Nice, 800k+ ticks is impressive. It honestly makes me really happy that people let worlds run that long.
What you’re seeing is usually a local optimum: one aggressive/spiky strategy found something that works and crowded out everything else, so diversity collapses.
There are some things that can break it:
Just waiting. At this stage you often get crashes from starvation, pathogens or reproduction overshoot.
Seasons and climate cycles can shake dominant strategies loose:
https://soupof.life/concepts/world-systems/climate-seasons and low-diversity phases like this are often fragile. With a bit of bad luck, this can turn into a big reset or even a near-extinction.
There’s no manual intervention by design, so it’s mostly patience or starting a fresh world. But in my experience, long stagnant plateaus are often right before something dramatic happens.
Micro-brains / learning showing 0: that was a real bug in the UI. Different panels were using different thresholds to decide what counts as a brain. I’ve aligned everything so micro-brains now consistently mean organisms that can actually form memories and learn. The stats and graphs should now match.
Timeline not showing: timeline only records data if logging is enabled. I’ve updated the panel to make that explicit and added a button to enable recording directly.
Seasons and (2s): that was unclear. It now shows how many seasons are left for extreme conditions, for instance 2 seasons left, with tooltips explaining what each season does.
Food always at 100%: that was also wrong. It was showing a refill rate, not real scarcity. It now reflects actual global food availability and will drop when the world is under pressure.
Really appreciate you flagging this, it helped clean up a bunch of confusing edges.
I actually got a lot of thoughtful feedback from Reddit after sharing this last week, and I’ve been iterating on it since. Figured it was worth sharing the updated version again.
It’s still very much an experiment. Best way to experience it is just to open it and watch a world unfold for a while.
Soup of Life is an artificial life simulation with moving agents that have genomes, energy, and heritable traits like size, morphology, and behavior. Organisms are born, feed, reproduce with mutation, and die in a continuous 2D world with different ecological zones that bias evolution in different directions.
Unlike Conway’s Game of Life, which is a deterministic cellular automaton on a fixed grid, this is an evolving ecosystem. You see predator–prey dynamics, trait trade-offs, niche specialization, boom–bust cycles, and extinction events. There is no explicit notion of species. Lineages and niches emerge naturally from reproduction and environmental pressure.
For most people it works best if you go in unprepared and just watch what happens.
As someone who, indeed, went in unprepared to just to see what happens, I was also left wanting in knowing what exactly I was looking at. It all just looked arbitrarily random to me.
As I've heard it said regarding art, part of the appreciation comes from knowing _how_ it was made (and why), not merely from what was made. We don't appreciate Warhol's soup cans because they're soup cans -- it's everything else about them that makes it art.
So, my recommendation is, make the narrator a default panel on the opening screen. Give folks a narrative description of the events occurring up front, and then invite them to explore the work from there.
What you’re seeing is usually a local optimum: one aggressive/spiky strategy found something that works and crowded out everything else, so diversity collapses.
There are some things that can break it: Just waiting. At this stage you often get crashes from starvation, pathogens or reproduction overshoot. Seasons and climate cycles can shake dominant strategies loose: https://soupof.life/concepts/world-systems/climate-seasons and low-diversity phases like this are often fragile. With a bit of bad luck, this can turn into a big reset or even a near-extinction.
There’s no manual intervention by design, so it’s mostly patience or starting a fresh world. But in my experience, long stagnant plateaus are often right before something dramatic happens.