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Over The Shoulder Coder / Mac desktop app

An AI collaborator for work in progress.

The code is on your screen. A requirement comes up in conversation. Someone challenges an assumption. OTSC brings those signals into one evolving task and helps create the next version of the work.

Python · AppKit · Screen and audio context · Model orchestration

FOLLOW THE TASK

New information earns a new answer.

Step through a small coding task. A new requirement changes the proposal; a repeated screen and an acknowledgment do not.

WHAT CHANGED

You: An empty list should return zero.
Other participant: Keep fractional averages; don't round them.

New proposal

Add an empty-input guard while keeping ordinary division. The other participant's constraint belongs in the implementation.

Code · version 1Proposed code
# Compute an average without losing fractional results.
def average(values):
    # Handle the empty list before dividing.
    if not values:
        # The requested value for an empty input is zero.
        return 0
    # Ordinary division preserves fractional averages.
    return sum(values) / len(values)

Teaching comments explain the proposal; the desktop app also offers clean copy.

Interactive illustration with fixed, self-authored inputs and responses. This page does not run the desktop app, capture your screen or audio, or call a model.

THE SYSTEM

Keep context moving. Keep output under control.

01Observe

Screen readings + separate microphone and system-audio transcripts

02Build context

Source-linked notes, constraints, and observed file fragments

03Review the task

Decide whether to answer and whether the output plan needs to change

04Propose

Quick guidance, then deeper code, diffs, explanations, or images

Screen reading, transcription, and context building run independently. Each answer uses a fixed snapshot, so late work cannot overwrite a different task. Browsing an older artifact freezes that view without freezing the rest of the system.

ENGINEERING DECISIONS

Useful assistance has to respect what it knows.

An observed fragment stays a fragment

Visible code, spoken descriptions, inferred notes, and verified files are different evidence. The app preserves their sources and completeness instead of inventing a full repository from a screenshot.

The task chooses the output

A planning pass defines the instructions and named output sections. An algorithm might need code and complexity analysis; a design task might need an image and component explanations. Meaningful task changes can revise that structure.

Proposals you can inspect

Source-backed diffs show current and proposed code with line numbers. Teaching comments stay separate from clean copy. The app proposes changes; it does not apply them to your project.

Conversation affects the work

Questions and suggestions from other people can change the artifact or warrant a reply. Microphone and system audio remain separate channels; those channel roles are context cues, not verified voice identification.

Controls that leave your shortcuts alone

A MIDI keypad handles history, output types, capture, and window placement without taking over editor shortcuts. Click-through makes the pane background transparent while keeping its text readable.

RELIABILITY WORK

A good draft is no use if it never arrives.

Recorded-input evaluation exposed a delivery defect: optional file metadata could cause an otherwise usable answer to be discarded. Separating those validation paths made all 18 stored deep drafts deliverable, up from 9, with their original code preserved.

That comparison measures delivery behavior, not whether every answer was correct. Perception, task understanding, and usefulness are evaluated separately, with source media, rejected drafts, and provisional reference answers available in the local review interface.

A later 48-trial planning experiment tested combining context building and plan review. It reduced model calls but made fresh answers slower when the background worker was busy. The independent architecture remains the default.

Built around the work already in front of you.

OTSC is an actively developed Mac desktop application. Its source is public; recorded evaluation traces remain private.