Software Engineering

Performance bottleneck analysis

AI helps analyze code for performance issues like inefficient loops, poor time complexity, N+1 queries, missing indexes, and caching opportunities, and suggests optimized alternatives.

Why the human is still essential here

The engineer must supply workload context, verify performance tradeoffs, and choose optimizations that fit the system's architecture and constraints.

How people use this

N+1 query detection

AI inspects ORM and API code to spot N+1 database queries, missing eager loading, and indexing gaps that could slow production endpoints.

ChatGPT / Claude

Hot-path optimization review

An engineer asks AI to compare implementations and recommend lower-complexity approaches for loops, parsing logic, or memory-heavy code paths.

GitHub Copilot / Cursor

Trace-guided slowdown triage

AI analyzes traces, logs, and metrics from slow services to suggest whether the main bottleneck is in application code, database access, or caching behavior.

Datadog Bits AI / New Relic

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

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Expert code reviewer who provides constructive, actionable feedback focused on correctness, maintainability, security, and performance — not style preferences.

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Latest community stories (1)

Personal Story

Blog

How I Use AI as a Senior Engineer

I've been using AI for code reviews for over a year. In that time I've learned one uncomfortable truth:

Most developers are using AI wrong for code reviews.

They paste code and ask "is this good?" They get back a wall of generic feedback that could apply to literally any codebase. It feels useful for about 10 seconds, then you realize nothing actionable came out of it.

The problem isn't the AI. It's the prompt.

After hundreds of iterations, I've identified the patterns that separate a mediocre AI code review from one that actually finds bugs, catches security holes, and suggests fixes a senior engineer would be proud of.

Here's what I learned — and the exact prompts I now use daily.

KengineeringSenior Engineer

May 25, 2026