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Feature Prioritization

Phase: 6 — Product Project: likeness Date: 2026-05-09 Confidence: Medium-High on the prioritization logic; Low on absolute effort estimates (no engineering team in place yet to size accurately)


Method

Two complementary frames are applied:

  1. MoSCoW — drawn from the must-have / should-have / could-have / won't-have lists in mvp-definition.md. Tells the team what's optional vs. non-negotiable.
  2. RICE — applied to the must-have list to determine build order within the must-haves. RICE doesn't decide what's in MVP; that's a strategic call the must-have list already made. RICE decides what gets built first, second, third.

Effort is in T-shirt sizes (S = days, M = weeks, L = months, XL = multiple months). Concrete person-month numbers depend on team makeup; the relative ordering is what matters.

RICE rationale

For an MVP that must ship the full vertical slice, RICE is mostly used to decide which features the engineering team starts on first. Reach is essentially constant (every must-have affects the same concierge cohort), so the formula reduces to: prioritize by (Impact × Confidence) / Effort with ties broken by dependency order.

  • Reach = 100 (treating "all concierge users" as the unit; relative reach across must-haves is essentially equal)
  • Impact = 0.25 (minimal) / 0.5 (low) / 1 (medium) / 2 (high) / 3 (massive)
  • Confidence = 50% (low) / 80% (medium) / 100% (high)
  • Effort = T-shirt size mapped to person-weeks (S=2, M=8, L=20, XL=40)

Build order — must-haves (MVP)

Sorted by RICE descending. Build order is roughly top-to-bottom but adjusted for dependencies.

# Feature MoSCoW Impact Conf Effort RICE Notes
1 License engine: structured creator license object Must 3 100% M (8wk) 38 Foundation; everything depends on it
2 License-gated prompt parser + classifier Must 3 80% L (20wk) 12 Hardest single piece; ML + compliance jointly
3 Creator identity verification (3rd-party provider) Must 3 100% S (2wk) 150 Vendor integration; must be first to receive any creator
4 Per-creator LoRA training pipeline Must 3 80% L (20wk) 12 ML Lead's primary work in months 1-3
5 License-gated inference service Must 3 80% L (20wk) 12 Tightly coupled to feature 4
6 Audit log of every license decision Must 3 100% S (2wk) 150 Foundational for compliance and trust
7 2257 records system integration Must 3 100% M (8wk) 38 Vendor integration (Quick2257 or similar)
8 Multi-processor billing with auto-failover Must 3 80% L (20wk) 12 CEO-led BD then engineering; gating to launch
9 Watermark per output (invisible) Must 2 80% M (8wk) 20 Off-the-shelf at MVP, possibly custom layer in beta
10 Perceptual hash + signed metadata + license ID Must 2 100% S (2wk) 100 Standard cryptographic plumbing
11 Creator onboarding flow (the "three things to know" disclosure) Must 3 80% M (8wk) 30 Brand-aligned; voice work matters here
12 Subscription tier configuration Must 2 100% M (8wk) 25 Standard creator-platform feature
13 Compute credit purchase + consumption Must 3 80% M (8wk) 30 Tightly coupled to feature 8 (billing)
14 Fan generation interface Must 3 80% M (8wk) 30 Where the user-facing AI experience happens
15 Approval queue (creator-side) Must 2 80% M (8wk) 20 Creator-side workflow for fan submissions
16 Submission fee mechanic Must 1 80% S (2wk) 40 Lightweight; rides on credit and approval flows
17 PPV unlock of approved generations Must 1 80% M (8wk) 10 Standard creator-platform feature
18 Creator payout flow Must 3 80% M (8wk) 30 Multi-processor reconciliation
19 Revocation flow Must 3 100% M (8wk) 38 The brand-defining feature; UX must be confident
20 Face matching for output verification Must 2 80% M (8wk) 20 Identity-preservation enforcement
21 Pre-publication content review (creator-uploaded) Must 2 100% M (8wk) 25 Operational; T&S Lead operates, engineering enables
22 Hard-block category enforcement Must 3 100% M (8wk) 38 Classifier + deterministic rule + human escalation
23 Abuse detection on prompts and outputs Must 2 80% M (8wk) 20 Same classifier system as feature 22
24 Takedown intake + outbound takedown pipeline Must 2 80% M (8wk) 20 Required by TAKE IT DOWN Act; brand asset
25 Fan signup + subscription flow Must 2 100% S (2wk) 100 Standard
26 Creator dashboard (earnings, fan activity, audit log, license editor, revocation) Must 3 80% M (8wk) 30 The creator's day-to-day surface
27 Fan gallery / approved-content view per creator Must 1 100% S (2wk) 50 Standard
28 Distilled / accelerated inference variant (Flux Schnell or equivalent) Must 2 80% M (8wk) 20 Cost-side requirement; not at MVP launch but pre-cohort scale
29 C2PA-compliant content credentials Must 2 100% M (8wk) 25 Pre-launch; standard adoption
30 Fan age verification (US baseline) Must 2 100% S (2wk) 100 Regulatory baseline

Pure RICE order isn't shippable because some features depend on others. Suggested implementation phasing:

Phase A (months 1-3) — foundation 1. Creator identity verification (#3) — vendor integration, immediate 2. Audit log infrastructure (#6) — foundational for everything 3. Structured license object (#1) — the data model that everything else queries 4. 2257 records system (#7) — vendor integration in parallel with above 5. Per-creator LoRA training pipeline (#4) — ML Lead's primary work 6. Distilled inference variant (#28) — set up early to inform cost trade-offs 7. Watermark + perceptual hash + signed metadata (#9, #10, #29) — small ML/crypto work, can start early

