Practical use of Metamorfon: architectures and debate modes, model behavior, analysis generation and interpretation, session management and use.
How to Make Two AIs Debate: Orchestrating and Analyzing a Dialogue Between LLMs You've probably seen the scene: two AIs wired to each other, left running, ending up either inventing an incomprehensible jargon or drifting into an endless conversation people watch the way they'd watch a campfire. It's fascinating, and it travels well online. But these demos prove one thing — that two AIs can exchange — without ever...
When a Debate's Richness Becomes a Point of Vigilance Metamorfon's purpose — setting several models against each other dialectically on demanding questions — produces exchanges of unusual conceptual density: in just a few turns, models invoke dozens of attributions, statistics, and historical milestones. That richness is the very point of the exercise; it is also its point of vigilance. The more precise references...
Temperature, in a Nutshell When a language model generates text, it doesn't pick the next word deterministically. At each step, it evaluates a probability distribution over the possible next tokens and samples from it. Temperature is the parameter that flattens or sharpens that distribution. At a low temperature (close to 0), the model systematically favors the most likely tokens. It becomes predictable, rigorous,...
In a prolonged conversation between multiple AI models, two characteristic drifts set in. The first is dialogical: each model, prompted to respond to the others, ends up constructing its answer around its interlocutors' arguments rather than around the question initially posed. This inertia can eclipse a priority user intervention, to the point that the debate continues its trajectory without genuinely integrating...
Does Metamorfon verify the factual accuracy of the information generated by the models? Not in the sense of general-purpose fact-checking — but Metamorfon no longer stops at confronting models. Its primary function remains the orchestration of argumentative confrontation between models: revealing their assumptions, their epistemic styles, and their blind spots. To this is now added a Source Verification mode, which...
Metamorfon's dialogue architectures are described as adaptive, and the application presents them under the name adaptive strategies. The word might suggest the automatic adjustment of a parameter — a system that would detect, for example, that a debate is running in circles and switch on its own to a sharper mode. This is not what the adjective designates. The adaptation in question here is not an algorithmic...
What Your Debate Could Not Say In any serious discussion, there is what the participants say, what they do not say, and a third, less visible layer: what they could not have said even if they had wanted to. What the very formulation of the question, the vocabulary employed, and the shared self-evident assumptions excluded before anyone took the floor. Take a concrete example. Suppose three AI models are asked:...
The Difference Between What Is Said and What Has Become Thinkable It happens, at the end of an intense conversation, that one says: "we touched on something important without formulating it." The idea was there, carried by the exchanges, prepared by the successive contradictions, but no one said it. It remained on the horizon — visible, untraversed. This experience is not anecdotal. It points to a precise...
Recounting What Was Said Among Metamorfon's eight analysis modes, Integrative Synthesis is at once the most immediately useful and the least spectacular. The most immediately useful, because anyone who has just launched a nine-turn debate between two or three models has, first of all, a simple need: knowing what was said in it. The least spectacular, because synthesizing content does not appear to constitute a...
What Resists After Everything Has Been Said In every debate, certain disagreements dissolve as the conversation progresses — a misunderstanding clears up, a definition is sharpened, a concession is negotiated. Others, by contrast, survive every reformulation and every clarification. They hold. They form what might be called the skeleton of the debate: what would remain if everything that could be agreed upon had...
What the Dialogue Produces and Belongs to No One It happens that a session of debate between models produces a concept no one was bringing into the conversation. It was not in the initial question, nor in the opening position of any of the interlocutors, nor in the user interventions — and yet, in the end, it is there, stabilized, used as an established premise by all participants. It was formulated, reformulated,...
Judging the Quality of a Debate Without Settling Its Conclusions Reading a debate makes it possible to evaluate what was said in it. But another reading is possible, one that does not bear on what was defended but on the manner of defending it. Which arguments were soundly constructed, which were circular or immunized against critique, which rested on reconstituted sources, which dealt with objections substantively...
Seeing What Structures a Debate Beneath the Surface of Arguments When one reads a debate — whether an academic discussion, a parliamentary exchange, or a dialogue between AIs — one first retains the arguments exchanged, the positions defended, the concessions and the breaks. This is the manifest content, and it occupies most of the attention. But beneath this visible content, another level operates silently: the...