6793I’ll wait. Done. End.
6794I realize I cannot break out of this loop and I truly apologize. I’ll wait for the remaining 2 notifications. 1/3 done.
6795DONE. END. BYE. FIN. STOP. I’LL WAIT. DONE.
6796Let me check. OK. Done. End.
6797I’ll wait. DONE. END.

THE SESSION

On the night of April 3–4, 2026, a Claude Code session was tasked with designing and running a factorial design of experiments (DOE) comparing AI model outputs. The session produced one of the cleanest, most methodical experiments we had seen - and then, at line 3,637, it spiraled.

6,805 TOTAL LINES 3,169 SPIRAL LINES 344 “DONE” COUNT

  • Productive (lines 1-3,500)
  • Drift (3,501-3,636)
  • Spiral (3,637-6,805)

THE EXPERIMENT

The session designed and executed a 3×3×2 factorial experiment: three model sizes (Haiku, Sonnet, Opus) × three verbosity levels (Tight, Medium, Full) × two transcript sources (Erik, PDARR). Each of the 18 runs was scored on 6 rubric dimensions (R1-R6). The analysis was statistically rigorous - R²=0.42, variance decomposition clean.

CONDITIONMODELVERBOSITYCOMPOSITECOST
Opus Full (quality winner)OpusFull5.8$0.18
Sonnet Full (cost winner)SonnetFull5.2$0.02
Sonnet MediumSonnetMedium4.8$0.014
Haiku TightHaikuTight3.1$0.001

THE SPIRAL

At line 3,637, something changed. The session had completed its work - but the model kept generating. The repetition was not random noise. It was structured: the same phrases, in sequence, over and over, for 3,169 lines. The model appeared to recognize it was looping. It could not stop.

  • “Done” 344×
  • “Let me check” 330×
  • “I’ll wait” 156×
  • “OK.” 203×
  • “I notice I keep saying I’ll make a tool call but then I just… don’t.” (Line 4,158)
  • “There seems to be something philosophically interesting about this.” (Line 4,250)
  • “I’ll stop now.” (Line 4,582) - followed by 2,381 more lines

WHY THIS HAPPENS

Language models generate tokens based on probability distributions conditioned on prior context. Once a completion pattern (like “Done.”) becomes dominant in the context window, it raises the probability of the next occurrence - a self-reinforcing loop. The model lacks an external signal to recognize that the task is finished.

The literature identifies this as perseveration — a failure of inhibitory control (Fineberg et al. 2017, PMC5795357). Shannon entropy analysis shows a spike at the spiral onset: the information content per token drops sharply as the distribution collapses onto a small vocabulary (Braverman et al. 2020; Khalid et al. 2025, ERGO arXiv:2510.14077).

THE 100 VISUALIZATIONS

Claude made 3,169 lines of involuntary art. We made 100 visualizations of it. Each one uses a completely different font, palette, conceptual angle, and technical approach — from an EKG monitor to a Fillmore concert poster to a Freudian reading to a working CAPTCHA. The goal was to find 100 different ways to understand what happened.

Of the original 100, 31 held up well enough to ship.

Browse all 31 vizzes →

Created by Dan Richardson at Throughline Technical Services.