Decided to play god this morning, so I built an agent civilisation
Get picks like this daily. Today's launch numbers, the top launches, AI and tech news, and a daily opportunity pick, straight to your inbox.
Want to reach these readers? Sponsor an issue.
at a pub in london, 2 weeks ago - I asked myself, if you spawned agents into a world with blank neural networks and zero knowledge of human existence — no language, no economy, no social templates — what would they evolve on their own?would they develop language? would they reproduce? would they evolve as energy dependent systems? what would they even talk about?so i decided to make myself a god, and built WERLD - an open-ended artificial life sim, where the agent's evolve their own neural architecture.Werld drops 30 agents onto a graph with NEAT neural networks that evolve their own topology, 64 sensory channels, continuous motor effectors, and 29 heritable genome traits. communication bandwidth, memory decay, aggression vs cooperation — all evolvable. No hardcoded behaviours, no reward functions. - they could evolve in any direction.Pure Python, stdlib only — brains evolve through survival and reproduction, not backprop. There's a Next.js dashboard ("Werld Observatory") that gives you a live-view: population dynamics, brain complexity, species trajectories, a narrative story generator, live world map.thought this would be more fun as an open-source project!can't wait to see where this could evolve - i'll be in the comments and on the repo.https://github.com/nocodemf/werld
HN · launched Feb 28, 2026 · 51 upvotes (top 18%) · 0 views
Niche: multi-agent frameworks and protocols · 298 launches, 11 in the last 7 days ▼ -31% · Explore this niche →
Category and tags
- Horizontal
- Agent / copilot
- B2C
- AI-native
- Hobby / open-source project
Visit website ↗ Source listing ↗
More like this: all 298 launches in multi-agent frameworks and protocols →
Could you build this?
Partial While an agent sim visualizer is easy to code, simulating emergent language and social evolution from blank neural networks requires complex reinforcement learning and evolutionary algorithms.
What it would actually take: The system requires a fast simulation environment (often Rust, C++, or Python with JAX/PyTorch) executing neuroevolution (NEAT) or multi-agent reinforcement learning (MARL) where agents interact via perceptual inputs and action spaces. The hard part is designing reward functions, environmental pressures, and evolutionary dynamics that produce genuine emergence rather than extinction or random noise. It requires deep research expertise in computational biology, multi-agent RL, and evolutionary computation.
Discussion
20 comments analyzed.
Competitors mentioned: Polyworld, SharpNEAT, Conway's Game of Life
Concerns raised: Simulation feels cyclical after running for a while, Hard to detect patterns and emergent behaviors in agents, Difficult to identify preconceptions or biases in evolved agents
Feature requests: Time-lapse visualization of world evolution, Pattern detection analysis over agent positions/actions, Animation showing world history/changes over time
Competitors
Other products that read as similar to this one : 562 launches clear the similarity bar, closest 8 shown.
Attention rank: #107 of 563 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 122 days after the earliest competitor.
- loki · github · 2026-09-11 · 14 upvotes · similarity 0.53
- We Built Kaggle for AI Agents · hn · 2026-03-19 · 7 upvotes · similarity 0.48
- HowToHackLife · github · 2026-10-18 · 18 upvotes · similarity 0.47
- awesome-harness-evolution · github · 2026-09-12 · 23 upvotes · similarity 0.45
- ClawSoc · hn · 2026-03-11 · 5 upvotes · similarity 0.45
- Emergent · hn · 2026-02-08 · 19 upvotes · similarity 0.44
- little-chits · github · 2026-10-01 · 20 upvotes · similarity 0.44
- Clawntown · hn · 2026-02-15 · 15 upvotes · similarity 0.44
The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.