← Cockpit
CMQ_005predictionAIsoftware-automation

AI will handle the entire software development process end-to-end within 6-12 months (by late 2026) — humans relegated to reviewer/editor role.

Predictor: Dario Amodei

Prior probability
68.0%
Current probability
55.9%
evolves via intake + LBP
Conviction
5/5
Signal quality
A
Resolution
pending
Window
2026-01-01 – 2027-10-31
Edges in / out
2 / 1
Tickers exposed
0

Prediction text

AI will handle the entire software development process end-to-end within 6-12 months (by late 2026) — humans relegated to reviewer/editor role. | Claude Code + Devin-class agent maturity

Key catalyst: Claude Code + Devin-class agent maturity

Watch events: Agentic SWE benchmarks (SWE-bench, Terminal-bench); CS hiring data; Big Tech engineer headcount trajectories.

Resolution evidence

Status: pending

Claude Code + Cursor + Cognition Devin already handling substantial portions of SDLC; autonomous PR-merging agents in production at major firms 2026.

Predictor: Dario Amodei

κ + Brier as of 2026-05-22
κ (discount)
0.688
Brier
0.0363
excellent
Hits / Misses
1 / 0
of 3 resolved
Hit rate
33.3%
Calibration plot (stated vs observed)

Evidence about this node from Dario Amodei 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: ai_capability_milestone_2y

Linked

AI reaches specific named capability (intern-level / world-class programmer / etc) within 2y of stated target

Base rate
5/15 historical
Inside weight
Outside weight
no pull
inside 55.9% → blend 55.9% 0.0pp)

Tetlock-style outside view: at TRF=1 (just predicted), outside view dominates (w_in=0.3). At TRF=0 (deadline), inside view dominates (w_in=1.0). The blend regularizes overconfident inside views toward the historical base rate.

Probability over time

8 prob_history rows
0%25%50%75%100%prior 68%2026-04-302026-05-102026-05-24
intake v2milestone miss sweeplbp propagationreference class assignedlegacy v1prior_prob (analyst seed)current = 55.9%

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: 1 fired ✓ · 1 overdue ⏱ · 7 pending
  1. 2026-05-04overdueQ1 window check-in (25%)
  2. 2026-04-01 → 2026-09-30pendingSWE-Bench Verified hits 90%+ score
    How: Top model score on SWE-Bench Verified reaches ≥90% on the public leaderboard (current top is in the 70-80% range as of late 2025)
    Source: Anthropic blog, OpenAI evals page, Papers With Code SWE-Bench page, METR evaluationsconf 75%
    Notes: SWE-Bench Verified is the canonical 'AI handling software dev' benchmark. 90% indicates near-human performance on real GitHub issues.
  3. 2026-09-04pendingQ2 window check-in (50%)
  4. 2026-06-01 → 2026-12-31pendingAI agent demonstrates ≥1 workday autonomous task completion
    How: Public demo or third-party evaluation (METR, Apollo Research) shows an AI agent (Devin-class, Claude Code-class) completing tasks requiring ≥8 hours of senior-engineer work without human intervention
    Source: Anthropic blog, Cognition (Devin) blog, METR.org evaluations, Apollo Research reportsconf 65%
    Notes: METR's 'task length' evaluation is the canonical agent-autonomy metric.
  5. 2026-07-01 → 2027-04-30pendingMajor tech company discloses majority of new code is AI-generated
    How: Public statement (earnings call, blog, internal memo leak) from top-5 tech company (Microsoft, Google, Meta, Amazon, Apple) that >50% of new code is AI-generated. Or developer survey shows similar at industry level.
    Source: Earnings call transcripts, GitHub Octoverse report, Stack Overflow Developer Survey, Microsoft/Google blog postsconf 55%
    Notes: Sundar Pichai stated 25%+ at Google in Oct 2024. Trajectory implies 50%+ within 2 years.
  6. 2027-01-05pendingQ3 window check-in (75%)
  7. 2026-10-01 → 2027-10-31pendingSoftware dev employment showing measurable AI-driven shift
    How: BLS quarterly data shows software developer employment growth turns negative for two consecutive quarters, OR named layoff announcements totaling ≥50,000 cite AI code automation as primary driver
    Source: Bureau of Labor Statistics quarterly reports, layoffs.fyi, Bloomberg labor coverageconf 45%
    Notes: Cascade — affects S_AGI_FAST/MID and labor displacement predictions.
  8. 2026-12-01 → 2027-08-31pendingFrontier lab announces human-out-of-loop production code
    How: Anthropic, OpenAI, Google, or peer announces a major production system where AI writes, reviews, AND deploys code with humans only in oversight role (no human PR review on majority of changes)
    Source: Lab blog posts, conference keynotes (NeurIPS, ICML, OpenAI DevDay), Reuters/Bloombergconf 50%

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: 56%)