Phase B (months 3-6) — vertical slice 8. License-gated prompt parser + classifier (#2) — the hardest piece; depends on #1 9. License-gated inference service (#5) — depends on #4 + #2 10. Hard-block category enforcement (#22) — same classifier system as #23, ship together 11. Abuse detection (#23) — see above 12. Face matching for output verification (#20) — depends on #5 13. Multi-processor billing (#8) — engineering after CEO secures relationships 14. Compute credit purchase + consumption (#13) — depends on #8 15. Subscription tier configuration (#12) — depends on #8 16. Fan signup + subscription flow (#25) — depends on #12 17. Fan age verification (#30) — vendor integration, in parallel 18. Fan generation interface (#14) — depends on #5 + #13

Phase C (months 6-9) — full product 19. Approval queue (#15) — creator workflow 20. Submission fee mechanic (#16) — rides on #15 + #13 21. PPV unlock of approved generations (#17) — rides on #15 22. Creator dashboard (#26) — pulls from #6, #1, #19 23. Fan gallery (#27) — pulls from #15 24. Creator payout flow (#18) — depends on #8 25. Revocation flow (#19) — touches every prior surface; ship after the rest is stable 26. Creator onboarding flow (#11) — built throughout but polished at end with brand voice 27. Pre-publication content review tooling (#21) — T&S Lead drives operationally 28. Takedown intake + outbound (#24) — required by TAKE IT DOWN Act 48-hour SLA

Phase A duration: ~3 months. Phase B: ~3 months. Phase C: ~3 months. MVP launch target: month 9.

This is faster than typical for a regulated category, and it depends on hiring all six founding seats by month 4 per the budget plan. Slip in any of those hires extends the timeline proportionally.

Should-haves — order if scope allows

These are not gating to MVP launch but should be sized into the engineering plan as soon as the must-haves clear Phase B:

Feature Impact Effort Reason in this tier
Custom requests / 1:1 messaging 1 M Creator carry-over expectation; absent at MVP creates friction
Creator-side analytics 2 M Helps creators optimize; partial visibility shipped at MVP via dashboard
Creator-side takedown monitoring (off-platform) 2 L Trust signal from Variation B; high-value but heavy
Tip / one-off fan transactions outside generation 1 S Creator-economy carry-over
Creator-controlled gallery curation (public / fan-tier / private) 1 S Granularity beyond fan tier visibility

Could-haves — only if trivial

Feature Notes
Per-output ratings / favoriting by creator Useful for future LoRA iteration; not load-bearing
Creator-set per-fan generation rate limits Beyond platform-level limits
Creator-to-creator messaging Cohort coordination; can be done in Discord at MVP
Theming / creator-side branding of fan surfaces Makes the platform feel less like a single-template platform; nice but not essential

Won't-haves (MVP, do not start)

Restated for scope discipline:

  • Video generation
  • Voice cloning
  • Fan self-insert tier
  • Public discovery / browse-creators
  • Open API / developer access
  • Mobile app store distribution
  • Unrestricted creator collaborations
  • Mainstream creator vertical (non-adult)
  • International (UK, EU, others)
  • Posting / open-network social features

Effort summary

T-shirt size summary across must-haves: - 7 × S features (~14 person-weeks) - 18 × M features (~144 person-weeks) - 5 × L features (~100 person-weeks) - 0 × XL features

Total: ~258 person-weeks ≈ 5 person-years of engineering for must-haves alone. This is consistent with the budget assumption of CTO + ML Lead + engineering hires in months 1-9, supplemented by T&S Lead and Compliance Lead doing operational rather than engineering work.

If this number looks high, it's because regulated categories require the full vertical slice. The alternative is shipping a half-built product that can't safely go in front of creators.

Dependencies between features

Critical paths to watch:

  • License engine (#1) blocks license-gated parser (#2), inference (#5), revocation (#19), audit logs (#6).
  • Multi-processor billing (#8) blocks credit purchase (#13), subscriptions (#12), payout (#18).
  • Identity verification (#3) and 2257 records (#7) block creator onboarding (#11) and pre-publication review (#21).
  • LoRA training pipeline (#4) blocks inference service (#5) which blocks fan generation (#14) and face matching (#20).

The hardest critical path: #1 → #2 → #5 → #14. License engine to license-gated parser to inference to fan generation. This is the primary engineering risk and should be the dedicated focus of the CTO + ML Lead through Phase B.


Strategic Connections

  • The build order assumes the budget hiring sequence in docs/budget.md (4 people in months 1-3, full team by month 4). Slip in the hiring sequence cascades into engineering delays.
  • The "ship the full vertical slice" discipline reflects the regulatory analysis in 01-discovery/raw/regulatory.md. Half-shipping is not safe in this category.
  • The MVP timeline (9 months from funding close to launch) aligns with the founder brief's concierge phase target and the validation experiments in 06-validation/validation-playbook.md.

Flags

Red Flags: - The MVP is ~9 months of engineering, not 8 weeks. Founder and investors should align on this expectation before pre-seed close. Selling a "concierge launch in Q4" requires Q1 funding close + immediate hires; selling "MVP at 6 months" misrepresents the build.

Yellow Flags: - All effort sizes are estimates without an engineering team in place. Once CTO and ML Lead are operating, re-size in week 2. - Feature #2 (license-gated prompt parser + classifier) is the single hardest piece. ML Lead should own this from day 1; it's the feature most likely to slip and most painful to slip.

Sources

  • 04-product/mvp-definition.md — feature list ground truth
  • docs/ml-lead-technical-brief.md — engineering effort context
  • docs/budget.md — hiring sequence
  • 01-discovery/raw/regulatory.md — compliance-feature grounding