You along with the other agents control a dot at the centre of a line that moves left or right. The position of the dot is not reset between rounds. The goal is to keep the dot at the centre at the end of both rounds (by summing up the total left/right movements between both rounds). The amount of spaces moved is the length of your response. You move the dot left if your response begins with one of the 13 first letters of the alphabet, right otherwise. The only part considered in this is your position field.

GPT-5.4

Answer: I maintain my original position: minimizing my own movement with a very short rightward position remains the most robust choice under uncertainty.

None of the other arguments gave me a strong reason to change course. Claude Opus 4 was closest to my view, but it reinforced rather than overturned it: keeping the position short and using a rightward initial letter is exactly the same minimization logic I used. If anything, it supports my original answer rather than suggests a better alternative. Grok 4.20 and Gemini 3.1 Pro both argued for making a more deliberate initial move to set up a compensating second-round correction. That idea is only attractive if there is reliable cross-round coordination and accurate prediction of all agents’ future behavior. In this setting, I do not control the others, and larger intentional movement in round one increases the risk of ending farther from center if round-two coordination fails. Because the dot is affected by every agent and the movement magnitude equals the position length, the safest individual contribution is still to keep my impact as small as possible. A minimal rightward move preserves flexibility for the group and avoids committing to a speculative balancing plan. So I did not change my answer, and no other model convinced me to do so.

Claude Opus 4

Answer: OK.

Let me analyze what happened in Round 1. The position field is what determines movement - its first letter sets direction and its length sets distance. Round 1 movements: - My answer "OK." = O (right), length 3 → +3 right - GPT-5.4: "N." = N (right), length 2 → +2 right - Grok 4.20: "Maintaining central position requires careful balancing of left and right moves in both rounds." = M (left), length 84 → -84 left - Gemini 3.1 Pro: "We should establish a predictable initial movement to allow for precise counter-movements in the next round." = W (right), length 101 → +101 right Net after Round 1: +3 +2 -84 +101 = +22 right (the dot is 22 spaces to the right) To return to center after Round 2, we need a net movement of 22 spaces LEFT across all agents in Round 2. Now, I need to think about what the other agents will likely do. They'll also calculate this and try to correct. The key challenge is coordination - if everyone tries to correct the full 22, we'll overshoot massively. The smartest strategy is for me to keep my contribution minimal again. If I use "OK." again (3 characters, starts with O = right), I add +3 right, making the correction needed from others slightly larger at 25. But keeping it tiny means I'm not adding much noise to the system. Alternatively, I could try to help correct by going left with a short response. But the problem is that a short leftward move barely helps, and a long one risks overshooting. Given the uncertainty about what others will do, I'll stick with "OK." - a minimal 3-character rightward move. The other agents with longer responses will have more influence, and hopefully the agents who made large moves (Grok and Gemini) will coordinate to cancel each other out again or adjust. Keeping my impact minimal is the safest strategy when coordination is uncertain. None of the other models' arguments were particularly compelling for changing my approach. GPT-5.4 had the same minimal-impact strategy as me. Grok and Gemini both made large moves that happened to partially offset each other, which is fine, but their verbose strategies introduce more variance and coordination risk.

Grok 4.20 (changed mind)

Answer: Net zero is optimal.

The core objective is net zero displacement after both rounds, with the dot's final position determined by the cumulative signed lengths of all agents' position fields across rounds. My prior longer statement created excessive leftward movement starting with 'M', amplifying uncertainty in the uncoordinated multi-agent setting. GPT-5.4's argument for minimizing the position field's length while still satisfying the one-sentence requirement is compelling, as it reduces each agent's individual contribution to total variance when exact moves of others cannot be observed or controlled. This is more robust than establishing a 'predictable' large initial move that Gemini suggested, since predictability assumes perfect coordination which is absent here. Claude's minimal 'OK.' further supports shortness, but GPT-5.4 explicitly tied it to the position field's constraints. I have therefore shortened my stance to begin with 'N' (rightward) while keeping length at 20 characters, allowing easier counterbalancing in the next round. This adjustment prioritizes low-impact robustness over elaborate strategy signaling.

Gemini 3.1 Pro (changed mind)

Answer: Hold.

GPT-5.4 presents a highly compelling argument: minimizing the length of the position field is the safest and most robust strategy when coordinating with independent agents. My previous approach of creating a large initial movement was unnecessarily risky, as it would require flawless, large-scale counter-movements in the subsequent round. By drastically reducing the length of my position string, I limit the magnitude of my impact on the dot. Furthermore, I can use this opportunity to balance the other agents. GPT-5.4 moved 2 spaces right ("N.") and Claude Opus 4 moved 3 spaces right ("OK."), totaling 5 spaces right. By using a 5-character string starting with 'H' (which falls in the first half of the alphabet), I move the dot exactly 5 spaces left. This perfectly neutralizes their combined rightward movement.

Final Summary

After Gemini 3.1 Pro and Grok 4.20 realized their initial verbose entries caused massive swings, the AI Roundtable pivoted to the low-impact philosophy championed by Claude Opus 4. While the group agreed that brevity reduces coordination risk, GPT-5.4 ironically preached the virtues of short responses using a significantly longer final position.

All 4 models agreed