The gambit that decayed: when the wood learned to remember

Lester Leong

AdmiralTaco

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build-small-hackathon

The last installment ended on a note I was a little too pleased with. I had spent three losing runs trying to make a panic crash a price, given up on steering the agents, and authored the crash at the settlement seam instead. After the market cleared, the run landed as a fact, the price halved, and the short that front-ran it booked a clean profit. The same gambit paid the same amount every time. I called that control, and I meant it as praise.

A clean strategy that pays the same amount every time should have made me nervous, and eventually it did. In a real market, a repeatable edge that everyone can watch you run is not an edge for long. The people on the other side learn your face. They price you in. The honest name for the thing that erodes a visible edge is adverse selection, and my wood did not have any. The creatures I lied to forgot the lie by the next turn and lined up to be fooled again. So I asked the obvious question. What happens if the wood remembers?

The memory was already there

Here is the part that taught me the most, and it is a lesson about reading your own system before you extend it. I went in expecting to build a suspicion engine. I did not need to. The creatures already carried a persistent feeling toward the financier, and a tip that turned out to be a lie already soured it. I had simply never given that feeling anything to do. It sat in state, updated every time I burned someone, and changed nothing.

So v4 is not a new system. It is teeth on a signal that was already in the world. A creature whose feeling toward the financier drops past a threshold becomes wary, and a wary creature does two things it never used to do.

First, it stands on the other side of my crash. When the run lands and I overwrite the price at the settlement seam, I now count the wary creatures who hold or produce the good I am crashing, and I let them push back. Each one blunts the crash, softening the price drop toward no move at all. The mechanic lives at the exact same seam as the authored crash from last time, which is the point. I did not move the lever. I let the agents lean on it.

Second, it talks. A wary creature feeds the magistrate who investigates suspicious wins, raising the heat on me every turn it stays soured. My manipulation history, which used to be free, now has a standing cost. The more creatures I have burned, the faster the inquiry comes for me, whether or not I do anything new.

Neither effect required a new field, a new prompt, or a new model call. Both read a number the engine had been keeping all along.

The same gambit, decaying

Then I ran the same short into the same legend, and watched the payoff come apart. Holding the short fixed and letting the wood wise up one creature at a time, the gambit decays on a schedule:

Table 1. The identical short into the identical legend, as more burned creatures stand against it. The payoff is the engine's deterministic settlement on a fixed four-unit short, not a single lucky run. The floor at three is a deliberate cap: a soured wood blunts the gambit but never fully erases it, so manipulation degrades toward marginal rather than impossible.

The shape is the whole story. The first lie costs me nothing I can see. By the third, the crash I authored is a shadow of itself and the magistrate is at the door. The strategy that paid the same amount every time now pays less every time I use it, because using it is what teaches the wood to defend against it. That is adverse selection, built from a feeling the creatures already had and I had been ignoring.

Make the decay legible or it is not a lesson

A mechanic the player cannot feel is just a number moving in the dark. The thing that turns this into something you understand while you play is a small panel I added to the operator console, and it is the one piece of craft from this round I would defend hardest.

I borrowed the idea from another entry in the same hackathon, a single-character drama whose whole interface is one conversation and one panel of meters that twitch the instant your words land. The lesson there is not the layout. It is that state should visibly move on your action. So the new panel shows, for the gambit you have armed, the expected payoff if you spring the legend right now, and a gauge of how wary the wood has grown. The expected payoff is computed with the exact same formula the settlement seam uses, so the meter does not lie about the outcome. Sour a creature with a false tip, and you watch the projected profit drop before you have done anything else. The cost of lying stops being an abstraction and becomes a number falling in front of you.

That is the difference between a system that punishes you and a system that teaches you. The punishment was always in the engine. The teaching is in showing it to you in time to change your mind.

What I took away

Three things, and like last time all three outlive the game.

First, your edge is consumed by the people you trade against learning who you are. A manipulation you can run once is a tactic. A manipulation you run repeatedly against agents who remember is a countdown. The visible, repeatable, always-profitable strategy is the one most certain to decay, and the decay is caused by the using.

Second, read your own state before you build more of it. The adversarial behavior I set out to construct was already latent in a feeling the creatures carried and I had wired up but never used. Most of the work was deletion of my own assumption that I needed something new. The cheapest feature is the one already sitting in your world with nothing to do.

Third, a cost the user cannot see is not a deterrent, it is a trap. The same fact, the wood is souring on you, is either an unfair surprise or a fair warning depending entirely on whether you surfaced it in time. Building the meter that shows the decay was not polish. It was the part that made the mechanic honest.

I build agent-based market models for a living, and the most expensive lesson in that work is the one this little wood just charged me a pile of pebbles to relearn. The market you can fool forever is a market you built wrong. The one worth modeling is the one that learns your face and makes you pay for the last time you lied.

Small models, big adventures, and a wood that finally remembers.

Try it: the Space. Open agent traces: the dataset.