tutor-service/.planning/ROADMAP.md

Roadmap: Tutor Platform

Milestone 1: Job-Seeker Interview Tutor MVP

Phase 1: Go Backend Foundation and Workflow Boundary

Goal: Establish the Go service skeleton and typed workflow boundary for internalized agent-farm-go patterns.

Requirements: BACK-01, BACK-02, BACK-03, BACK-04, BACK-05

Success Criteria:

• Go backend scaffold exists with clear module boundaries.
• No manually authored source file exceeds 600 lines.
• Workflow interfaces are typed and isolated from HTTP handlers.
• Runtime config can identify the third-one / deepseek-v4-flash target.
• Basic build/test command is documented in AGENTS.md.

Phase 2: Diagnostic Interview Loop

Goal: Prove the first job-seeker loop from role selection through graded diagnostic interview.

Requirements: INT-01, INT-02, INT-03, INT-04, INT-05, INT-06

Success Criteria:

• User can choose target role and stack.
• Backend can create a diagnostic session.
• System produces role-specific interview questions.
• User answers are graded through typed workflow results.
• Grading evidence and original answer are persisted.

Phase 3: Learner Memory

Goal: Convert graded answer evidence into structured learner memory.

Requirements: MEM-01, MEM-02, MEM-03, MEM-04, MEM-05

Success Criteria:

• Learner profile is persisted.
• Concept mastery updates require evidence.
• Misconceptions link to supporting answers.
• Session context and durable memory remain separate.
• Memory extraction workflow emits typed candidates.

Phase 4: Progression and Gamified Learning Routine

Goal: Make readiness and next challenge visible without empty rewards.

Requirements: PROG-01, PROG-02, PROG-03, PROG-04, PROG-05

Success Criteria:

• Readiness map displays concept states.
• Challenge ladder exists for the first backend interview track.
• Next challenge is selected from learner memory and grading evidence.
• Boss question unlocks after prerequisite stability.
• Streak/reward behavior avoids punitive and random-reward mechanics.

Phase 5: Source-Backed Ontology Builder

Goal: Start material ingestion and ontology candidate generation.

Requirements: ONTO-01, ONTO-02, ONTO-03, ONTO-04

Success Criteria:

• User/operator can add source material.
• Concepts, prerequisites, rubrics, and question candidates carry provenance.
• Missing prerequisites and weak areas are flagged.
• Generated/inferred content is not promoted as canonical automatically.

Phase 6: Visual Teaching Asset Pipeline

Goal: Generate reviewable teaching asset candidates from ontology concepts.

Requirements: ASSET-01, ASSET-02, ASSET-03

Success Criteria:

• Asset prompt generation contract exists.
• Generated assets store prompt lineage, source concept, source evidence, model config, and review state.
• Actual image model identifier is verified before production image calls.

Parking Lot

• General student mode.
• Teacher/parent dashboards.
• School tenant administration.
• Company-specific interview packs.
• Human ontology review console.

Milestone 2: Frontend MVP

Phase 7: Web App Shell and Diagnostic Start

Goal: Serve the first web app from the Go service and let a job seeker start diagnostic practice without API tooling.

Requirements: WEB-01, WEB-02, WEB-03

Success Criteria:

• Go service serves a web app at /.
• User can enter target role, stack, and interview timeline.
• User can create a diagnostic session from the browser.
• User can submit an answer and see typed grading feedback.
• UI has loading and error states for the diagnostic flow.

Phase 8: Learning Progress View

Goal: Show evidence-backed learning progress after practice.

Requirements: WEB-04

Success Criteria:

• User can see learner profile and concept mastery after answering.
• User can see readiness percentage and concept ladder state.
• User can see the next recommended challenge and its evidence.
• Empty states explain what to do before memory/progression exists.

Phase 9: Material and Asset Workspace

Goal: Let an operator use ontology and teaching asset prompt workflows from the web app.

Requirements: WEB-05, WEB-06, WEB-07, WEB-08

Success Criteria:

• Operator can ingest text material from the browser.
• Operator can inspect ontology candidate concepts, edges, and gaps.
• Operator can generate teaching asset prompt candidates from a concept.
• UI clearly shows candidate review state, source evidence, and model verification guard.

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Roadmap updated: 2026-04-26 after v2 Frontend MVP milestone start.