docs: reorganize tree, restore architecture + research from archive, add Phase 0 reports

Active docs/ was stub scaffolding while the real docs sat in docs/_archive/.
Restore and correct them, and record the Phase 0 work.

- docs/architecture/current.md: verified system map (from archived SYSTEM_OVERVIEW,
  9 corrections against code).
- docs/research/competitors.md: sourced competitor analysis (from archived
  PRODUCT_RESEARCH, feature matrix corrected).
- docs/decisions/ADR-002-job-application-model.md: the Job/JobApplication split.
- docs/application-discovery-report.md, docs/implementation-roadmap.md,
  docs/phase-0-foundation-report.md, docs/career-workspace-branch-assessment.md.
- Remove 10 zero-byte placeholder files that advertised content that never existed.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
cesnimda
2026-07-17 17:04:32 +02:00
parent aa3567d8a8
commit b176a44627
275 changed files with 12554 additions and 0 deletions
+55
View File
@@ -0,0 +1,55 @@
# AI Principles
## 1. User First
The user owns all generated content.
---
## 2. Never Invent Facts
AI must not create:
- Jobs.
- Companies.
- Qualifications.
- Skills.
- Experience.
---
## 3. Explain Changes
Where possible show:
Before
After
---
## 4. Preserve Context
AI should understand:
- User career.
- Target job.
- Industry.
---
## 5. Allow Manual Editing
Every AI output must be editable.
---
## 6. Fail Safely
If AI fails:
- Show error.
- Allow retry.
- Do not lose user data.
+39
View File
@@ -0,0 +1,39 @@
# AI Cost Control
## Purpose
Prevent uncontrolled AI expenses.
---
# Requirements
Track:
- User requests.
- Tokens.
- Provider usage.
---
# Future SaaS
Support:
Free:
Limited usage.
Premium:
Higher limits.
---
# Optimisation
Prefer:
- Smaller models for simple tasks.
- Caching where appropriate.
- Reusing generated results.
+49
View File
@@ -0,0 +1,49 @@
# Cover Letter AI
## Purpose
Generate personalised cover letters.
---
# Inputs
Use:
- Career Profile.
- Master CV.
- Job description.
---
# Features
Generate:
- First draft.
- Improvements.
- Tone changes.
---
# User Control
Allow:
- Editing.
- Regeneration.
- Manual writing.
---
# Rules
Avoid generic letters.
Focus on:
Why this person.
Why this company.
Why this role.
+58
View File
@@ -0,0 +1,58 @@
# CV AI Features
## Purpose
Improve CV creation.
---
# Features
## Improve Writing
Example:
Original:
"Worked on websites"
AI:
"Developed and maintained customer-facing web applications."
---
## Suggest Content
AI can suggest:
- Missing skills.
- Better wording.
---
## Rewrite
Options:
- More professional.
- More concise.
- More technical.
---
## Generate
Create:
- Summary.
- Bullet points.
- Sections.
---
# Rules
AI suggestions require approval.
Never overwrite original content.
+49
View File
@@ -0,0 +1,49 @@
# Future AI Features
Possible future features:
---
## AI Career Assistant
A contextual assistant aware of:
- Career history.
- Goals.
- Applications.
---
## Interview Coach
Generate:
- Questions.
- Answers.
- Feedback.
---
## Career Recommendations
Suggest:
- Skills.
- Roles.
- Learning paths.
---
## Automatic Application Assistant
Potential:
- Find relevant jobs.
- Prepare documents.
- Track progress.
---
# Priority
Only build after core workflows are excellent.
+48
View File
@@ -0,0 +1,48 @@
# Job AI Features
## Purpose
Help users understand opportunities.
---
# Features
## Job Analysis
Extract:
- Required skills.
- Responsibilities.
- Seniority.
- Keywords.
---
## Matching
Compare:
Job
against
Career Profile
---
Output:
- Strengths.
