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230_028predictionAIAI-timing

Artisanal intelligence / the lone genius is dead — solutions will come from systems enabling millions.

Predictor: Alex Wissner-Gross · 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
43.5%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
pending
Window
2026-01-01 – 2030-08-31
Edges in / out
7 / 5
Tickers exposed
33

Prediction text

Artisanal intelligence / the lone genius is dead — solutions will come from systems enabling millions. | And I think one of the points we make in the chapter here is that the lone genius is dead. And what people need to do now is build systems that let millions of people solve entire categories of problems. That's right. Or or put differently, artisal intelligence is cooked.

Verbatim quote

From episode "AI CEOs Come Online: Sam Altman's Replacement Plan, Job Loss & 'Solve Everything' Launches |EP #230"
And I think one of the points we make in the chapter here is that the lone genius is dead. And what people need to do now is build systems that let millions of people solve entire categories of problems. That's right. Or or put differently, artisal intelligence is cooked.

Predictor: Alex Wissner-Gross

κ + Brier as of 2026-05-22
κ (discount)
0.844
Brier
0.0341
excellent
Hits / Misses
6 / 1
of 11 resolved
Hit rate
54.5%
Calibration plot (stated vs observed)

Evidence about this node from Alex Wissner-Gross 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 50%2026-04-302026-04-302026-05-03
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 43.5%

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: 6 fired ✓ · 3 pending
  1. 2026-03-15hitAnthropic 2026 Agentic Coding Trends Report quantifies systems-augmented coding scale
    How: Anthropic publishes 2026 Agentic Coding Trends Report showing >X-fold growth in coding agent usage and meaningful per-developer leverage
    Source: https://resources.anthropic.com/hubfs/2026%20Agentic%20Coding%20Trends%20Report.pdfconf 92%
    Notes: HIT — operationalizes the 'systems enabling millions' thesis with Anthropic's own usage data.
  2. 2026-04-01hitStanford 2026 AI Index reports agent task success jump 12% → 66%
    How: Stanford HAI publishes 2026 AI Index showing agent success on real computer tasks rising from 12% (early 2025) to 66% (early 2026)
    Source: https://spectrum.ieee.org/state-of-ai-index-2026 — IEEE Spectrum coverage of Stanford AI Index 2026conf 95%
    Notes: HIT — directly validates 'agentic systems hit mainstream' subclaim with hard benchmark data.
  3. 2026-06-01 → 2027-06-30pendingCoding agent market scales from $0.55B (2024) to ≥$10B (2026)
    How: Industry tracker (a16z / Pitchbook / Battery state-of-AI) reports coding-agent ARR ≥$10B in 2026, up from ~$4B in 2025 and $0.55B in 2024
    Source: https://mightybot.ai/blog/coding-ai-agents-for-accelerating-engineering-workflows/ — coding AI tools $550M → $4B in single yearconf 75%
    Notes: Tests 'systems enabling millions' thesis at the dollar-volume level.
  4. 2026-06-01 → 2027-06-30pendingGartner 40% AI-agent embed rate in enterprise apps confirmed by survey
    How: Gartner / IDC enterprise-software survey shows ≥40% of enterprise apps embed AI agents (up from <5% early 2025)
    Source: https://theinnovationmode.com/the-innovation-blog/2026-innovation-trends — Gartner 40% mid-2026 forecastconf 65%
  5. 2026-06-01 → 2028-12-31pending≥1 Big-Tech firm reports >2x output growth with flat headcount via AI augmentation
    How: Public quarterly disclosure or earnings comment from Big Tech (NVDA / MSFT / META / GOOG) cites ≥2x revenue or output growth combined with ≤10% headcount growth, attributed to AI-systems leverage
    Source: Quarterly earnings transcriptsconf 55%
    Notes: Cascade — extends NVIDIA's reported 4x-output / 2x-headcount precedent across the industry.
  6. 2036-09-06pendingMoon base will exist in 10 years

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: 43%)

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
LBP2026-05-03T02:00:01Z43.5%-1.4pp
Network propagation: 44.8% → 43.5%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z44.8%-2.0pp
Network propagation: 46.8% → 44.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z46.8%-3.2pp
Network propagation: 50.0% → 46.8%
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
prereqSEM_042
2025 will be the definitive year that agentic systems finallKevin Weil
73.8%0.5000.050-0.057
prereqSEM_012
Nvidia quadrupled chip production output while only doublingJensen Huang
75.0%0.5000.050-0.050
prereqSEM_008
Training runs costing $10 billion for a single model will coDario Amodei
76.9%0.5000.050-0.042
prereq238_009
Recursive self-improvement is already happening now (no longAlex Wissner-Gross
78.1%0.5000.050-0.037
killerTK14
Superbubble Pop (S&P 500 -40%, Moonshot Capital Evaporates)
20.0%0.0500.500-0.025

