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Enhance Planning AI with Roadmap-First Architecture and New Features
- Introduced a roadmap-first approach for the planning AI, allowing for a structured progression graph that aligns with the overall project roadmap.
- Added new functionality to strip off-topic steps from exercise paths, improving the relevance of generated exercise suggestions.
- Implemented a detailed goal text generation for AI proposals, enhancing the context provided for new exercises.
- Updated the ExerciseProgressionPathBuilder component to support new features, including roadmap previews and improved focus area handling.
- Incremented application version to 0.8.205 and updated database schema version to 20260606086 to reflect these changes.
2026-06-08 08:10:53 +02:00

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# Planungs-KI — Produkt-Roadmap
**Stand:** 2026-06-07
**App-Version:** ab **0.8.204** — maßgeblich `backend/version.py`
Diese Roadmap ergänzt die **Architektur-Refaktor-Roadmap** (`UMSETZUNGSPLAN_ROADMAP.md`) und gilt **nur für KI-gestützte Trainingsplanungsunterstützung**.
**Leit-Spec:** `.claude/docs/working/PLANNING_PROGRESSION_ROADMAP_SPEC.md`
---
## Strategische Entscheidung (verbindlich)
1. **Progressionsgraph:** Planung **vom Ziel rückwärts** (Roadmap-first), nicht Bibliothek-first.
2. **Keine Gruppenanalyse** im Graphen — Kontext = Zieltext, Thema, Schrittanzahl, optional Graph-Kanten.
3. **Trainingsplanung** (Einheit, Rahmen, Abschnitt): eigene Pipeline später, **mit** Gruppenkontext — siehe `AI_PLANNING_KI_MULTISTAGE_FORECAST.md` S0S4.
4. **Orchestrierung:** Workflow-**lite** jetzt (`planning_progression_roadmap.py`); Mitai Workflow-Engine **später**, wenn 23 Pipelines stabil sind.
---
## Phasen-Übersicht
| Phase | Domäne | Kurzbeschreibung | Status |
|-------|--------|------------------|--------|
| P0P2 | Übungssuche | Kontext-Pack, Hybrid-Score, LLM-Rerank | ✅ |
| AC2 | Übungssuche | Voll-Library, Graph, Varianten | ✅ |
| C3 | Progressionsgraph | Pfad-Builder (retrieval-first) | ✅ |
| EE3 | Progressionsgraph | Semantik, QA, Lücken-Angebote | ✅ |
| **F0F1** | Progressionsgraph | Roadmap-Pipeline Scaffold + API-Preview | 🔄 **0.8.204** |
| **F2F4** | Progressionsgraph | LLM Roadmap, roadmap-first Retrieval, UI Review | 🔲 |
| D | Übungs-Neuanlage | `planning_context` an `suggestExerciseAi` | 🔲 |
| G | Trainingsplanung | Kontext-Pack Gruppe/Historie, S0S4 | 🔲 |
| H | Plattform | Mitai-Workflow-Engine (optional) | 🔲 Backlog |
---
## Phase F — Progressions-Roadmap (aktiver Fokus)
### F0 — Foundation (0.8.204)
- [x] Spec `PLANNING_PROGRESSION_ROADMAP_SPEC.md`
- [x] Modul `planning_progression_roadmap.py` (Pydantic, Pipeline-Skeleton)
- [x] Migration **078** Prompt-Slugs (Zielanalyse, Roadmap)
- [x] API: `include_roadmap_preview` auf `progression-path-suggest`
- [x] Doku: HANDOVER, PLANNING_EXERCISE_SUGGEST_CONTEXT, MULTISTAGE_FORECAST
### F1 — Deterministische Roadmap
- [x] Phase A aus Semantic Brief
- [x] Phase B: `micro_objectives` aus `development_arc` + Konsolidierung auf N
- [x] Phase C: heuristische `stage_specs`
- [ ] pytest für Konsolidierung
### F2 — LLM Roadmap (0.8.205)
- [x] Prompts **078/079** in `ai_prompts` — Code nur Slugs (`PROMPT_SLUG_*`)
- [x] `include_llm_roadmap` + `load_and_render_ai_prompt` + JSON-Validierung
- [x] Deterministischer Fallback wenn Prompt/OpenRouter fehlt
- [ ] Response/UI: genutzte `prompt_slugs` sichtbar machen (Admin-Hinweis)
### F3 — roadmap-first
- [ ] Retrieval pro `major_step` + `stage_spec` statt iterativem Pfad-Bau
- [ ] QA/Lücken an Roadmap koppeln
### F4 — UI
- [ ] Roadmap-Review im `ExerciseProgressionPathBuilder`
- [ ] Major Steps editierbar vor Übungs-Match
---
## Abhängigkeiten
| Von | Nach | Hinweis |
|-----|------|---------|
| F2 | Enrichment / Skills | Bessere Roadmap bei technikspezifischen Skills |
| F3 | F2 | LLM-Roadmap oder stabile heuristische B |
| G | F4 | Trainingsplanung kann Roadmap aus Graph referenzieren |
| H | G + F4 | Workflow-Engine lohnt bei verzweigten Planungsflows |
---
## Pflege
Bei Abschluss einer Teilphase: diese Datei, `HANDOVER.md` §2.8, `PLANNING_EXERCISE_SUGGEST_CONTEXT.md` §24, Changelog in `version.py`.