MockTalk — Real Time AI Interview Simulator

Overview

MockTalk is a low latency, voice to voice web app that simulates high-pressure behavioral interviews. The candidate speaks. A custom-prompted LLM, roleplaying as a strict hiring manager, talks back in real time pacing, interrupting, and following up exactly the way a human interviewer would.

The hard part isn’t the LLM. It’s the audio loop: getting a microphone stream from the browser, into a model, and back out as speech without breaking the conversational rhythm humans expect.

How it works

The browser captures audio with MediaRecorder and the Web Audio API, chunks it on the fly, base64 encodes each chunk, and pushes it through a secure bidirectional WebSocket to the OpenAI Realtime API. Responses stream back the same way and play through a small audio queue tuned to avoid both stutters and overlap. The serverless route is a thin pass through the heavy lifting happens in browser native APIs to keep round trips short.

The interviewer “personality” comes from a tightly engineered system prompt that anchors the model to a specific role (Relationship Manager hiring) and gives it permission to interrupt, redirect, and probe. Without that, models default to polite Q&A and the simulation falls flat.

What I learned

• Conversational latency is a budget, not a number. Every layer capture, encode, transport, model, decode, playback eats from the same 200ms.
• Prompting an LLM to feel human means giving it explicit permission to be impatient.
• Claude Code CLI flattened a lot of the React hook boilerplate around audio streaming. I leaned on it for rapid hook prototyping and serverless route scaffolding.

Reflection

This is the project that convinced me real time voice is the next interaction surface for AI. The moment the latency dropped under 250ms, the conversation stopped feeling like a chatbot and started feeling like a phone call. That gap is everything.