Determinism over randomness
Same input, same video. A re-run is a no-op — nothing drifts between renders unless we change the script. AI in the loop, not in the output.
Deterministic, sandboxed, hand-paced screencast tutorials — for any tool worth learning. Built like software, not generated like a tweet.
See samples ↓// the problem
Invented steps. A voice that sounds like every other channel. Audio dubbed onto a screen recording, drifting half a second behind the action. The viewer can't tell if it's true, and after thirty seconds, they don't care.
// our approach
We didn't make AI tutorials better by making the model bigger. We made them better by being strict about what the model is allowed to decide.
Same input, same video. A re-run is a no-op — nothing drifts between renders unless we change the script. AI in the loop, not in the output.
Every action on screen actually happened, in a sealed environment, with real results. No mocked frames, no fabricated output. If it works in the video, it works on your machine.
Narration is synthesised first. The recording paces itself to land after the sentence finishes. The audio was never dubbed onto the recording — the recording was timed to the audio.
The pre-action pause. The mouse-to-keyboard transition. The keystroke and click sounds. The observation beat after something happens on screen. Detail you don't notice — until it's missing.
// see for yourself
Tap to play — same audio, same pacing, same accuracy as anything you'd see on the feed. No edits between social and here.
// how it gets made
A research pass writes a beginner-first script with one new idea per beat. A sealed environment performs the actions on screen — every step real, every result captured live. A renderer composites the recording, mixes the narration, lays in the input sounds, and exports — at whatever resolution and aspect the destination calls for.
We built the rig. We're using it to make tutorials.
// say hi
Commissions, requests, a hello — all welcome. A short note is enough.
talk@clipeek.dev