Future Features

Three expansion directions beyond the core MVP: Cover Letter generation, Networking intelligence, and Mock Interview practice.

1. Cover Letter Generation

Generated alongside resume tailoring — after analyzing a JD, produce both a tailored resume and a matching cover letter in one step.

Workflow

flowchart TD
    JD[JD Analysis] --> Tailor[Tailor Resume]
    JD --> CL[Generate Cover Letter]
    Tailor --> Review[Review Resume Diff]
    CL --> ReviewCL[Review Cover Letter]
    Review --> Export[Export Package]
    ReviewCL --> Export
    Export --> Apply[Apply]

Design

Input: JD Analysis + User Profile + Base Resume
Output: A cover letter targeted to the specific role (Markdown / PDF)
LLM rules:
- Only reference experiences and skills present in the resume
- Match keywords and responsibilities from the JD
- Professional tone without exaggeration
- Controlled length (250-400 words)
Anti-hallucination: Same rules as resume tailoring — never fabricate experiences

CLI usage:

kairos resume tailor --job-id <id>               # generates resume + cover letter
kairos resume export --job-id <id> --format pdf   # export full application package

Architecture Impact

kairos-core: New CoverLetter entity + CoverLetterService trait
kairos-llm: New cover letter prompt template
kairos-db: Cover letter storage (linked to Job + Resume)
API: POST /api/resumes/:id/cover-letter, GET /api/resumes/:id/cover-letter/:job_id

2. Networking

Help users discover industry events and networking opportunities at target companies.

Two Dimensions

Dimension	Description	Data Sources
Industry Events	Tech community meetups, conferences, hackathons	Meetup.com, Eventbrite, Lu.ma
Company Events	Hiring events, open days, tech talks by target companies	LinkedIn Events, company websites

Example

kairos events search --location perth --tags rust,backend
kairos events search --company atlassian

Output:

  Score  Event                           Date        Location
  0.92   DDD Perth 2026                  2026-05-16  Perth Convention Centre
  0.85   Perth Rust Meetup #42           2026-04-10  Spacecubed
  0.78   Atlassian Hiring Event Perth    2026-04-22  Atlassian Office

Design

Match scoring: Score events against User Profile (skills, target roles, location)
LLM-assisted: Analyze event descriptions to determine relevance to user’s goals
Smart alerts: Applied to a company → automatically surface that company’s events
Storage: New Event table in SQLite, linked to companies and skill tags

Architecture Impact

kairos-core: New Event entity + EventSearchService trait
kairos-platform: New event adapters (Meetup, Eventbrite, Lu.ma)
API: GET /api/events, POST /api/events/search
Reuses the existing adapter pattern — same structure as job platform adapters

3. Mock Interview

LLM-powered interview practice based on the specific JD and company information.

Three Modes

Mode	Content	Data Source
Technical	Algorithms, system design, language-specific questions	JD required skills + tech stack
Behavioral	STAR-format questions (teamwork, conflict, leadership)	JD responsibilities + common behavioral question bank
Company Culture	Company values, team dynamics, “why this company”	LinkedIn, Glassdoor, company website

Workflow

flowchart TD
    Select[Select an applied job] --> Mode{Choose mode}
    Mode --> Tech[Technical Questions]
    Mode --> Behavioral[Behavioral Questions]
    Mode --> Culture[Company Culture]
    Tech --> QA[LLM asks → User answers]
    Behavioral --> QA
    Culture --> QA
    QA --> Feedback[LLM provides feedback + suggestions]
    Feedback --> Next{Continue?}
    Next --> |Yes| QA
    Next --> |No| Summary[Practice Summary Report]

Design

Input: JD Analysis + Company Info + interview mode
Interaction:
- CLI: Q&A conversation (good for quick practice)
- Web: Chat interface (better experience)
LLM role:
- Act as interviewer, generate questions based on JD
- Evaluate answers with scoring and improvement suggestions
- Follow-up questions to simulate real interview flow
Session storage: Save practice history, track improvement over time
Temperature: 0.7 (needs variety — avoid repeating the same questions)

CLI Usage

kairos interview --job-id <id> --mode technical
kairos interview --job-id <id> --mode behavioral
kairos interview history                          # view practice history

Architecture Impact

kairos-core: New InterviewSession, InterviewQuestion entities
kairos-llm: New interview prompt templates (per mode)
kairos-db: Session + question + answer storage
API: POST /api/interview/start, POST /api/interview/:id/answer, GET /api/interview/:id/summary
WebSocket: Real-time streaming for conversational flow

Priority

Feature	Priority	Rationale
Cover Letter	High — can ship with Phase 4	Reuses existing LLM + JD Analysis, small incremental effort, high user value
Mock Interview	Medium — Phase 8+	Value-add after core workflow is complete, better with Web UI
Networking	Low — Phase 8+	Requires new data source adapters, independent of the core job application flow

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