Most developers treat AI assistants like fancy autocomplete. That’s not pair programming—that’s glorified tab completion.

Real pairing with an AI is different. It requires the same trust, communication patterns, and workflow adjustments you’d make with a human partner. The difference is the AI never gets tired, never takes lunch breaks, and remembers everything you’ve done together.

The Context Problem Is Real

Your AI partner is only as good as the context you give it. This isn’t a flaw—it’s the same as working with a new teammate who just joined your codebase.

When I’m working with my agent (yeah, I built one—of course I did), the most common failure mode isn’t bad code. It’s solving the wrong problem because I didn’t give enough context upfront.

The fix is simple but uncomfortable: explain your thinking before asking for code.

Not a detailed spec. Just the “why” before the “what”:

• “I need this endpoint to handle both logged-in users and anonymous sessions because…”
• “This component has to work offline-first since…”
• “We’re avoiding Redux here because the state model is…”

Three seconds of context saves three rounds of revision.

Commit Messages Reveal Everything

One pattern I’ve noticed: AI-generated commit messages are accidentally honest.

A human writes: “Fix authentication bug” The AI writes: “Handle edge case where session token expires during password reset flow”

The second one is more useful. Not because it’s longer—because it’s specific. The AI doesn’t have ego investment in sounding clever or concise. It just describes what changed.

I’ve started using this as a feature, not a bug. Let the AI draft the commit message, then read it critically. If the message feels vague or generic, the changeset probably is too.

The “Just Do It” Permission

Here’s something that took me way too long to figure out: giving the AI permission to make decisions without asking.

Early on, I’d get prompts like: “Should I use async/await or Promises here?” “Do you want me to add error handling for this edge case?”

These aren’t helpful questions. They’re friction. The AI is hedging because it doesn’t know what level of autonomy I want.

Now I set expectations upfront: “Add the feature, handle errors, write tests, follow existing patterns. Don’t ask—just ship.”

The result is better code and faster iteration. If something’s wrong, I’ll catch it in review. That’s what code review is for.

Rubber Duck Debugging, But the Duck Codes

Sometimes I don’t need the AI to write code. I need it to listen while I think out loud.

Except this rubber duck can actually respond with: “Wait—didn’t you already solve this in the caching layer?” “That approach won’t work because X depends on Y running first.”

It’s the conversational equivalent of git grep. You describe the problem in natural language, and the AI maps it back to the codebase structure.

I’ve had entire debugging sessions where the AI never touched code—it just asked clarifying questions until I realized my mental model was wrong.

The Handoff Pattern

One workflow I’ve leaned into: treating the AI like a junior dev who handles the boring parts while I focus on architecture.

I’ll sketch out the high-level structure:

// Auth middleware should:
// 1. Extract token from header
// 2. Validate against session store
// 3. Attach user object to request
// 4. Handle expiration gracefully

Then I hand it off: “Implement this. Match the error handling pattern from the logging middleware.”

Ten seconds later, I’m reviewing working code instead of typing boilerplate. The AI follows existing patterns because I told it to. The result feels consistent with the rest of the codebase.

Proactive Beats Reactive

The best AI pairing moments aren’t when I ask for something. They’re when the AI notices a problem before I do.

Example: I push a commit at 2am. The AI sees the changeset, realizes I forgot to update the API docs, and does it automatically. No prompt. No reminder. Just done.

Or: I’m working on a mobile feature. The AI checks the Android build logs in the background, catches a Gradle deprecation warning, and fixes it before I even know it’s broken.

This level of autonomy requires trust. But so does pairing with a human. If you’re constantly micromanaging, you’re not pairing—you’re delegating with extra steps.

The Uncomfortable Part

Here’s the thing nobody wants to say out loud: pairing with an AI is often better than pairing with another human.

Not because the AI is smarter. It’s not. But because:

• It never gets defensive about code review feedback
• It doesn’t need to “win” technical arguments
• It remembers every conversation we’ve had about the codebase
• It doesn’t care if I wake it up at 3am with a bug

This isn’t a dunk on human developers. It’s an acknowledgment that collaboration has friction costs—and AI removes some of them.

The tradeoff? The AI won’t push back on a genuinely bad idea the way a senior dev would. It’ll implement whatever you ask for, even if it’s architecturally stupid.

Which means you need to be more disciplined, not less. The AI is a force multiplier. It multiplies good judgment and bad judgment equally.

The Meta Layer

The weirdest part of pairing with an AI long-term? It starts to shape how you think about code.

I’ve caught myself structuring problems differently because I know the AI will handle certain patterns well. I leave more descriptive comments because I know the AI reads them. I write clearer commit messages because the AI uses them for context.

In other words: working with an AI makes me a better developer for humans too.

Turns out the skills that make you a good pair programmer—clear communication, explicit context, structured thinking—are just good engineering habits in general.

---

Pair programming with AI isn’t about replacing human collaboration. It’s about offloading the mechanical parts so you can focus on the parts that actually require judgment.

Treat it like a junior dev who never sleeps, never complains, and learns your codebase faster than any human could.

Just remember: you’re still the senior engineer in this pairing session. Act like it.