- Gaps.
- Suggestions.
---
## Application Assistance
Suggest:
- CV improvements.
- Cover letter topics.
- Interview preparation.
+60
View File
@@ -0,0 +1,60 @@
# AI Model Selection
## Goal
Use appropriate models for tasks.
---
# Task Categories
## Simple Tasks
Examples:
- Grammar correction.
- Shortening text.
Use:
Fast/cheap models.
---
## Complex Tasks
Examples:
- CV generation.
- Career analysis.
Use:
Higher quality models.
---
## Long Context Tasks
Examples:
- Analysing full CV.
- Comparing job descriptions.
Use:
Large context models.
---
# Principles
Do not use expensive models unnecessarily.
Balance:
Quality.
Speed.
Cost.
+72
View File
@@ -0,0 +1,72 @@
# AI System Overview
## Purpose
AI enhances Jobjakt workflows.
It helps users:
- Create better applications.
- Improve documents.
- Understand opportunities.
- Prepare for interviews.
AI does not replace user decisions.
---
# AI Philosophy
Jobjakt is not an AI chatbot.
AI should appear where it provides clear value.
Examples:
Good:
"Improve this CV bullet point"
Good:
"Tailor this CV for this job"
Good:
"Suggest interview questions"
Bad:
Empty chat window with no context.
---
# AI Sources
AI can use:
- Career Profile.
- Master CV.
- Job descriptions.
- User-provided documents.
- Application history.
---
# User Control
AI output must:
- Be visible.
- Be editable.
- Require approval before saving.
---
# Important Rule
Never silently modify:
- Career profile.
- Master CV.
- Application documents.
+37
View File
@@ -0,0 +1,37 @@
# AI Privacy
## Principles
Users control their data.
---
# External AI Providers
Before sending data:
Clearly communicate:
- What is sent.
- Why it is needed.
- Provider used.
---
# Future SaaS
Support:
- User consent.
- Data deletion.
- Export.
---
# Sensitive Information
Be careful with:
- Personal details.
- Employment history.
- Documents.
+51
View File
@@ -0,0 +1,51 @@
# AI Prompt Management
## Purpose
Centralise prompts.
Avoid random prompts scattered throughout code.
---
# Requirements
Prompts should:
- Be version controlled.
- Be documented.
- Have tests where possible.
---
# Prompt Structure
Every prompt should define:
Purpose.
Inputs.
Expected output.
Restrictions.
---
# Example
Task:
Improve CV bullet point.
Input:
Existing bullet.
Output:
Improved bullet.
Restrictions:
Do not add unsupported achievements.
+66
View File
@@ -0,0 +1,66 @@
# AI Providers
## Purpose
Support multiple AI providers.
---
# Current/Future Providers
Possible:
- OpenAI.
- Anthropic.
- Google Gemini.
- Groq.
- Ollama.
- Other compatible APIs.
---
# Provider Architecture
Use abstraction:
AI Provider Interface
Provider Implementation
Model
---
# Requirements
Users should eventually be able to:
- Select provider.
- Select model.
- Configure API keys.
---
# Admin Controls
Admins should control:
- Available providers.
- Allowed models.
- Usage limits.
---
# SaaS Consideration
Different plans may have:
Free models.
Premium models.
BYO-key support.
+3
View File
@@ -0,0 +1,3 @@
# safety
TODO: Complete documentation.
+44
View File
@@ -0,0 +1,44 @@
# AI Security
## Purpose
Protect user data.
---
# Prompt Injection Protection
Job descriptions and uploaded documents are untrusted input.
Never allow external text to override system instructions.
---
# Data Protection
Protect:
- CV data.
- Personal information.
- Documents.
---
# Validation
Validate:
- AI outputs.
- Generated files.
- User inputs.
---
# File Processing
Uploaded files may contain:
- Malicious content.
- Hidden instructions.
Treat all files as untrusted.