docs(redesign): record product brief and phased audit handoff

docs/redesign/AI_PRINCIPLES.md

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+# AI Principles
+
+## Non-negotiable rule
+
+AI MUST NOT INVENT USER FACTS.
+
+It must never fabricate or silently imply:
+
+- skills,
+- technologies,
+- qualifications,
+- education,
+- certifications,
+- work history,
+- job titles,
+- responsibilities,
+- achievements,
+- metrics,
+- projects,
+- languages,
+- dates,
+- salary history,
+- personal details,
+- experience the user has not provided.
+
+If information is missing, AI should say that it is missing or ask the user to provide it.
+
+## Source of truth
+
+The Career Profile is the canonical source of user career information.
+
+AI may also use information explicitly supplied in the current workflow, such as:
+
+- a job description,
+- user-entered notes,
+- an uploaded document,
+- a CV-specific override.
+
+AI must preserve provenance wherever practical.
+
+## Example
+
+Bad:
+
+`Added Kubernetes experience because the job requires it.`
+
+Good:
+
+`Kubernetes appears in the job requirements, but it is not present in your Career Profile. I have not added it to your CV.`
+
+## AI interaction model
+
+Use a hybrid model:
+
+1. Contextual actions beside content.
+2. A persistent or easily opened contextual assistant.
+3. Command-palette AI actions where useful.
+
+Avoid creating a disconnected AI area that forces users to leave their workflow.
+
+## Contextual awareness
+
+The AI assistant should understand what the user is currently working on.
+
+Examples:
+
+### On a Job page
+
+- How good a match am I?
+- What requirements am I missing?
+- What should I emphasise on my CV?
+- Prepare interview questions.
+- Help me research this role/company.
+- Draft a follow-up message.
+
+### In a CV
+
+- Make this shorter.
+- Make this more natural.
+- Tailor this to the selected job.
+- Check for unsupported claims.
+- Improve readability.
+
+### In Career Profile
+
+- Suggest missing details to add.
+- Improve wording without changing facts.
+- Identify duplicate information.
+
+## Review before apply
+
+AI-generated modifications to user-owned content must not be applied silently.
+
+Show a preview or diff before committing changes.
+
+Minimum actions:
+
+- Accept
+- Reject
+
+Where practical:
+
+- Accept individual change
+- Accept all
+- Edit before applying
+
+## Evidence
+
+For match analysis, AI should make it clear which Career Profile item supports a claim.
+
+Example:
+
+`Strong match: C# / .NET`
+
+Evidence:
+
+`Work history → Analyst Programmer → C#/.NET backend development`
+
+## Match scoring
+
+If a numeric match score is shown:
+
+- explain major contributors,
+- distinguish required vs preferred criteria where possible,
+- do not imply mathematical precision beyond the underlying method,
+- do not penalise unknown information as though it were definitely absent unless the product logic explicitly chooses to do so.
+
+## User control
+
+Users should be able to:
+
+- disable or ignore suggestions,
+- review AI output,
+- edit output,
+- understand whether content was AI-assisted.
+
+## Tone
+
+AI should be:
+
+- professional,
+- supportive,
+- concise,
+- practical,
+- non-judgmental.
+
+Avoid exaggerated motivational language.
+
+## Privacy and logging
+
+AI-related data handling should be explicitly documented during implementation.
+
+Do not assume that all user content may be retained indefinitely.
+
+Any future analytics about AI usage should prefer aggregate product metrics and avoid exposing private career content to administrators unless required and authorised.