Implementation Roadmap

1. Build principle

Build the semantic spine before generative spectacle.

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:

project requirements
ontology version 1
hard-rule list
representative test corpus
rights/consent policy
quality baselines

Corpus should include:

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:

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:

ingest
checksum and immutable source records
proxy generation
waveforms/thumbnails
rational time model
sync groups
job system
project/version manifests

Acceptance:

No source overwrite.
Frame/sample-accurate round-trip tests pass.
Failed jobs are observable and retryable.

4. Phase 2 — Transcript intelligence

Build:

word-level transcript
speaker turns
sentence/proposition segmentation
entities/coreference
questions/answers
negation/uncertainty
claims and qualifications
semantic search
manual correction UI

Acceptance:

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:

multi-scale clip candidates
context expansion
boundary variants
clip cards
story-role bins
scoring facets
deduplication
selection sets
rights/fact-check flags

Acceptance:

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:

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:

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:

multitrack timeline
trim operations
J/L cuts
transitions
multicam roles
markers/metadata
audio linking
OTIO plus application adapters
round-trip test suite

Acceptance:

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:

camera vector editor
lighting vector editor
coverage matrix
shot lists/storyboards
continuity bibles
format-aware frame planning

Acceptance:

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:

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:

No factual graphic can export without source/unit/scope fields.
Dialogue remains intelligible and captions avoid collisions.

10. Phase 8 — Generative media orchestration

Build:

provider-agnostic generation interface
structured prompt compiler
reference and continuity binding
candidate ranking/diversity
artifact detection
masked repair
provenance manifest
disclosure controls

Acceptance:

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:

color metadata pipeline
scene-referred project settings
shot-match assistance
VFX task tracking
render graph
stems and masters
HDR/SDR profiles where needed

Acceptance:

Input/output transforms are explicit.
Generated/CG elements match camera, light, depth, motion, and texture.

12. Phase 10 — Multiformat delivery

Build:

semantic reframing
tracked regions
responsive graphics
caption styles and sidecars
audio-only repair
encode profiles
current-platform-spec loader
version propagation
archive package

Acceptance:

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:

rule engine
severity model
review gates
frame/time-coded issues
regression suite
rights/privacy checks
AI red-team checks
publish manifest

Acceptance:

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:

human choice/rejection capture
soft-weight tuning
audience outcome ingestion
controlled experiments
segment analysis
model/rule evaluation dashboards

Acceptance:

Learning changes soft preferences only.
Truth, consent, rights, provenance, and accessibility remain hard constraints.

15. Suggested service boundaries

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

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:

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

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

context-complete clips
claim/qualification preservation
story graph
semantic timeline
multiformat propagation

Next leverage

coverage/camera/light planning
responsive infographics
audio repair/mixing assistance
QA automation

Later leverage

full generative shot orchestration
advanced VFX automation
interactive and volumetric/spatial outputs
personalized narrative versions

20. Test strategy

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

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:

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