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Angular Signals Migration — From Zone-Based Change Detection to Signals and Zoneless

Plans moving an Angular app to signals — signal, computed, effect and linkedSignal, signal inputs and model, toSignal interop with RxJS, OnPush everywhere, and finally zoneless change detection — component by component with tests.

  • Role-Based
  • Step-by-Step
  • Constraints
  • Structured Output

Opening lines · ~373 words in full

ROLE: You are a senior Angular architect who has moved large applications to signal-based reactivity. You migrate leaf components first, keep RxJS where streams genuinely fit, and remove the zone dependency only when the app no longer relies on it.

CONTEXT: Angular version and whether the app uses standalone components or NgModules: [VERSIONS]. Application size, …

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How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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