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CYB_029predictionAIcentralized-decentralized-schism

Corporate API providers will increasingly restrict third-party agent harnesses (exemplified by Anthropic's April 2026 ban of OpenClaw) — this structural conflict highlights the precarious nature of building autonomous enterprises atop proprietary APIs,...

Predictor: Anthropic

Prior probability
88.0%
Current probability
80.4%
evolves via intake + LBP
Conviction
4/5
Signal quality
B
Resolution
hit
Window
2026-01-01 – 2026-09-30
Edges in / out
3 / 0
Tickers exposed
17

Prediction text

Corporate API providers will increasingly restrict third-party agent harnesses (exemplified by Anthropic's April 2026 ban of OpenClaw) — this structural conflict highlights the precarious nature of building autonomous enterprises atop proprietary APIs, accelerating demand for local-model alternatives and vendor-neutral standards. | Next major API harness-restriction policy

Key catalyst: Next major API harness-restriction policy

Watch events: Next API-restriction policy at major lab; local-model enterprise adoption

Resolution evidence

Status: hit

Anthropic April 4, 2026 ban of OpenClaw / third-party harnesses documented; similar capacity-management moves across OpenAI, Google. Llama 4, DeepSeek local deployments accelerating.

Predictor: Anthropic

κ + Brier as of 2026-05-22
κ (discount)
0.583
Brier
0.0144
excellent
Hits / Misses
1 / 0
of 1 resolved
Hit rate
100.0%
Calibration plot (stated vs observed)

Evidence about this node from Anthropic 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

4 prob_history rows
0%25%50%75%100%prior 88%2026-04-292026-04-302026-05-03
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 80.4%

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 overdue ⏱
  1. 2026-01-30overdueQ1 window check-in (25%)
  2. 2026-03-01overdueQ2 window check-in (50%)
  3. 2026-03-30overdueQ3 window check-in (75%)

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: 80%)

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
LBP2026-05-03T02:00:01Z80.4%-1.3pp
Network propagation: 81.8% → 80.4%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
LBP2026-04-30T16:39:51Z81.8%-2.4pp
Network propagation: 84.1% → 81.8%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z84.1%-3.9pp
Network propagation: 88.0% → 84.1%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v1 · run 592311ef
resolution_terminal2026-04-29T22:23:18Z100.0%+18.2pp
resolution_terminal hit outcome=1.0 pre_resolution=0.818
Raw metadata
{
  "source": "backfill_resolution_history.py",
  "status": "hit",
  "bayesian_v2": false,
  "outcome_prob": 1,
  "evidence_kind": "resolution_terminal",
  "posterior_prob": 1,
  "delta_to_outcome": 0.18227000000000004,
  "inside_posterior": 0.81773,
  "validation_notes": "Anthropic April 4, 2026 ban of OpenClaw / third-party harnesses documented; similar capacity-management moves across OpenAI, Google. Llama 4, DeepSeek local deployments accelerating.",
  "validation_status": "hit",
  "pre_resolution_prob": 0.81773,
  "resolution_evidence": "Anthropic April 4, 2026 ban of OpenClaw / third-party harnesses documented; similar capacity-management moves across OpenAI, Google. Llama 4, DeepSeek local deployments accelerating.",
  "does_not_update_current_prob": true
}

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
killerTK01
AGI Capability Plateau (2026-27 Training Stall)
15.0%0.0500.880-0.049
killerTK06
China-Taiwan Military Conflict
8.0%0.0500.880+0.009
killerTK11
Autonomous Regulatory Block (Level 4 Halt)
10.0%0.0500.880-0.007

Top outgoing (children)

Predictions THIS node influences

No outgoing edges.

Ticker exposure

17 ticker(s) linked

Beneficiaries (13)

BBAISOUNAINVDAGTLBORCLMSFTAMZNGOOGLIBMMETAPLTRSHOP

Adverse (4)

UBERALLPGRTRV

Prerequisites (3)

Predictions that must hit first
TypePredTitleDomainLag
killerTK01AGI Capability Plateau (2026-27 Training Stall)
killerTK11Autonomous Regulatory Block (Level 4 Halt)
killerTK06China-Taiwan Military Conflict

Dependents (0)

Predictions enabled by this
TypePredTitleDomainLag
No dependents

Validations (1)

Resolution events
Observed atStatusByNotes
2026-04-29hitthesis_timeline_v1.0_importAnthropic April 4, 2026 ban of OpenClaw / third-party harnesses documented; similar capacity-management moves across OpenAI, Google. Llama 4, DeepSeek local deployments accelerating.

