Body (Get-EventLog -LogName System)
    

3. Linux Cyber Commands for AI Workflows

  • Monitor AI Processes:
    List GPU-utilizing processes (for AI/ML)
    nvidia-smi | grep -E "python|jupyter"
    
  • Secure AI APIs:
    Block suspicious IPs accessing your AI endpoint
    sudo iptables -A INPUT -p tcp --dport 5000 -s 192.168.1.100 -j DROP
    

4. Debugging AI-Generated Code

  • Validate Python Scripts:
    Lint AI-written Python code
    pylint ai_generated_script.py
    
  • Test SQL Injection in AI Outputs:
    Use sqlmap to test AI-generated SQL queries
    sqlmap -u "http://test.com/api?query=$(cat ai_query.txt)" --risk=3
    

What Undercode Say

AI-assisted coding is a force multiplier, not a replacement. Key takeaways:
1. AI excels at boilerplate but struggles with architecture.
2. Security risks (e.g., AI suggesting vulnerable code) require manual review.
3. Hybrid workflows (AI + human oversight) dominate future dev pipelines.

Relevant Commands:

  • Linux:
    Audit AI tool permissions
    find /opt/ai_tools -perm -4000 -exec ls -ld {} \;
    
  • Windows:
    Log AI tool executions
    Get-WinEvent -LogName "Microsoft-Windows-PowerShell/Operational" | Where-Object {$_.Message -like "Copilot"}
    

Prediction

By 2026, 75% of devs will use AI daily, but critical systems (e.g., kernel code, cryptography) will remain human-authored.

Expected Output:

References:

Reported By: Shanselman Episode – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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