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244_008predictionOtherAI-timing

If you build liquid supply with product-market fit, demand will show up

Predictor: Dara Khosrowshahi · ep#244 "Uber's Robotaxi Playbook, End of Human Driving & $10B Bet on Robots | Dara Khosrowshahi (Uber CEO)" · source

Prior probability
60.0%
Current probability
52.9%
evolves via intake + LBP
Conviction
4/5
Signal quality
C
Resolution
pending
Window
— – —
Edges in / out
3 / 0
Tickers exposed
33

Prediction text

If you build liquid supply with product-market fit, demand will show up | And if you build liquid supply, if you have product market fit fit to some extent, the demand just shows up.

Verbatim quote

From episode "Uber's Robotaxi Playbook, End of Human Driving & $10B Bet on Robots | Dara Khosrowshahi (Uber CEO)"
And if you build liquid supply, if you have product market fit fit to some extent, the demand just shows up.

Predictor: Dara Khosrowshahi

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0105
excellent
Hits / Misses
2 / 0
of 3 resolved
Hit rate
66.7%
Calibration plot (stated vs observed)

Evidence about this node from Dara Khosrowshahi is multiplied by κ in /api/intake. Lower κ = less weight; floors at 0.10 (effectively silenced) and caps at 1.00 (full weight).

Reference class

Not linked

This node isn't linked to a reference class. The Bayesian update applies without outside-view blending.

Probability over time

3 prob_history rows
0%25%50%75%100%prior 60%2026-04-302026-04-302026-05-03
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 52.9%

Milestone chain

Pre-event signals (upstream prereqs + window checkpoints) → resolution event → downstream cascades. Status/dates update from linked nodes; re-derive nightly via scripts/ops/derive_milestones.py.
Leading chain: 3 pending
  1. 2026-05-01 → 2027-12-31pendingMarketplace SaaS/two-sided unit-economics report supports liquid-supply→demand causation
    How: Andreessen Horowitz, NFX, or Bessemer marketplace report cites Uber as exemplar of liquid-supply-creates-demand pattern with quantitative case study
    Source: a16z marketplace reports, NFX Manual, Bessemer Marketplace Indexconf 80%
  2. 2026-12-31 → 2027-12-31pendingUber driver supply continues growth ≥10% YoY 2026-2027
    How: Uber 10-K reports active monthly drivers grow ≥10% YoY 2026 vs 2025 — confirming 'liquid supply' thesis
    Source: Uber Inc. annual reports (10-K), DAU/MAPC disclosuresconf 75%
  3. 2026-05-01 → 2028-12-31pendingCounter-example: marketplace where supply scaling did NOT trigger demand
    How: ≥1 high-profile marketplace failure where reported high-quality liquid supply did NOT generate proportional demand (e.g., late-stage Q-commerce, vertical SaaS marketplace failure)
    Source: Crunchbase failed-startup tracker, Pitchbook, TechCrunch closuresconf 85%
    Notes: Tests boundary of Khosrowshahi's claim — supply alone is necessary but not always sufficient.

No downstream cascades — this prediction is a leaf in the dependency graph.

What if this resolves?

Clamp this prediction TRUE or FALSE and run a counterfactual Gibbs sample. Surfaces the predictions whose marginals shift most under that assumption.
(live posterior: 53%)

Click a button to clamp this prediction and run a Gibbs sample. Returns the predictions whose marginals shift most. ~30s per run; ideal for stress-testing "if X resolves, what else moves?"

Evidence chain

Every probability update with full Bayesian provenance — chronological, latest first
LBP2026-05-03T02:00:01Z52.9%-1.1pp
Network propagation: 54.0% → 52.9%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z54.0%-2.1pp
Network propagation: 56.0% → 54.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z56.0%-4.0pp
Network propagation: 60.0% → 56.0%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef

Network propagation neighbors

Top edges sorted by latest LBP cross-impact
All propagation →

Top incoming (parents)

Edges that influence THIS node's belief

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
killerTK14
Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
20.0%0.0500.600-0.039
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.600+0.016
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.600-0.011

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (3)