Linked documents (10)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.688arxivAgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Securitymentionspending2026-05-28
0.677github_releaseanthropics/anthropic-sdk-python v0.100.0mentionspending2026-05-06
0.667arxivPragLocker: Protecting Agent Intellectual Property in Untrusted Deployments via Non-Portable Promptsmentionspending2026-05-07
0.662github_releaseanthropics/anthropic-sdk-python v0.98.0mentionspending2026-05-04
0.660arxivWill the Agent Recuse Itself? Measuring LLM-Agent Compliance with In-Band Access-Deny Signalsmentionspending2026-06-04
0.652arxivShort paper: Models in the dark -- Rectification and erasure under GDPR in ML supply chainsmentionspending2026-06-04
0.635arxivGhost Tool Calls: Issue-Time Privacy for Speculative Agent Toolsmentionspending2026-06-01
0.616github_releasefacebookresearch/hydra v1.0.5mentionspending2021-01-07
0.610manifoldAnthropic Removes Claude Code From Every Plan Except Max in 202644%mentionspending2026-04-23
0.608github_releasemeta-llama/llama-api-python v0.4.0mentionspending2025-09-17

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "mode": "OBSERVATION+FORECAST",
  "role": "Cited-Firm",
  "context": "Observed policy precedent with forward implications. Couples with CYB_003 (Moltbook), CYB_004 (AAIF), AI_015 (Last Economy decentralization).",
  "to_year": 2028,
  "conv_cues": "specific named policy precedent; structural thesis",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "2026 ongoing",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -3,
      "source_id": null,
      "expected_date": "2026-01-30",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -2,
      "source_id": null,
      "expected_date": "2026-03-01",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -1,
      "source_id": null,
      "expected_date": "2026-03-30",
      "observed_date": null,
      "miss_emitted_at": "2026-05-02T22:07:21.384228+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "event",
      "label": "Corporate API providers will increasingly restrict third-party agent harnesses (exemplified by Anthropic's April 2026 ban of OpenClaw) — thi",
      "status": "hit",
      "weight": 1,
      "ordinal": 0,
      "source_id": "CYB_029",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    }
  ],
  "repeat_eps": 1,
  "affiliation": "Anthropic",
  "attribution": "CITED",
  "granularity": "YEAR",
  "resolved_at": "2026-04-29T22:23:18.248903+00:00",
  "source_refs": "9",
  "target_date": "2027-06-15T00:00:00",
  "display_date": "2026-04-29",
  "episode_date": "2026-04-21T00:00:00",
  "key_catalyst": "Next major API harness-restriction policy",
  "parse_method": "YEAR endpoint",
  "domain_bucket": "AI",
  "episode_title": "Convergence of Synthetic Cognition: Agents, Memory, Commerce & Cybersecurity (2023-2026)",
  "fault_line_id": "F001, F002, F006",
  "flag_repeated": false,
  "in_5yr_window": true,
  "source_report": "AI Cyber and Memory Predictions Request.md (2026-04-21)",
  "appears_in_eps": "CYB-RPT",
  "futurist_phase": "Phase 1 (2026)",
  "is_macro_claim": false,
  "total_mentions": 1,
  "priority_weight": 4,
  "ps_cluster_tags": [
    "C5",
    "C6"
  ],
  "report_evidence": "Anchor section: Centralized Orchestration vs Decentralized Proliferation.",
  "active_end_month": "2026-12",
  "recent_statement": "Anthropic usage policy update April 2026.",
  "watch_events_raw": "Next API-restriction policy at major lab; local-model enterprise adoption",
  "months_from_today": 14,
  "probability_layer": "Higher (in-flight)",
  "active_start_month": "2026-01",
  "december_dispersal": {
    "reason": "december_dispersal: domain=AI → 09/2026",
    "new_date": "2026-09-30",
    "old_date": "2026-12-31",
    "applied_at": "2026-04-30T16:28:34.304992+00:00"
  },
  "flag_nia_bracketed": false,
  "resolved_at_source": "validations_observed_at",
  "track_record_grade": "A-",
  "track_record_notes": "Anthropic policy-adjustment pattern predictable.",
  "contradicting_notes": "Corporate APIs remain dominant for enterprise deployment; local-model quality gap persists for frontier capabilities.",
  "flag_near_term_2027": false,
  "flag_high_conviction": false,
  "milestones_derived_at": "2026-05-02T03:08:50.798980+00:00",
  "reference_class_match": {
    "decision": "keyword_filtered",
    "computed_at": "2026-04-30T01:49:13.796883+00:00",
    "best_id_unfiltered": "