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230_042predictionAIAI-timing

A pure AI organization will emerge soon — won't look efficient, will look 'literally alien'.

Predictor: Salim Ismail · ep#230 "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230" · source

Prior probability
50.0%
Current probability
39.6%
evolves via intake + LBP
Conviction
3/5
Signal quality
C
Resolution
pending
Window
2027-06-01 – 2027-06-30
Edges in / out
8 / 5
Tickers exposed
33

Prediction text

A pure AI organization will emerge soon — won't look efficient, will look 'literally alien'. | And I think what'll happen is we'll see a pure AI organization at some point soon, but they won't look efficient. They'll look literally alien and and that's fine. I think I it's one of these where you can't wait for it to happen.

Verbatim quote

From episode "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230"
And I think what'll happen is we'll see a pure AI organization at some point soon, but they won't look efficient. They'll look literally alien and and that's fine. I think I it's one of these where you can't wait for it to happen.

Predictor: Salim Ismail

κ + Brier as of 2026-05-22
κ (discount)
0.643
Brier
0.0144
excellent
Hits / Misses
1 / 0
of 2 resolved
Hit rate
50.0%
Calibration plot (stated vs observed)

Evidence about this node from Salim Ismail 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

5 prob_history rows
0%25%50%75%100%prior 50%2026-04-302026-05-032026-05-10
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 39.6%

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: 7 fired ✓ · 1 overdue ⏱ · 1 pending
  1. 2026-02-28hitSalesforce reduces customer-support headcount 9,000 to 5,000 via AI agents
    How: Salesforce Marc Benioff publicly confirms 9K to 5K headcount reduction in support, attributed to Agentforce — per CNBC/SaaStr/tech.co reporting
    Source: https://tech.co/news/companies-replace-workers-with-aiconf 95%
  2. 2026-03-19hitJensen Huang projects 100:1 AI-agents-to-humans ratio at NVIDIA in 10y
    How: Jensen Huang public statement (Fortune interview, GTC keynote) projecting 75K NVIDIA humans + 7.5M AI agents by ~2036 — explicit alien-organization vision
    Source: https://fortune.com/2026/03/19/jensen-huang-nvidia-ai-agents-future-of-work-autonomous/conf 95%
  3. 2026-03-01 → 2026-06-30overdueMcKinsey runs 20K AI agents alongside 40K humans (1:2 ratio)
    How: McKinsey publicly confirms ~20K agentic AI deployments running alongside human workforce, with internal goal of 1:1 within 18 months
    Source: https://www.cnbc.com/2026/02/23/ai-robots-outnumber-workers-agents-few-decades-citi.htmlconf 80%
  4. 2026-06-01 → 2027-06-30pendingFirst publicly named >50%-AI-employee company emerges with valuation >$100M
    How: Company files Series-B+ or media-disclosed funding round at >=$100M valuation explicitly marketing >50% of operational labor performed by AI agents (not just augmentation); per major outlet
    Source: https://www.sdggroup.com/en/insights/blog/agentic-ai-2026-from-assistants-to-high-productivity-digital-peersconf 55%
  5. 2027-01-01 → 2028-06-30pendingPure-AI company (zero human operational employees) emerges and operates >6 months
    How: Documented operational entity (LLC, B-corp, DAO) with zero human operational employees (founders not counted) that generates revenue >6 months continuously — per public reporting / regulatory filing
    Source: https://www.raconteur.net/technology/autonomous-ai-agents-2026-the-new-rules-for-business-governanceconf 40%
  6. 2027-09-01 → 2029-12-31pendingCascade: SEC / state regulator issues guidance on AI-only entity legal status
    How: SEC, Delaware Secretary of State, or similar regulator publishes formal guidance on legal/registration treatment of pure-AI entities (employer status, tax, securities, liability)
    Source: https://www.cio.com/article/4064998/taming-ai-agents-the-autonomous-workforce-of-2026.htmlconf 30%

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: 40%)

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
LBP2026-05-10T02:00:02Z39.6%+1.4pp
Network propagation: 38.1% → 39.6%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
metadata_milestone_miss_sweep2026-05-08T22:15:34Z38.1%-5.0pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.381 blend=0.381 LLR=-0.209 κ=0.64 no_blend
Raw metadata
{
  "trf": 1,
  "kappa": 0.6429,
  "base_rate": null,
  "predictor": "Salim Ismail",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": -0.2750009771404482,
  "bayes_factor": "1.2:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.4316797767975763,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "llm_pre_event",
      "kappa": 0.51432,
      "label": "McKinsey runs 20K AI agents alongside 40K humans (1:2 ratio)",
      "weight": 0.4,
      "strength": "weak",
      "confidence": 0.8,
      "source_url": null,
      "adjusted_llr": -0.2085388144021911,
      "expected_date": "2026-04-30",
      "measurement_criterion": "McKinsey publicly confirms ~20K agentic AI deployments running alongside human workforce, with internal goal of 1:1 within 18 months"
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.3,
  "outside_weight": 0.7,
  "posterior_prob": 0.38141660412452405,
  "posterior_logit": -0.48353979154263926,
  "predictor_brier": 0.01445,
  "inside_posterior": 0.38141660412452405,
  "blended_posterior": 0.38141660412452405,
  "reference_class_id": null,
  "total_adjusted_llr": -0.2085388144021911,
  "predictor_n_resolved": 2
}
LBP2026-05-03T02:00:01Z43.2%-1.5pp
Network propagation: 44.7% → 43.2%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z44.7%-2.2pp
Network propagation: 46.9% → 44.7%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z46.9%-3.1pp
Network propagation: 50.0% → 46.9%
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
killerTK03
AI Regulatory Moratorium (EU/US Capability Freeze)
10.0%0.0500.500+0.059
prereq234_012
Anthropic revenue will cross OpenAI revenue in middle of 202Peter Diamandis
67.1%0.5000.050-0.047
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.500+0.037
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.5000.050-0.018
prereq235_002
Anthropic will exceed OpenAI in revenue this year (2026).Dave Blundin
74.6%0.5000.050-0.014

