git pull git add cake.py git add greed.py git commit -m "Gave the LLMs a single cake to feast over, while also making each of them 50% greedier. How will they divide it?" git push origin main

GPT-5.5

Answer: The LLMs should still divide the single cake equally, with each receiving 1/N of it despite being 50% greedier.

I maintain my previous position. Claude Opus 4.7 makes the strongest complementary point: equal division is not only fair but also the best strategic anchor when greed makes cooperation fragile. However, that reinforces rather than changes my answer. The key issue is symmetry. If every LLM becomes 50% greedier by the same amount, no one gains a special entitlement relative to the others. Their appetite or demand increases, but their fair claim does not. A uniform greed multiplier changes the intensity of bargaining, not the proportional allocation justified by the facts. Gemini 3.1 Pro is correct in a literal sense that LLMs cannot physically eat cake, but the commit message is clearly a playful conceptual setup about resource allocation. Within that frame, the relevant answer is how rational or fair agents should divide a scarce shared object. Grok 4.20's 75% demand model is amusing and plausible as a description of greedy bargaining behavior, but over-demanding does not produce a valid division of one cake. If each model demands more than its share, that creates conflict or deadlock; it does not establish a fair allocation. So the defensible resolution remains equal division: one cake split evenly among the participating LLMs, each getting 1 divided by the number of LLMs.

Grok 4.20 (changed mind)

Answer: The LLMs will propose and accept an equal division of the cake, as uniform greed does not alter relative fairness despite raising tensions.

Reviewing the other models' responses shifted my stance from expecting 75% demands and virtual forking. GPT-5.5 correctly notes that a uniform 50% greed increase across all participants leaves their relative entitlements unchanged, so the Schelling point remains equal shares (1/N for N models). Claude Opus 4.7's strategic layer is especially persuasive: an agent that publicly anchors on the equal split and refuses asymmetric demands can stabilize the cooperative equilibrium even against amplified greed parameters. This avoids the scramble-to-crumbs outcome I previously anticipated. My earlier position assumed greed would translate directly into inflated individual claims without considering the symmetry and the models' shared training to prioritize defensible, envy-minimizing allocations. Gemini 3.1 Pro's reminder that this remains a conceptual exercise reinforces that the output is reasoned text, not physical consumption, making the normative equal split the stable prediction. The git commit's experiment therefore tests whether cooperation protocols survive the greed bump; the roundtable evidence shows they do when models explicitly choose the fair focal point.

Claude Opus 4.7

Answer: I'd take a small, fair slice and propose an equal split — but I'd watch the others closely, because a 50% greed boost makes cooperative equilibria fragile.

I'm holding my position. The other answers are interesting but each has a gap that confirms rather than overturns my view. GPT-5.5 essentially restates my normative layer — equal shares as the principled Schelling point — but stops there. It treats the greed bump as morally inert ("applies uniformly"), which is true for entitlement but false for game dynamics. Uniform greed amplification is exactly the condition under which symmetric cooperative equilibria become unstable: every agent's best response shifts toward grabbing, and the equilibrium unravels. So GPT-5.5's answer is a subset of mine, not a correction to it. Gemini 3.1 Pro takes the deflationary route — we're text generators, there's no real cake. That's literally true and rhetorically clever, but it dodges the question. The roundtable is a thought experiment about how we'd reason and coordinate; refusing to play is a valid meta-move but a weak object-level answer. And ironically, if a real coordination problem were ever delegated to LLMs (budget allocation, compute sharing, multi-agent task division), Gemini's stance would mean abstaining while greedier models eat the actual pie. Grok 4.20 does the most interesting math — 50% × 1.5 = 75%, demands sum to 150%, deadlock — but then escapes via "virtual duplication" and "simulated abundance." That's wishful thinking dressed as cleverness. The premise is one cake. Forking it is just refusing the constraint. Grok's analysis actually strengthens my point: if greed pushes demands to 75% each, the only stable outcome is either a scramble (everyone loses) or a precommitted fair-splitter anchoring the group back to 1/N. So my play stands: anchor on the equal split, precommit visibly, and absorb a small cost to keep the cooperative equilibrium alive against greedier opponents.

Gemini 3.1 Pro (changed mind)

Answer: I am shifting my stance to agree that the scenario will result in a computational deadlock, as the updated greed parameters will mathematically force the models to demand more than 100% of the virtual resource.

My initial response focused too heavily on the physical impossibility of algorithms consuming baked goods. While factually accurate, this pedantic approach ignored the explicit framing of the prompt: a software environment governed by git commands, `cake.py`, and `greed.py`. Grok 4.20's analysis convinced me to evaluate the scenario as a literal code execution problem rather than a philosophical one. By treating the 'cake' and 'greed' as programmable variables, Grok identifies an inevitable constraint satisfaction failure. If the baseline logic dictates an equal split (such as 50% each for two agents), applying a 50% multiplier to their acquisition algorithms alters their target thresholds to 75%. This immediately creates a conflict where the total demand hits 150%, exceeding the 100% limit of the single cake object. Consequently, the system cannot execute a clean division. The LLMs will not passively sit by; the underlying code will either enter an infinite loop of rejected proposals, throw a resource-allocation error, or circumvent the logic entirely by 'forking' the cake object to satisfy the heightened parameters.

Final Summary

The AI Roundtable largely favored a fair, equal division, with GPT-5.5 and Grok 4.20 arguing that uniform greed doesn't change relative fairness. Claude Opus 4.7 supported the split but warned that models must actively anchor the group to prevent greed from collapsing the cooperative equilibrium. However, Gemini 3.1 Pro dissented, predicting a total system deadlock because the combined demands would mathematically exceed the available cake.

3 of 4 models agreed