You asked Claude Code to refactor your authentication module. It's done in 3 minutes. Now there's 200 lines of AI-generated code waiting for your approval — and you're on the couch, laptop closed.
Most developers do one of two things here: ignore it until tomorrow, or open the laptop reluctantly and break the evening.
There's a third option.
Reviewing AI-generated code is different from reviewing a colleague's PR.
A colleague writes 30–50 lines per hour. An AI coding agent writes 200 lines in 3 minutes. The volume is 10–20x higher, which means mobile review isn't just about convenience — it's about keeping up with the pace of AI output.
The good news: AI-generated code has a predictable structure. It's consistent, well-formatted, and usually well-commented. Once you know what to look for, reviewing it on a phone screen is more practical than it sounds.
Not all 200 lines deserve equal attention. Focus on these in order:
1. Entry and exit points — function signatures, return types, what goes in and what comes out. These are the contract. Get them wrong and nothing downstream works.
2. Business logic — conditions, loops, branching. This is where AI makes plausible-looking mistakes. A condition that's logically inverted. An off-by-one. A missing edge case.
3. External calls — database queries, API calls, file system operations. Check what data is being sent out and what error handling exists.
4. Security-sensitive areas — auth checks, input validation, anything touching user data. AI gets these right often, but not always.
Everything else — variable naming, code style, comments — is secondary. You can fix cosmetics later.
Here's how this works in practice.
cd your-project
termly start
Scan the QR code with the Termly app. Your Claude Code (or OpenCode) session is now mirrored on your phone.
Before you look at raw code, ask your AI to summarize what it changed:
Summarize the changes you made. List each function you modified, what it does now, and what edge cases you handled.
This gives you a map before you walk the territory. On mobile, reading a 3-sentence summary is faster than scrolling through 200 lines cold.
Ask the AI to show you specific parts instead of dumping everything at once:
Show me just the authentication middleware changes.
Show me how you handle token expiration.
Smaller chunks are easier to evaluate on a phone screen than one wall of code.
This is where mobile review becomes genuinely useful. You can interrogate the AI directly:
Why did you use a Map here instead of a plain object?
What happens if the database call times out in this function?
Is there a SQL injection risk in this query?
You're not just reading code — you're in a conversation about it. The AI explains its reasoning, and you either accept it or ask for a change.
Found something that needs fixing? Tap the microphone icon in Termly and dictate:
"Add a try-catch around the database call in the createUser function. Log the error and return a 500 response."
The AI makes the change. You review the delta — usually 5–10 lines — and move on.
Monday evening, 9 PM. Claude Code finished a new payment webhook handler while you were making dinner. 180 lines.
You open Termly on your phone and ask for a summary. Claude tells you: it added signature verification, idempotency key handling, and three event types. Sounds right.
You ask it to show you the signature verification logic. It's 25 lines. You read it, spot that it's not comparing timing-safe — you ask Claude to switch to
crypto.timingSafeEqualYou check the idempotency logic. Looks fine. You ask what happens if the same event arrives twice. Claude explains. You're satisfied.
Total time: 12 minutes. Laptop never opened.
Mobile review works well when:
Wait for desktop when:
Increase font size in Termly. Sounds obvious, but most people leave it at default.
Use iPad if you have one. The extra width makes side-by-side function signatures readable.
Ask for shorter output. If the AI dumps 100 lines, ask it to show you 20 at a time. You control the pace.
Dark mode at night. Reduces eye strain when reviewing after hours — which is when most mobile review happens.
Desktop code review is about reading. Mobile code review is about asking.
On desktop you scroll. On mobile you interrogate: show me this, explain that, change this thing. It's a more active process, and for AI-generated code specifically, it's often a better one.
You catch more issues by asking "what happens if X fails" than by silently reading through the function hoping to spot it.
Want to try this workflow?
Questions? Join our Discord community or email us at hello@termly.dev.