Predictions that must hit first
TypePredTitleDomainLag
killerTK14Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.618polymarketLoL: Team Liquid vs Shopify Rebellion (BO5) - LCS Playoffs99%mentionspending2026-05-25
0.617polymarketLoL: Team Liquid vs Shopify Rebellion - Game 1 Winner100%mentionspending2026-05-25
0.617polymarketLoL: Team Liquid vs Shopify Rebellion - Game 2 Winner100%mentionspending2026-05-25
0.616polymarketLoL: Team Liquid vs Cloud9 (BO3) - LCS Regular Season0%mentionspending2026-05-11
0.611polymarketLoL: Team Liquid vs Cloud9 - Game 2 Winner0%mentionspending2026-05-11
0.610polymarketLoL: LYON vs Team Liquid (BO3) - LCS Regular Season49%mentionspending2026-05-04
0.609manifoldWill this market appear on a mug?26%mentionspending2026-05-06
0.609polymarketGame Handicap: TL (-2.5) vs Shopify Rebellion (+2.5)81%mentionspending2026-05-25
0.607polymarketCounter-Strike: BIG vs Liquid (BO1) - IEM Cologne Major Stage 155%mentionspending2026-05-16
0.605polymarketLoL: Team Liquid vs Cloud9 - Game 1 Winner0%mentionspending2026-05-11

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=Mh9yC4j0_rI",
  "mode": "THESIS",
  "role": "Guest-CEO",
  "caveats": "Conditional on product-market fit",
  "context": "put real tools in place to become kind of the easiest to use and the most liquid as it relates to supply. And then if you if you do have product market fit, the demand will show up.",
  "verbatim": "And if you build liquid supply, if you have product market fit fit to some extent, the demand just shows up.",
  "conv_cues": "demand just shows up",
  "direction": "HAPPEN",
  "timeframe": "Ongoing",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Marketplace SaaS/two-sided unit-economics report supports liquid-supply→demand causation",
      "source": "a16z marketplace reports, NFX Manual, Bessemer Marketplace Index",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -3,
      "source_id": null,
      "confidence": 0.8,
      "expected_date": "2027-03-01",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2027-12-31",
        "from": "2026-05-01"
      },
      "measurement_criterion": "Andreessen Horowitz, NFX, or Bessemer marketplace report cites Uber as exemplar of liquid-supply-creates-demand pattern with quantitative case study"
    },
    {
      "kind": "llm_pre_event",
      "label": "Uber driver supply continues growth ≥10% YoY 2026-2027",
      "source": "Uber Inc. annual reports (10-K), DAU/MAPC disclosures",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.75,
      "expected_date": "2027-07-01",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2027-12-31",
        "from": "2026-12-31"
      },
      "measurement_criterion": "Uber 10-K reports active monthly drivers grow ≥10% YoY 2026 vs 2025 — confirming 'liquid supply' thesis"
    },
    {
      "kind": "llm_pre_event",
      "label": "Counter-example: marketplace where supply scaling did NOT trigger demand",
      "notes": "Tests boundary of Khosrowshahi's claim — supply alone is necessary but not always sufficient.",
      "source": "Crunchbase failed-startup tracker, Pitchbook, TechCrunch closures",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -1,
      "source_id": null,
      "confidence": 0.85,
      "expected_date": "2027-08-31",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2028-12-31",
        "from": "2026-05-01"
      },
      "measurement_criterion": "≥1 high-profile marketplace failure where reported high-quality liquid supply did NOT generate proportional demand (e.g., late-stage Q-commerce, vertical SaaS marketplace failure)"
    }
  ],
  "repeat_eps": 1,
  "untimeable": true,
  "affiliation": "Uber",
  "attribution": "FIRST_PERSON",
  "episode_num": 244,
  "granularity": "VAGUE",
  "episode_date": "2026-04-02",
  "parse_method": "UNMAPPABLE",
  "domain_bucket": "Other",
  "episode_title": "Uber's Robotaxi Playbook, End of Human Driving & $10B Bet on Robots | Dara Khosrowshahi (Uber CEO)",
  "fault_line_id": "F001, F002, F003",
  "flag_repeated": false,
  "in_5yr_window": false,
  "appears_in_eps": "244",
  "is_macro_claim": false,
  "total_mentions": 1,
  "priority_weight": 4,
  "ps_cluster_tags": [
    "C2",
    "C3",
    "C5"
  ],
  "active_end_month": 0,
  "untimeable_reason": "philosophical business principle ('build supply, demand follows')",
  "active_start_month": 0,
  "flag_nia_bracketed": false,
  "track_record_grade": "B+",
  "track_record_notes": "Uber CEO; 'drivers increase not decrease' 2030 call is counterintuitive but has been accurate on Uber's trajectory 2017-2026.",
  "flag_near_term_2027": false,
  "flag_high_conviction": true,
  "milestones_phase2_at": "2026-05-02T03:20:39.366665+00:00",
  "reference_class_match": {
    "decision": "keyword_filtered",
    "computed_at": "2026-04-30T01:49:13.796883+00:00",