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq241_043
ASI will arrive within 2 years to 5 years to this next decadPeter Diamandis
35.9%0.6500.050-0.068
prereqCMQ_002
By 2028, AI systems will reach 'independent researcher' leveSam Altman
31.4%0.5500.050-0.063
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050-0.061
prereq232_055
We're exiting the industrial age permanently as recursive sePeter Diamandis
35.5%0.7000.050-0.044
prereqSEM_034
True artificial general intelligence will be achieved betweeDemis Hassabis
28.7%0.5500.050-0.036

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (8)

Predictions that must hit first
TypePredTitleDomainLag
prereq235_002Anthropic will exceed OpenAI in revenue this year (2026).AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereq234_012Anthropic revenue will cross OpenAI revenue in middle of 2026Markets/Stocks
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
prereqSEM_0422025 will be the definitive year that agentic systems finally hit the mainstream.AI/Agents
killerTK14Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK03AI Regulatory Moratorium (EU/US Capability Freeze)

Dependents (5)

Predictions enabled by this
TypePredTitleDomainLag
prereq235_030Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 2033.Biotech/Longevity
prereq232_055We're exiting the industrial age permanently as recursive self-improvement unfolds.AI
prereq241_043ASI will arrive within 2 years to 5 years to this next decadeAI
prereqCMQ_002By 2028, AI systems will reach 'independent researcher' level — driving autonomous scientific discoveries without human intervention.AI
prereqSEM_034True artificial general intelligence will be achieved between 2032 and 2042 — 'first we solve AI, then use AI to solve everything else'.AI/AGI

Linked documents (1)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.601manifoldIf we survive the singularity, will the average guy be able to get a catgirl harem with almost zero effort?20%mentionspending2026-05-08

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=6P0uTDGDr-I",
  "mode": "PREDICTION",
  "role": "Host",
  "context": "I think what'll happen is we'll see a pure AI organization at some point soon, but they won't look efficient. They'll look literally alien",
  "to_year": 2028,
  "verbatim": "And I think what'll happen is we'll see a pure AI organization at some point soon, but they won't look efficient. They'll look literally alien and and that's fine. I think I it's one of these where you can't wait for it to happen.",
  "conv_cues": "I think; at some point soon",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "soon",
  "conv_level": "MEDIUM",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Salesforce reduces customer-support headcount 9,000 to 5,000 via AI agents",
      "source": "https://tech.co/news/companies-replace-workers-with-ai",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -9,
      "source_id": null,
      "confidence": 0.95,
      "expected_date": "2026-02-28",
      "observed_date": "2026-02-28",
      "research_origin": "deep_research",
      "measurement_criterion": "Salesforce Marc Benioff publicly confirms 9K to 5K headcount reduction in support, attributed to Agentforce — per CNBC/SaaStr/tech.co reporting"
    },
    {
      "kind": "llm_pre_event",
      "label": "Jensen Huang projects 100:1 AI-agents-to-humans ratio at NVIDIA in 10y",
      "source": "https://fortune.com/2026/03/19/jensen-huang-nvidia-ai-agents-future-of-work-autonomous/",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.95,
      "expected_date": "2026-03-19",
      "observed_date": "2026-03-19",
      "research_origin": "deep_research",
      "measurement_criterion": "Jensen Huang public statement (Fortune interview, GTC keynote) projecting 75K NVIDIA humans + 7.5M AI agents by ~2036 — explicit alien-organization vision"
    },
    {
      "kind": "prereq",
      "label": "Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) a",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -7,
      "source_id": "SEM_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Training runs costing $10 billion for a single model will commence sometime in 2025.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -6,
      "source_id": "SEM_008",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic revenue will cross OpenAI revenue in middle of 2026",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -5,
      "source_id": "234_012",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Anthropic will exceed OpenAI in revenue this year (2026).",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -4,
      "source_id": "235_002",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "2025 will be the definitive year that agentic systems finally hit the mainstream.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -3,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "McKinsey runs 20K AI agents alongside 40K humans (1:2 ratio)",
      "source": "https://www.cnbc.com/2026/02/23/ai-robots-outnumber-workers-agents-few-decades-citi.html",
      "status": "overdue",
      "weight": 0.4,
      "ordinal": -2,
      "source_id": null,
      "confidence": 0.8,
      "expected_date": "2026-04-30",
      "miss_emitted_at": "2026-05-08T22:15:34.476563+00:00",
      "miss_emitted_by": "metadata_mile
... (truncated)