Software Engineering

AI-assisted debugging and code review

AI helps detect bugs, suggest fixes, explain root causes, and support iterative debugging during development.

Why the human is still essential here

The developer remains responsible for confirming fixes, catching hallucinations, protecting security, and ensuring the final behavior is correct.

How people use this

Stack trace diagnosis

AI reads an error message or failing log output and suggests likely root causes along with candidate fixes in the affected files.

GitHub Copilot / Cursor

Pull request review bot

AI reviews diffs in pull requests to flag logic risks, code smells, missed edge cases, and style inconsistencies before human approval.

CodeRabbit / GitHub Copilot

Failing test investigation

AI inspects broken tests and surrounding code to explain why behavior changed and recommend the smallest safe fix.

Claude Code / Sourcegraph Cody

Need Help Implementing AI in Your Organization?

I help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.

LLM Orchestration

Design and build LLM-powered products and agentic systems

AI Strategy

Go from idea to production with a clear implementation roadmap

Compliance & Safety

Build AI with human-in-the-loop in regulated environments

Connect on LinkedIn

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Latest community stories (1)

Personal Story

Medium

Coding with AI: What I Learned from AI Pair Programming

Over the past few months, I’ve been creating projects/applications with AI-powered coding assistants, and the experience has been nothing short of transformative. What started as curiosity has evolved into a fundamental shift in how I approach software development. Here’s what I learned about the capabilities, limitations, and best practices of coding with AI.

W ShamimAI solutions engineer at IBM

May 20, 2026