Why Build a MUD in 2025?

Posted on Development, Game Development, Networking, AI, Go
Why Build a MUD in 2025?

Multi-User Dungeons (MUDs) are text-first, real-time multiplayer worlds that predate modern MMOs. In 2025, building a MUD might seem contrarian, but it’s exactly the kind of project that rewards strong engineering, clean contracts, and a relentless focus on player experience. I’m building one as both a learning lab and a playable product.

Multi-User Dungeons (MUDs) are text-first, real-time multiplayer worlds that predate modern MMOs. In 2025, building a MUD might seem contrarian, but it’s exactly the kind of project that rewards strong engineering, clean contracts, and a relentless focus on player experience. I’m building one as both a learning lab and a playable product.

This post lays out the “why”: the technical leverage, the design space, and the practical upside of shipping a modern MUD today.

TL;DR

  • Low cost to build, host, and scale—perfect for iterative development.
  • Forces great systems design: protocols, state, persistence, and concurrency.
  • Ideal sandbox for applied AI: agents, content tooling, and testing.
  • Accessible UX: works everywhere, inclusive for screen readers, low bandwidth.
  • Recaptures the fun of tight feedback loops that many modern games have lost.

What I’m Building

I’m working on a networked MUD in Go with a modular architecture: dedicated services for auth, world simulation, NPCs/agents, economy, and observability. It’s engineered for clarity and testability, not just nostalgia.

  • Repo (private for now): ~/Repositories/mud
  • Language: Go
  • Shape: service-oriented core with focused modules (auth, energy, NPCs, network, advertising)
  • Tests: high coverage with per-module coverage reports and profiling artifacts
  • Deployment: Kubernetes; local dev + CI; S3 + CloudFront for web docs

This series will cover the design and evolution of the system—starting with the “why,” then the network and world simulation, then tools and content.

Why a MUD Still Makes Sense

1) Systems Thinking with Instant Feedback

MUDs require you to design clear interfaces between networking, world state, persistence, and AI. There’s nowhere to hide: strong contracts and repeatable tests win. Small mistakes are visible instantly—and fixable just as fast.

What you learn transfers cleanly to backend engineering, multiplayer infrastructure, and agent systems.

2) Agentic AI Is Better in Text-First Worlds

Text-first worlds are a natural habitat for AI agents:

  • Observations are structured text; actions are tokens; no rendering pipeline required.
  • You can mix GOAP/BT planners with LLM tooling for dynamic behaviors.
  • Content generation is safer and cheaper: descriptions, quests, items, chatter.
  • Simulation speed is limited by CPU and your update loop, not frame rate.

The result: richer NPCs, faster iteration, and better telemetry for evaluation.

3) Accessibility and Reach

MUDs run anywhere—terminal, web, mobile SSH client (I’m not enabling telnet for security)—and are friendly to screen readers. Latency tolerance is high, bandwidth use is tiny, and players can drop in for 5 minutes without a 10 GB patch. That’s a superpower.

4) Operates Well on a Small Budget

The stack is lean and predictable. A single modest server can host thousands of concurrent connections when the code is efficient. It’s the right canvas for one person (or a small team) to ship something real.
I’m known for overengineering things, so this is running on a Kubernetes cluster with network policies, lots of observability, and workflows—but it could easily be pared down to a single VM or even a serverless function.

5) Teaches the Hard Parts—Safely

You’ll touch concurrency, protocols, persistence, migrations, observability, and liveops. You’ll also build tooling: map editors, item pipelines, NPC behavior fixtures. All of this pays dividends on any backend system.

Architecture Notes

I’m leveraging agents and LLMs for development, but I believe the future is in learning to build with these systems using a systematic methodology. This allows for stretch goals and learning that would have been otherwise unachievable. This project is also about what makes architecture and design so important, interesting, reliable, and predictable.

Key principles I’m following:

Planned posts will include:

  1. Network protocol and session lifecycle
  2. World tick, ECS-like entities, and state persistence
  3. NPCs and agent behaviors (rule-based + LLM-assisted)
  4. Economy design and anti-exploit checks
  5. Tooling, profiling, and deploys

What “Success” Looks Like

  • A stable, well-documented server with clean contracts.
  • A small, active player base enjoying tight loop gameplay.
  • A flexible AI layer that’s fun to extend and evaluate.
  • Reusable components applicable to other multiplayer/back-end work.
  • A series of posts sharing what I learned along the way.
  • API access for bots and extensions. (ReadOnly)

Call for collaborators - Maybe?!?

Interested in systems, networking, or AI behaviors? I’m sure I would love discussing ideas and approaches. I don’t plan on opening the repo as it is a personal project, but if you want to help, look around or kick the tires when it’s ready, ping me or just stay tuned!

– Cheers