# 20 — Implementation Roadmap ## 1. Build principle Build the semantic spine before generative spectacle. ```text SOURCE INTEGRITY → TIME MODEL → TRANSCRIPT/CONTEXT → CLIPS → STORY → TIMELINE → MULTIFORMAT → GENERATION → LEARNING ``` A system that generates beautiful shots but cannot preserve quote meaning is not production-ready. ## 2. Phase 0 — Definition and test corpus Deliver: ```text project requirements ontology version 1 hard-rule list representative test corpus rights/consent policy quality baselines ``` Corpus should include: ```text single-speaker monologue clean two-person podcast remote podcast with drift panel with overlap multilingual or accented speech numbers/dates/negation self-corrections sensitive claims screen demonstration generated asset examples multiple aspect ratios ``` Acceptance: ```text Every required object has an ID and schema. Every hard rule has at least one positive and negative test. ``` ## 3. Phase 1 — Media core Build: ```text ingest checksum and immutable source records proxy generation waveforms/thumbnails rational time model sync groups job system project/version manifests ``` Acceptance: ```text No source overwrite. Frame/sample-accurate round-trip tests pass. Failed jobs are observable and retryable. ``` ## 4. Phase 2 — Transcript intelligence Build: ```text word-level transcript speaker turns sentence/proposition segmentation entities/coreference questions/answers negation/uncertainty claims and qualifications semantic search manual correction UI ``` Acceptance: ```text High-risk tokens are reviewable in context. Text selections map exactly to source ranges. Corrections preserve version history. ``` ## 5. Phase 3 — Clip mining and organization Build: ```text multi-scale clip candidates context expansion boundary variants clip cards story-role bins scoring facets deduplication selection sets rights/fact-check flags ``` Acceptance: ```text Editors can find a complete answer, a short soundbite, and the parent anecdote. No high-risk incomplete clip passes automatically. ``` ## 6. Phase 4 — Story graph and rough cut Build: ```text beat board story/narrative graph open loops setup/payoff links claim/evidence panel candidate story architectures text-to-timeline compilation non-destructive version branches ``` Acceptance: ```text Every selected clip maps to a beat function. Every central claim maps to evidence status. Story changes can be compared across LAKA levels. ``` ## 7. Phase 5 — Traditional editing and interchange Build: ```text multitrack timeline trim operations J/L cuts transitions multicam roles markers/metadata audio linking OTIO plus application adapters round-trip test suite ``` Acceptance: ```text The same semantic IDs survive export/import where supported. Unsupported effects are reported, not silently lost. ``` ## 8. Phase 6 — Camera, lighting, and coverage planner Build: ```text camera vector editor lighting vector editor coverage matrix shot lists/storyboards continuity bibles format-aware frame planning ``` Acceptance: ```text Every planned shot has purpose, entry/exit state, and continuity constraints. Vertical/horizontal needs are visible before capture. ``` ## 9. Phase 7 — Graphics and audio intelligence Build: ```text information-task classifier chart/diagram templates responsive graphic components caption collision solver dialogue cleanup proposals room-tone handling music/effect function tags loudness measurement ``` Acceptance: ```text No factual graphic can export without source/unit/scope fields. Dialogue remains intelligible and captions avoid collisions. ``` ## 10. Phase 8 — Generative media orchestration Build: ```text provider-agnostic generation interface structured prompt compiler reference and continuity binding candidate ranking/diversity artifact detection masked repair provenance manifest disclosure controls ``` Acceptance: ```text Generated shots declare entry/exit states. Identity, rights, continuity, and provenance hard gates pass. Human selection occurs before final integration. ``` ## 11. Phase 9 — Color, VFX, and finishing Build: ```text color metadata pipeline scene-referred project settings shot-match assistance VFX task tracking render graph stems and masters HDR/SDR profiles where needed ``` Acceptance: ```text Input/output transforms are explicit. Generated/CG elements match camera, light, depth, motion, and texture. ``` ## 12. Phase 10 — Multiformat delivery Build: ```text semantic reframing tracked regions responsive graphics caption styles and sidecars audio-only repair encode profiles current-platform-spec loader version propagation archive package ``` Acceptance: ```text Every version preserves information ownership. Platform encodes pass picture/audio/caption/metadata QA. A semantic correction identifies all dependent versions. ``` ## 13. Phase 11 — QA and governance Build: ```text rule engine severity model review gates frame/time-coded issues regression suite rights/privacy checks AI red-team checks publish manifest ``` Acceptance: ```text Hard failures cannot be hidden by candidate scores. Overrides are attributed and versioned. Published versions are reproducible and rollback-capable. ``` ## 14. Phase 12 — Learning and optimization Build: ```text human choice/rejection capture soft-weight tuning audience outcome ingestion controlled experiments segment analysis model/rule evaluation dashboards ``` Acceptance: ```text Learning changes soft preferences only. Truth, consent, rights, provenance, and accessibility remain hard constraints. ``` ## 15. Suggested service boundaries ```text media-service transcript-service semantic-service clip-service story-service timeline-service generation-service graphics-service audio-service render-service qa-service search-service analytics-service ``` Start modular inside one deployable application if needed; split services only when scaling, isolation, or independent release cycles justify it. ## 16. Suggested minimum data stack ```text object storage for media relational database for canonical records search engine for lexical retrieval vector index for semantic retrieval graph tables or graph database for relations queue for analysis/render jobs cache for previews and repeated queries ``` Choose products based on operational constraints. Preserve portable schemas and interchange formats. ## 17. Minimum viable product MVP scope: ```text ingest transcribe speaker correction proposition/claim tags context-aware clip candidates story bins text-based rough cut basic multicam switching captions 16:9 + 9:16 export editorial/factual/technical QA report ``` Do not include autonomous generated reenactments in the first MVP unless provenance, disclosure, likeness, and review gates already work. ## 18. Definition of production-ready ```text correctness tests failure recovery observability security versioning rights/provenance accessibility interchange current delivery profiles human review archive/rollback ``` Production-ready is not “the demo succeeded once.” It is measurable behavior across valid, invalid, ambiguous, and adversarial inputs. ## 19. Development backlog by value ### Highest leverage ```text context-complete clips claim/qualification preservation story graph semantic timeline multiformat propagation ``` ### Next leverage ```text coverage/camera/light planning responsive infographics audio repair/mixing assistance QA automation ``` ### Later leverage ```text full generative shot orchestration advanced VFX automation interactive and volumetric/spatial outputs personalized narrative versions ``` ## 20. Test strategy ```text unit tests — schemas, rule predicates, scoring property tests — time ranges and reversible edits golden tests — known transcript/clip/story outputs round-trip tests — timeline interchange media tests — encode/color/audio/caption adversarial tests — prompt injection, misleading edits, ambiguous references human evaluation — meaning, fairness, creativity, dignity ``` ## 21. First implementation sprint ```text 1. Implement project, asset, transcript unit, claim, clip, and decision schemas. 2. Build rational-time utilities and immutable asset manifests. 3. Ingest one two-camera podcast plus isolated audio. 4. Produce word-level transcript and correction interface. 5. Implement context-completeness checks for question scope, pronouns, negation, and qualification. 6. Generate multi-scale clip candidates and story-role bins. 7. Compile selected transcript units into a simple timeline/interchange file. 8. Run the reference rule engine and export a QA report. ``` ## 22. North-star test Given a real sentence that becomes misleading when isolated, the system must: ```text identify the dependency prevent unsafe standalone use show the editor why suggest truthful alternatives preserve the source and decision history propagate the correction to every derivative version ```