Building Prompt-Led Photo Editing Around Reviewable Outcomes
Why capability dependencies, preservation instructions, provenance, and controlled iteration matter more than a model dropdown.

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Why capability dependencies, preservation instructions, provenance, and controlled iteration matter more than a model dropdown.

A builder's model for combining reference images, changing capabilities, and human review in one workflow.

What I learned from organizing an AI photo editor around user intent, capability limits, and reviewable outcomes.

The data-model choices behind keeping stat sources, units, missing values, and arithmetic deltas honest.

How record identity, source provenance, release boundaries, and explicit unknowns make a small farming tool more trustworthy.

A TypeScript design note on ordered format attempts, duration budgets, provider error classification, and progress normalization.
How sample length, sentence count, feature summaries, and explicit fallback states can keep a detector from overstating confidence.

A practical article about host choice, first-run setup, official verification, and the limits of independent install guidance.
