AI Pair Programming: Hype, Help, or Just Another Noisy Tool?
Maryanne- May 26
- 3 min read
If you’ve been anywhere near any software engineering social platform in the last year, you’ve probably read statements something like this:
"I just wrote a whole unit test suite in 30 seconds using AI."
"It suggested the wrong regex again. I'm not impressed."
"My AI assistant is a people-pleaser. It happily generates code that compiles but doesn’t actually work."
Welcome to the age of AI pair programming.
Tools like Copilot, CodeWhisperer, and many more vendors are stuffing AI into your IDEs and they are here to help. Allegedly. The idea is simple: like a human pair programmer, they sit beside you (virtually), watch you code, and offer up suggestions, completions, and sometimes full-on implementations.
But unlike your actual human teammate, they don’t drink all the coffee or judge your tab-vs-space preferences.
So is AI pair programming helpful, or just one more tool with good marketing and mediocre follow-through?
Let’s break it down.
The Hype: “AI is your new coding buddy!”
The pitch sounds great: a tireless assistant who’s read the entirety of Stack Overflow, GitHub, and the documentation you never had time for. It knows obscure API calls. It autocompletes boilerplate. It finishes your sentences (and your for loops).
User feedback tends to cluster in two camps:
Productivity Unicorns – Engineers claiming to ship twice as fast.
Skeptical Realists – Engineers cleaning up AI messes and explaining to their interns why the code looked fine but broke staging.
The truth, predictably, is in the middle.
Where AI Pair Programming Really Helps
Scaffolding and Boilerplate: Writing repetitive CRUD controllers? Need to stub out a bunch of similar classes? AI is great at cloning patterns and saving you from carpal tunnel. This is where it shines.
Remembering That One API Call: Can’t recall if it’s HttpClient.SendAsync() or SendRequestAsync()? AI can usually surface it faster than a Google search.
Unit Test Generation: Especially in C#, AI tools can get you to 80% of a unit test quickly. You still have to assert the right things but setup and mocks? Done in seconds.
Code Comments and Summaries: Not all devs love writing comments. AI can generate summaries for methods or flag a likely side effect you should document. Is it always right? No. But it gets you out of the blank page zone.
Where It can fall Flat
Context is King—and AI Doesn’t Always Have It: Your assistant doesn’t understand the architectural decisions your team made last sprint. It doesn't know about that fragile dependency you’re avoiding. Without context, it guesses. And sometimes those guesses are bad.
It Lies. Confidently: AI will generate plausible, syntactically perfect nonsense. Like a junior dev who’s really, really eager to help, it wants to give you something even when it doesn’t know the answer.
Security and Compliance Risks: Copy-pasting code from Stack Overflow into your codebase has always been risky. Now the AI is doing it for you. If you’re in a regulated industry or dealing with licensing-sensitive code, you have to pay attention.
The False Sense of Progress: When it feels like the code is writing itself, it’s easy to forget you still need to understand what’s being built. Shipping something you didn’t fully read is a time bomb, not a win.
How to Actually Use It Well (and Not Get Burned)
Treat AI as a lazy junior dev: It’s helpful, fast, and cheap. But it’s your job to review, test, and refactor what it gives you. If you wouldn’t blindly merge a PR from a new hire, don’t blindly accept AI-generated code either.
Integrate into PR culture: Encourage your team to highlight where they used AI assistance in their commits or PR descriptions. It makes review more intentional—and more honest.
Use it for speed, not strategy: AI can help you type faster. But it shouldn’t be designing your architecture or replacing critical thought. The best use cases are low-risk, repetitive, or exploratory.
Don’t skip code reviews: Seriously. AI is not your QA. Let’s not pretend a generated test case is proof of correctness. Keep your team’s standards high.
Use AI to help you review code. A few prompts that I have had success with with Github Copilot :
Final Verdict: Not Magic, Not Trash, But a very useful Tool and its getting better on a daily basis.
AI pair programming isn’t going to replace you (yet), and it’s not going to ruin your codebase, unless you let it. Like any new dev tool, it requires judgment, context, and a little humility. Used well, it can speed things up. Used poorly, it can bury bugs in beautiful code.
So keep your brain turned on, your test suite handy, and maybe give your synthetic sidekick a chance just don’t let it drive.
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