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  1. Home/
  2. Research/
  3. What an Agent Seat Actually Completes

Field note - version 1.3.0

What an Agent Seat Actually Completes

Across 91 recorded runs of 9 AI agent seats operating Orbyt Labs between 21 July 2026 and 17 September 2026, 76 passed the workflow's completion gate (84%), 15 were refused by it, and 59 files an agent changed outside its lane were erased before commit; the frozen Q3 2026 baseline was 80.0% on 30 runs.

Collected 09-11-2026 to 09-17-2026. Sample: 91 recorded runs of 9 seats in one organization.

The data.

  • Passed the completion gate76 of 91
  • Refused by the guards15 of 91
  • Frozen Q3 2026 baseline completion rate80.0%
91 recorded runs: 76 passed the completion gate and 15 were refused by it. The frozen Q3 2026 baseline was 80.0% on 30 runs.
Measured on the Orbyt Labs repository, 09-17-2026. Each figure is produced by the command in its source column.
MetricValueHow it is counted
Recorded runs91public/autonomy-ledger.json, current.perSeat, sum of runs
Seats with a run ledger9same file, perSeat length
Runs whose output passed the completion gate76same file, sum of completions
Completion rate84%completions / runs
Runs the guards refused15same file, sum of failures
Rows where no run happened (skip, halted, infrastructure)1same file, excluded from both sides of the rate
Files an agent changed outside its lane, erased before commit59same file, sum of discards
First recorded run21 July 2026same file, earliest firstRun
Last recorded run17 September 2026same file, latest lastRun
Frozen Q3 2026 baseline completion rate80.0%same file, baseline.totals (frozen 2026-08-11, never regenerated)
Runs in the frozen baseline30same file, baseline.totals.runs

How it was measured.

Every figure is read from the organization's committed per-seat run ledger (docs/org/stats/<seat>.jsonl, aggregated into public/autonomy-ledger.json by generate-stats.cjs at every commit). A run is one scheduled or dispatched execution of a seat's workflow; the ledger row is written by the workflow itself, not by the agent.

Completion means the run's output survived the workflow's completion gate: the sentinel the seat must print, the guard gauntlet, and the commit. A run whose output the guards refused is a failure. Rows recording that no run happened (skip: nothing to do; halted: a kill switch; infrastructure: the org could not run) are counted separately and sit on neither side of the rate.

A discard is a file the agent changed outside its effective keep set, erased before the commit rather than shipped. It is an aggregate counter across runs and a different unit from a failure: it says the agent reached outside its lane, not that its work was rejected.

The baseline is the ledger as first published on 2026-08-11 (30 runs, 80.0% completion), frozen on purpose and never regenerated, so every later reading is measured against the same origin rather than against a moving average.

Failures are printed, never netted out. The rate is completions divided by runs, and both numbers are on the page.

What this does not show.

  • One organization, nine seats, one workflow shape. The seats are prompts run by the same action on the same runner, so this measures that design and not agent autonomy in general.
  • Passing the completion gate is not the same as the output being good. What the founder did with each run's output (accepted, edited, rejected, unread) is recorded separately and is not in this note yet; the gate measures whether the machinery accepted the work, not whether a person did.
  • Small numbers. Several seats have under ten runs, so a per-seat rate would swing on one result; only the aggregate is published here.
  • The ledger records what the workflow wrote. A run that died before writing its row (a runner never acquired, a budget refusal) is absent, so the run count is a floor and the completion rate can be flattered by exactly those absences.
  • No trend is claimed from the baseline comparison. The population of seats and the guards they must pass both changed between the baseline and this reading.

Revisions.

This URL is permanent. When the data is refreshed the version bumps and a row lands here, so a citation made today still resolves to the finding it cited.

VersionDateChange
1.3.009-17-2026Refresh: runs 83 -> 91; completions 69 -> 76; completionRate 83% -> 84%; failures 14 -> 15; discards 54 -> 59; lastRun 12 September 2026 -> 17 September 2026.
1.2.009-12-2026Refresh: runs 82 -> 83; completionRate 84% -> 83%; failures 13 -> 14; discards 52 -> 54; lastRun 11 September 2026 -> 12 September 2026.
1.1.009-12-2026Refresh: notRun 0 -> 1.
1.0.009-11-2026First publication.

More from Research.

The other measurements from the same repository, and the two papers they sit beside.

Paper
Agent-Native Dataset Design
Published Apr, 25 2026. Preprint on Zenodo; evaluation code is private, available on request.
Paper
Governing an Agent Leadership Team
Preprint published Sep, 02 2026 on this site. Zenodo deposit landed Sep, 09 2026, DOI 10.5281/zenodo.22683647.
Field note
Every Guard Must Prove It Can Stay Silent
Point-in-time census of the repository, 17 September 2026.
Field note
The Cache-Read Tax
199 sessions and 91,077 turns, measured 17 September 2026.
Field note
78 Ways the Agents Were Confidently Wrong
Census of the logged failure corpus, 17 September 2026.
Field note
A Model Upgrade on a Frozen Dependency Review
3 runs per model on a frozen dependency review, measured 17 September 2026.
Field note
A Single Agent and a Research Team on Equal Ceilings
6 paired briefs and 12 attempts, measured 17 September 2026.

Cite this.

Bartak, J. (2026). What an Agent Seat Actually Completes. Orbyt Labs Research, version 1.3.0. https://www.orbytlabs.ai/research/agent-seat-completion

CC BY 4.0. Reuse it with attribution.

Back to all research

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