Interview mode

The interview copilot.

It hears the interviewer, drafts the answer as the question lands, and puts it where only you can see it. Short enough to use mid-sentence.

Transcript
InterviewerDesign a URL shortener. Assume one of the links goes viral.
YouLet me scope it first — how many new links a month are we expecting?
InterviewerSay a hundred million, mostly re
Q: URL shortener that survives a viral link
Design
  • Requirements: 100M links/month, 10:1 reads, p99 < 100 ms
  • API: POST /shorten · GET /{code} → 302
  • Data model: code → long URL, owner, expiry
  • Core flow: hash, collision check, stateless redirect service
  • Storage: key-value store, codes as keys
  • Scaling: cache hot codes, shard by code prefix
  • Failure modes: hot key on viral link → CDN + in-memory cache
Say

I’ll assume a hundred million new links a month, reads ten to one over writes, and a p99 under 100 milliseconds on the redirect. The headline is a stateless redirect service over a key-value store, with an in-memory cache and CDN edge caching for the hot codes.

Trade-offs
  • Key-value over relational because lookups are by code only (accepting no rich queries)
  • 302 over 301 because analytics need every hit (accepting one extra hop)
⌘⇧A Ask⌘⇧S Snap⌘⇧M Mic⌘⇧\ Hide⌘ on macOS · Ctrl on Windows · global, even while the call has focus
Inside a session

What happens between the question and your first word.

Both sides of the call, transcribed live

Your microphone and the system audio are captured as two channels, so the interviewer and you appear as separate, labelled bubbles. Each bubble updates in place as the words arrive and locks when the sentence ends. Live transcription runs in 40+ languages, including bilingual pairs.

InterviewerWalk me through how you’d shard this table.
YouI’d start from the access pattern —
InterviewerAnd if one tenant is ten times the

Scan to glance at. Say to read aloud.

Every answer has a fixed shape so you never have to read to find the point. Scan is 3–5 bullets of eight words or fewer, the direct answer first. Say is the same answer as 50–90 words of first-person prose. Coding questions get Say · Code · Explain; system design gets Design · Say · Trade-offs; behavioral questions get four STAR beats and a 90–130-word story.

Concept · MLScanSay
CodingSayCodeExplain
System designDesignSayTrade-offs
BehavioralScan (STAR)Say

Go Deeper when they follow up

One click on any answer adds 250–350 words that add the two insights that matter most, and never restates the original. In a system-design round, each Go Deeper expands the next stage the interviewer will ask about, in the order they ask it: requirements, API, data model, components, storage, scaling, failure modes. ML designs follow their own ladder from data and labels through serving and evaluation.

  1. Requirements & numbers
  2. API
  3. Data model ← Go Deeper
  4. Core components
  5. Storage
  6. Scaling
  7. Failure modes & consistency
  8. Observability & rollout

Snap the screen for written questions

Cmd/Ctrl+Shift+S captures the screen. A coding problem in the editor comes back as a one-line approach to say, a full runnable solution in the language on screen, and a two-bullet explanation with the complexity. A diagram or a design prompt gets the design walkthrough. Screenshots are processed and discarded.

Code
def two_sum(nums, target):
    # one pass: value -> index
    seen = {}
    for i, n in enumerate(nums):
        if target - n in seen:
            return [seen[target - n], i]
        seen[n] = i
Complexity: O(n) time, O(n) space

Your résumé, the job description, your notes

Upload files once and they become reference material for every answer. Set the company, role, and round type when you start a session; they never leak from a previous one. Answers are calibrated to your seniority and never claim an employer or project that is not in your material.

resume.pdfjob-description.txtsystem-design-notes.md
CompanyAcme Robotics
RoleSenior ML Engineer
RoundSystem design

History, a summary, and a choice of model

Sessions are saved to your local history with their transcript. When you end it, you get a recap of what came up, a score out of 10 with one-line call-outs on clarity, depth, and structure, and what to tighten next time. Pro lets you pick the model per session.

  • Claude Haiku 4.5 (fast, default)
  • Claude Sonnet 4.6 (sharper)
  • GPT-5 mini (reasons first)
Screen share

The overlay is excluded from screen capture.

It uses the operating system’s own exclusion (NSWindow sharingType on macOS, SetWindowDisplayAffinity on Windows), so it never appears in a shared screen or a recording. It stays out of the taskbar, can be dimmed to a whisper, and can pass clicks straight through.

Three modes

One app for the interview, the rehearsal, and the job after.

Keyboard

Every action is a shortcut.

Cmd on macOS, Ctrl on Windows. The four global ones fire even while Zoom has focus.

Global work even while the call has focus

  • ⌘/Ctrl⇧AAsk from voice
  • ⌘/Ctrl⇧SSnap / Solve
  • ⌘/Ctrl⇧MToggle mic
  • ⌘/Ctrl⇧\Hide / show app

In-app when the overlay is focused

  • ⌘/Ctrl⇧RReset feed
  • ⌘/Ctrl⇧TClear transcript
  • ⌘/Ctrl⇧↑Scroll up
  • ⌘/Ctrl⇧↓Scroll down
  • ⌘/Ctrl⇧=Bigger font
  • ⌘/Ctrl⇧-Smaller font
  • ⌘/Ctrl⇧CCopy response
  • ⌘/Ctrl⇧]More opaque
  • ⌘/Ctrl⇧[More transparent
  • ⌘/Ctrl⇧GGhost mode (click-through)
Interview mode

Questions about the copilot.

Ready before the next question.

Free to download. Ten minutes of live transcription a day on the free plan; Pro removes the caps.

Free plan: 10 minutes a day, no card · Apple Silicon · Windows 10/11 x64