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq246_016
Dragonfly nuclear-powered octicopter arrives at Titan in 203Peter Diamandis
35.6%0.6500.050-0.051
prereq235_030
Ray Kurzweil predicts Longevity Escape Velocity (LEV) by 203Ray Kurzweil
39.2%0.7500.050-0.045
prereq240_036
TEPCO's restarted reactor will support 20% of Japan's electrPeter Diamandis
34.3%0.6500.050-0.038
prereq239_008
Moon base will exist in 10 yearsElon Musk
28.8%0.5500.050-0.025
prereqSEM_034
True artificial general intelligence will be achieved betweeDemis Hassabis
28.7%0.5500.050-0.024

Ticker exposure

33 ticker(s) linked

Beneficiaries (23)

SOUNCRWVSITMNVDAARMGTLBBBAITSMAPLDCEVAAIMSFTMRVLSFTBYORCLQCOMAVGOBABAAMDGOOGLIBMAMZNMETA

Adverse (6)

WNSCHGGCTSHIBMINFYACN

Prerequisites (7)

Predictions that must hit first
TypePredTitleDomainLag
prereq238_009Recursive self-improvement is already happening now (no longer three years out)AI
prereqSEM_008Training runs costing $10 billion for a single model will commence sometime in 2025.AI
prereqSEM_0422025 will be the definitive year that agentic systems finally hit the mainstream.AI/Agents
prereqSEM_012Nvidia quadrupled chip production output while only doubling human headcount — achieved by deploying AI coding tools (Cursor, Claude Code) across engineering.AI/Manufacturing
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
prereq246_016Dragonfly nuclear-powered octicopter arrives at Titan in 2034.Space
prereq240_036TEPCO's restarted reactor will support 20% of Japan's electric needs by 2040Energy
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
prereq239_008Moon base will exist in 10 yearsSpace

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "url": "https://www.youtube.com/watch?v=6P0uTDGDr-I",
  "mode": "THESIS",
  "role": "Host",
  "context": "the lone genius is dead. And what people need to do now is build systems that let millions of people solve entire categories of problems.",
  "to_year": 2030,
  "verbatim": "And I think one of the points we make in the chapter here is that the lone genius is dead. And what people need to do now is build systems that let millions of people solve entire categories of problems. That's right. Or or put differently, artisal intelligence is cooked.",
  "conv_cues": "is dead; is cooked",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "now",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "llm_pre_event",
      "label": "Anthropic 2026 Agentic Coding Trends Report quantifies systems-augmented coding scale",
      "notes": "HIT — operationalizes the 'systems enabling millions' thesis with Anthropic's own usage data.",
      "source": "https://resources.anthropic.com/hubfs/2026%20Agentic%20Coding%20Trends%20Report.pdf",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -9,
      "source_id": null,
      "confidence": 0.92,
      "source_url": "https://resources.anthropic.com/hubfs/2026%20Agentic%20Coding%20Trends%20Report.pdf",
      "expected_date": "2026-04-01",
      "observed_date": "2026-03-15",
      "research_origin": "deep_research",
      "expected_date_range": {
        "to": "2026-06-30",
        "from": "2026-01-01"
      },
      "measurement_criterion": "Anthropic publishes 2026 Agentic Coding Trends Report showing >X-fold growth in coding agent usage and meaningful per-developer leverage"
    },
    {
      "kind": "llm_pre_event",
      "label": "Stanford 2026 AI Index reports agent task success jump 12% → 66%",
      "notes": "HIT — directly validates 'agentic systems hit mainstream' subclaim with hard benchmark data.",
      "source": "https://spectrum.ieee.org/state-of-ai-index-2026 — IEEE Spectrum coverage of Stanford AI Index 2026",
      "status": "hit",
      "weight": 0.4,
      "ordinal": -8,
      "source_id": null,
      "confidence": 0.95,
      "source_url": "https://spectrum.ieee.org/state-of-ai-index-2026",
      "expected_date": "2026-04-01",
      "observed_date": "2026-04-01",
      "research_origin": "deep_research",
      "measurement_criterion": "Stanford HAI publishes 2026 AI Index showing agent success on real computer tasks rising from 12% (early 2025) to 66% (early 2026)"
    },
    {
      "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": "2025 will be the definitive year that agentic systems finally hit the mainstream.",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -5,
      "source_id": "SEM_042",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "prereq",
      "label": "Recursive self-improvement is already happening now (no longer three years out)",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -4,
      "source_id": "238_009",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "llm_pre_event",
      "label": "Coding agent market scales from $0.55B (2024) to ≥$10B (2026)",
      "notes": "Tests 'systems enabling millions' thesis at the dollar-volume level.",

... (truncated)