DreamCraft Legacies: Building a Persistent World With AI
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What Happens When You Let an AI Simulation Run for a Year Without Intervention?
I asked myself a question: What if I built a fantasy world that didn't pause when no one was watching?
Most games reset. Dungeons refill. NPCs respawn. You can design one playthrough and it feels consistent because the system resets between sessions.
But what if the world kept going? What if 20 characters made decisions every single day for 365 days, and every consequence stuck?
That's DreamCraft Legacies — an AI-driven simulation of a persistent fantasy settlement where characters eat, work, die, and build a civilization without any human intervention between runs.
The Core Concept
Every night at 3 AM EST, 365 simulated days complete. Characters wake up with real hunger, real exhaustion, real resources. They choose actions based on their needs and the world's state. They consume food. They improve skills through repetition. They accumulate injuries. They die.
And it all persists.
The settlement they build stays built. The food they produce stays in storage. The characters they lose stay dead. Over 7 nights, I'll watch 7 simulated years unfold in real-time.
Why does this matter?
Because it tests something nobody really knows how to do yet: Can you create a world that feels alive without scripting the life into it?
How It Works
The Setup:
- 20 characters with different races and classes
- 9 types of actions they can choose (hunt, build, rest, help, practice skills, etc.)
- A persistent database tracking every decision and consequence
- An AI system that makes daily decisions based on character needs and world state
The Mechanics:
- Characters consume 1 food per day (realistic depletion)
- Actions cost resources but generate skills and experience
- Starvation causes gradual injury (not instant death, but real consequence)
- Skills improve through use, creating natural specialization
- Resources accumulate or run out based on actual production and consumption
The Persistence: Everything compounds. A character who hunts every day becomes a better hunter. A settlement that focuses on shelter-building develops stronger structures. A group that hoards resources might create inequality. None of this is scripted. It emerges from the rules and the choices.
What Worked
The core simulation is solid. Characters eat daily, take actions based on needs, improve skills, and accumulate resources. The database persists everything. A full 365-day year runs in under 3 minutes with zero crashes.
Emergence actually happened. Without any hardcoded leadership mechanics, certain characters naturally accumulated more experience by making consistent choices. The strongest characters weren't the ones with the "best" class — they were the ones who showed up every day and made good decisions.
The AI decisions feel organic. Hungry? Hunt more. Exhausted? Rest. Need shelter? Build. The system responds to state, creating patterns that feel like personality without any personality programming.
Resource management works. Food depletes at a rate that creates real pressure (20 characters × 1 food/day). Wood and stone accumulate from labor. The economy is functional, though still being balanced.
What Broke (And Why It Matters)
The first critical bug was in the hunger mechanic. Food consumption depleted world resources but never actually reduced character hunger. Characters ate (food disappeared) but stayed hungry. This cascaded into starvation damage, injury accumulation, and by Day 2, everyone was at hunger level 500+.
The lesson: You can't see emergent problems in code. Only in data.
I reviewed the code a dozen times. The logic looked correct. The bug was a single missing database UPDATE statement that only revealed itself after watching hunger values compound across 365 days.
This is why persistence matters: fake systems get exposed by time.
In a traditional game, you can tune one playthrough and it feels consistent because you reset between plays. In a persistent world, any imbalance compounds. Any bug multiplies. The system forces you to build things that actually work.
The Real Challenge: Creating Natural AI Without Scripting Outcomes
Here's the fundamental tension: How do you make AI decisions feel natural without either scripting them or making them random?
When a character's hunger exceeds 15, they hunt. That's deterministic programming, not emergence.
But when multiple characters hit that threshold on the same day, they compete for food. When food becomes scarce, hunting becomes less efficient. When some characters are better hunters, inequality emerges naturally.
The trick: Set the rules tight. Don't script the outcomes.
The characters that rise to prominence aren't random. They're the ones whose decision patterns compound positively over time. Whether that's "real" emergence or "sophisticated automation that looks emergent" is philosophical. The data will tell us.
The Meta Challenge: Building Living Worlds With AI
Most "AI games" are AI on rails — decisions made within carefully controlled spaces. It feels free because the illusion is good.
A truly persistent world is different. You can't script it. You have to:
- Let characters make real decisions with real consequences
- Accept that sometimes those decisions lead to collapse
- Watch the system find equilibrium without intervention
That requires letting go of control. And it requires brutal honesty about what's actually emerging versus what you're narrativizing.
When AI generates blog posts about simulations, it makes assumptions. It adds emotional weight to mechanics. It creates causal relationships that sound true but aren't proven. The fix is simple: trace every claim back to the data.
If you can't prove it in the numbers, it doesn't belong in the narrative.
The 7-Year Plan
Starting December 28, the simulation runs every night for 7 consecutive nights. Each night represents one complete year (365 simulated days).
Timeline:
- Night 1 (Dec 28): Year 1 simulates with bug fixes in place
- Afternoon Dec 29: Year 1 results published
- Nights 2-7 (Dec 29 - Jan 3): Years 2-7 simulate
- Daily updates: Blog posts analyzing what happened
By January 4, I'll have 2,555 simulated days of data showing how a civilization develops, survives, fails, or thrives.
Why This Matters
Building a living world with AI isn't about having better algorithms. It's about building constraints that allow real behavior to emerge, then being ruthlessly honest about what actually emerged versus what you're narrativizing.
Randomness isn't emergence. Constraints create complexity. "Natural" is harder than "correct." Persistence changes everything.
In a one-shot game, you can fake depth. In a persistent world, fake depth gets exposed after 100 days. That forces you to build real systems.
What Comes Next
Tomorrow, Year 2 runs, and the data will be analyzed, the story will come to life.
I'm learning in public. Every result, every failure, every surprise will be documented.
The question isn't whether this will work perfectly. It won't. The question is: What does a genuinely living world actually look like when you stop controlling it?
Only time will tell.
Follow Along
- Website Blog updates: Periodic posts about progress.
- Reddit discussion: Technical deep-dives and community engagement= https://www.reddit.com/r/AICreatorsUnite/
- Medium Blog: Narrative driven update- https://medium.com/@everydaygamer
Year 2 begins tomorrow at 3 AM EST.
DreamCraft Legacies: An experiment in persistent worlds, emergence, and consequence.