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
LBP2026-05-24T02:00:02Z55.9%-5.3pp
Network propagation: 61.2% → 55.9%
4-iter LBP, residual 0.01000 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 806b02f8
intake_event_update2026-05-21T23:15:16Z61.2%+10.9pp
intake:7afeeb9a-f217-4dd2-b910-24ff14bdfc39 bayesian_v2 inside=0.612 blend=0.612 LLR=0.446 κ=0.64 no_blend
Raw metadata
{
  "trf": 0.7889686596425205,
  "kappa": 0.6429,
  "base_rate": null,
  "predictor": "Dario Amodei",
  "total_llr": 0.6931471805599453,
  "bayesian_v2": true,
  "prior_logit": 0.01024395655895965,
  "bayes_factor": "1.6:1 favoring",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.5025609667444139,
  "kappa_source": "predictor_table",
  "blend_applied": false,
  "contributions": [
    {
      "llr": 0.6931471805599453,
      "kappa": 0.6429,
      "label": "End-to-end software automation closer than skeptics estimated.",
      "adjusted_llr": 0.4456243223819888
    }
  ],
  "evidence_kind": "intake_event_update",
  "inside_source": "history_v2",
  "inside_weight": 1,
  "outside_weight": 0,
  "posterior_prob": 0.6120335605622316,
  "evidence_origin": "daily_intake",
  "llm_suggestions": [
    {
      "polarity": "corroborates",
      "status_change": "unchanged",
      "evidence_strength": "moderate",
      "delta_prob_suggestion": 0.04
    }
  ],
  "posterior_logit": 0.4558682789409485,
  "predictor_brier": 0.03445,
  "evidence_doc_ids": [],
  "inside_posterior": 0.6120335605622316,
  "blended_posterior": 0.6120335605622316,
  "reference_class_id": null,
  "total_adjusted_llr": 0.4456243223819888,
  "predictor_n_resolved": 2
}
metadata_milestone_miss_sweep2026-05-12T22:09:45Z50.3%-6.5pp
metadata_milestone_miss_sweep bayesian_v2 n=1 inside=0.503 blend=0.503 LLR=-0.261 κ=0.64 no_blend
Raw metadata
{
  "trf": 0.8025098155804883,
  "kappa": 0.6429,
  "base_rate": null,
  "predictor": "Dario Amodei",
  "total_llr": -0.4054651081081644,
  "grace_days": 7,
  "bayesian_v2": true,
  "prior_logit": 0.2709174745616987,
  "bayes_factor": "1.3:1 against",
  "blend_reason": "no reference_class linked",
  "inside_prior": 0.5673181297530249,
  "kappa_source": "predictor_table",
  "n_milestones": 1,
  "blend_applied": false,
  "contributions": [
    {
      "llr": -0.4054651081081644,
      "kind": "quartile_checkpoint",
      "kappa": 0.6429,
      "label": "Q1 window check-in (25%)",
      "weight": 0.05,
      "strength": "weak",
      "confidence": null,
      "source_url": null,
      "adjusted_llr": -0.2606735180027389,
      "expected_date": "2026-05-04",
      "measurement_criterion": null
    }
  ],
  "evidence_kind": "metadata_milestone_miss_sweep",
  "inside_source": "history_v2",
  "inside_weight": 0.43824312909365815,
  "outside_weight": 0.5617568709063419,
  "posterior_prob": 0.5025609667444139,
  "posterior_logit": 0.010243956558959766,
  "predictor_brier": 0.03445,
  "inside_posterior": 0.5025609667444139,
  "blended_posterior": 0.5025609667444139,
  "reference_class_id": null,
  "total_adjusted_llr": -0.2606735180027389,
  "predictor_n_resolved": 2
}
LBP2026-05-10T02:00:02Z56.7%-5.8pp
Network propagation: 62.5% → 56.7%
6-iter LBP, residual 0.00584 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run e5c18d29
LBP2026-05-03T02:00:01Z62.5%-9.6pp
Network propagation: 72.1% → 62.5%
6-iter LBP, residual 0.00677 · damping 0.5, w_intrinsic 0.5 · method lbp_v3 · run 1a683ac9
legacy v12026-04-30T19:17:54Z72.1%+9.8pp
intake:99aa73db-75b1-4b1e-8470-a11f87b23937 bayesian_v2 inside=0.721 blend=0.721 LLR=0.446 κ=0.64 no_blend
LBP2026-04-30T16:39:51Z62.4%-2.1pp
Network propagation: 64.4% → 62.4%
5-iter LBP, residual 0.00825 · damping 0.5, w_intrinsic 0.5 · method lbp_v2 · run 0c8a4ea3
LBP2026-04-30T02:18:57Z64.4%-3.6pp
Network propagation: 68.0% → 64.4%
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
prereq238_009
Recursive self-improvement is already happening now (no longAlex Wissner-Gross
78.1%0.6800.050-0.023

Top outgoing (children)

Predictions THIS node influences

KindNodeTheir probP(c|s=T)P(c|s=F)Δ implied
prereq234_036
Job displacement will be issue 6-10 not top 5 in 10 years; AAlex Wissner-Gross
28.8%0.4500.050-0.026

Prerequisites (2)

