Remote technical interviews are broken.

Not because the questions are bad. Not because the candidates are unprepared.

Because the tooling gets in the way.

The Problem

Every engineering team running remote interviews has hit some version of this:

• The candidate can't open the shared doc because they need to sign in first.
• The "online IDE" you picked requires a download, an extension, or a 3-minute setup.
• Someone's corporate laptop blocks the tool entirely.
• The session drops mid-interview and there's no way to recover it.

By the time everyone's actually coding together, ten minutes are gone. The candidate is flustered. The interviewer is apologizing. And whatever signal you were trying to get is already compromised.

The root cause isn't any single tool. It's that most collaborative coding environments weren't built for the interview context. They were built for general-purpose use and bolted onto hiring workflows as an afterthought.

We felt this ourselves running technical screens at SkillBrew.AI. So we stopped patching around it and built something purpose-built.

The Resolution: Build for Zero Friction

The design constraint was simple: a candidate gets a link, clicks it, and they're coding. No account. No install. No configuration. Under 30 seconds from link to live session.

Everything else followed from that constraint.

Browser-native, not desktop. The moment you ask someone to install anything, you've created a drop-off point you can't control. A browser session works on any machine, any OS, behind most corporate firewalls. The trade-off is that a browser sandbox can't execute code natively—you need a remote runtime for that. We made peace with it early. Getting candidates into a live session fast matters more than where the code executes.

WebSockets, not polling. Real-time collaboration needs a persistent, bidirectional channel. Polling burns server resources and still delivers a laggy experience. WebSockets keep every keystroke, cursor movement, and selection range in sync in near-real-time. The server holds the canonical session state—that becomes the anchor for everything else.

OT-based conflict resolution. Two people typing at the same time is where most collaborative editors quietly break. We went with an Operational Transformation approach on a central-server model: the server sequences all operations and each client transforms its edits against concurrent ones before applying them. It's what powers Google Docs. For our use case—two to four participants, always server-connected—it's simpler to operate and easier to debug than the alternative (CRDTs), which shine in peer-to-peer or offline scenarios we don't have.

What Made It Hard

Even with the right architecture, four problems burned us in ways the design didn't fully anticipate.

Latency perception. Users shouldn't feel the network when they type. We apply optimistic local updates—the client applies the edit immediately and reconciles with the server in parallel. This keeps the editor feeling instant even at 80–120ms round-trip. But broadcast to collaborators has to stay under ~50ms. Above that, the lag becomes visible and the collaborative experience breaks down.

Cursor positions aren't static. If you insert characters before my cursor, my position in the document shifts. Every cursor update has to be transformed against the same operation stream as the document content. We also broadcast full selection ranges, not just caret positions—knowing what someone is looking at during a live interview is different from knowing where their cursor is.

Undo is a trap. In a collaborative context, undoing your own edit might conflict with something the other person typed in the same window. We scoped undo to local-only and documented it clearly. Not the most elegant solution, but it avoided shipping a class of subtly broken behavior that would have eroded trust fast.

Reconnection has to be invisible. Browsers disconnect. Laptops sleep. Candidates accidentally close the tab. A session that loses its state on reconnect is unusable. We treat reconnection as a first-class flow: the client pulls a full document snapshot, rebinds the WebSocket, and resumes exactly where it left off. The candidate sees nothing. We found the worst bugs here during beta—later than we should have.

What We Shipped

The result is a collaborative code editor built specifically for technical interviews. Sessions start via link in seconds. There's syntax highlighting across major languages, live cursor presence, and code execution through a remote sandbox. The interface is minimal—nothing in it that doesn't serve the interview.

We run every internal technical screen on it. That dogfooding is what drove most of the reliability work. When you use your own tool every day, rough edges don't stay hidden.

What We'd Do Differently

Start simpler on session management. We built a generalized room system before we understood what our sessions would actually look like. Most of that flexibility never got used.

Observability from day one. When early users said "it feels slow," we couldn't tell if the problem was the WebSocket, the broadcast, or the client rendering. Structured latency metrics should have been in from the start.

Ship cursor polish early. Remote cursors that jump between positions look broken even when everything's technically correct. We underestimated how much that visual detail affects trust in the product.

The core lesson from building this: real-time collaborative systems expose edge cases fast. The best thing you can do is get real users in the session early—two people editing the same document live for twenty minutes will surface more problems than any unit test suite.

We're still iterating. If you're building in this space and want to compare notes, or you try it and find something broken, we want to hear it.