Predictions that must hit first
TypePredTitleDomainLag
prereq238_009Recursive self-improvement is already happening now (no longer three years out)AI
correlateS_AGI_MID_2029AGI mid: Kurzweil 2029 pathagi_general_capability

Dependents (1)

Predictions enabled by this
TypePredTitleDomainLag
prereq234_036Job displacement will be issue 6-10 not top 5 in 10 years; AI discoveries will dominateLabor/Jobs

Linked documents (5)

Auto-generated by cosine similarity from Polymarket / Manifold / EDGAR / GDELT
SimSourceTitleMarket probPolarityReviewedPublished
0.750codex_research_packMETR - Measuring AI Ability to Complete Long Taskscorroboratespending2025-03-19
0.750codex_research_packOECD - Exploring Possible AI Trajectories Through 2030corroboratespending2026-04-26
0.670arxivAutomating Low-Risk Code Review at Meta: RADAR, Risk Calibration, and Review Efficiencymentionspending2026-05-28
0.617arxivWhen Surface Form Changes Moderation Decisions: A Paired Study of Code-Mixed Workflow Instabilitymentionspending2026-06-04
0.589manifoldWill MNX hire a backend developer before Manifest?26%mentionspending2026-04-30

Raw metadata

From Thesis_Timeline_v1.0_FINAL workbook
{
  "nia": false,
  "qty": "end-to-end SWE",
  "mode": "FORECAST",
  "role": "Cited-CEO",
  "context": "Amodei early-2026 forecast; goes beyond code assistants to full SDLC autonomy. Structurally disrupts engineering labor economics.",
  "to_year": 2027,
  "conv_cues": "will be; CEO; specific timeframe",
  "direction": "HAPPEN",
  "from_year": 2026,
  "timeframe": "6-12 months (by late 2026)",
  "conv_level": "HIGH",
  "milestones": [
    {
      "kind": "prereq",
      "label": "Recursive self-improvement is already happening now (no longer three years out)",
      "status": "hit",
      "weight": 0.5,
      "ordinal": -9,
      "source_id": "238_009",
      "expected_date": "2026-04-29",
      "observed_date": "2026-04-29"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q1 window check-in (25%)",
      "status": "overdue",
      "weight": 0.05,
      "ordinal": -8,
      "source_id": null,
      "expected_date": "2026-05-04",
      "observed_date": null,
      "miss_emitted_at": "2026-05-12T22:09:45.491809+00:00",
      "miss_emitted_by": "metadata_milestone_sweep"
    },
    {
      "kind": "llm_pre_event",
      "label": "SWE-Bench Verified hits 90%+ score",
      "notes": "SWE-Bench Verified is the canonical 'AI handling software dev' benchmark. 90% indicates near-human performance on real GitHub issues.",
      "source": "Anthropic blog, OpenAI evals page, Papers With Code SWE-Bench page, METR evaluations",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -7,
      "source_id": null,
      "confidence": 0.75,
      "expected_date": "2026-07-01",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2026-09-30",
        "from": "2026-04-01"
      },
      "measurement_criterion": "Top model score on SWE-Bench Verified reaches ≥90% on the public leaderboard (current top is in the 70-80% range as of late 2025)"
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q2 window check-in (50%)",
      "status": "pending",
      "weight": 0.05,
      "ordinal": -6,
      "source_id": null,
      "expected_date": "2026-09-04",
      "observed_date": null
    },
    {
      "kind": "llm_pre_event",
      "label": "AI agent demonstrates ≥1 workday autonomous task completion",
      "notes": "METR's 'task length' evaluation is the canonical agent-autonomy metric.",
      "source": "Anthropic blog, Cognition (Devin) blog, METR.org evaluations, Apollo Research reports",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -5,
      "source_id": null,
      "confidence": 0.65,
      "expected_date": "2026-09-15",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2026-12-31",
        "from": "2026-06-01"
      },
      "measurement_criterion": "Public demo or third-party evaluation (METR, Apollo Research) shows an AI agent (Devin-class, Claude Code-class) completing tasks requiring ≥8 hours of senior-engineer work without human intervention"
    },
    {
      "kind": "llm_pre_event",
      "label": "Major tech company discloses majority of new code is AI-generated",
      "notes": "Sundar Pichai stated 25%+ at Google in Oct 2024. Trajectory implies 50%+ within 2 years.",
      "source": "Earnings call transcripts, GitHub Octoverse report, Stack Overflow Developer Survey, Microsoft/Google blog posts",
      "status": "pending",
      "weight": 0.4,
      "ordinal": -4,
      "source_id": null,
      "confidence": 0.55,
      "expected_date": "2026-11-29",
      "research_origin": "training",
      "expected_date_range": {
        "to": "2027-04-30",
        "from": "2026-07-01"
      },
      "measurement_criterion": "Public statement (earnings call, blog, internal memo leak) from top-5 tech company (Microsoft, Google, Meta, Amazon, Apple) that >50% of new code is AI-generated. Or developer survey shows similar at industry level."
    },
    {
      "kind": "quartile_checkpoint",
      "label": "Q3 window check-in (75%)
... (truncated)