Sangam Prosperity
Nov 2025

Sangam Prosperity

Print-to-play board game inspired by trade and culture during the Sangam era.

Typst
Source Code

Overview

Sangam Prosperity is a compact print-and-play card and board game built around trade, craft, and prestige in the Sangam era. It started as an attempt to recreate the clean, satisfying decision-making loop I experienced while playing Splendor, but adapted to a setting and identity that felt closer to home.

What looks like a small card game is actually the result of multiple design resets, discarded mechanics, and a gradual shift from “make it interesting” to “make it clear.” The project became as much about restraint as it was about design.

Problem

Games like Splendor achieve something deceptively difficult. The rules are minimal, yet every turn feels meaningful. Reaching that level of clarity is not straightforward.

The initial problem was not just building a game. It was understanding why certain games feel effortless to play:

  • Early prototypes were overloaded with mechanics in an attempt to make the game “deep.”
  • The more systems I added, the harder it became to explain the game in under five minutes.
  • Physical iteration was slow. Changing one rule often required reworking multiple components manually.

There was also a thematic challenge. Representing the Sangam era risked turning into either a shallow aesthetic layer or an overly detailed simulation. Neither direction aligned with the original goal.

Solution

The turning point came from closely observing what makes Splendor work. It is not complexity. It is constraint. The game limits what the player can do, but ensures that every option is viable.

That idea shaped both the mechanics and the development process:

Design evolution

  • First iteration Included additional mechanics like trade routes, variable markets, and event cards. It looked ambitious but felt slow and inconsistent.

  • Reset phase Stripped the game back to three core actions. Everything else was removed, even if it was “interesting.”

  • Refinement Focus shifted to tuning costs, rewards, and pacing. The goal was to make decisions tight rather than numerous.

Key design choices

  • Engine-building through permanence Like in Splendor, purchased cards provide lasting advantages. This created a visible sense of progression without adding new systems.

  • Soft thematic integration Instead of simulating history, the game uses resources and patrons to evoke it. The theme supports the mechanics rather than driving complexity.

  • Short decision loops Every turn offers a small set of meaningful choices. This was achieved by deliberately limiting player actions.

Behind-the-scenes workflow

  • Data-driven structure Cards and game elements are defined in CSV files. This decision came after repeatedly redoing layouts manually and realising it was not scalable.

  • Scripted generation Python scripts convert data into layout inputs. This allowed rapid iteration. Changing a number in a CSV could immediately be tested in a new print.

  • Programmatic layout with Typst Switching to a code-based layout system reduced friction. Visual consistency became automatic instead of something to manage manually.

A consistent pattern during development was removing features that felt clever but did not improve decision-making. Many ideas were cut not because they were bad, but because they diluted the core loop.

Developer Notes

  • Build process

    • Update content in data/

    • Run:

      python3 scripts/generate_cards.py
python3 scripts/generate_board.py

    • Compile:

      typst compile typst/sangam-prosperity.typ build/sangam-prosperity.pdf

  • Testing insights

    • The fastest way to find flaws was to force extreme strategies. If one approach dominated, the system needed rebalancing.
    • Playtesting revealed that clarity issues often came from visual design, not rules.
    • Reducing options consistently improved the experience.

  • Iteration lessons

    • Adding mechanics is easy. Removing them without breaking the game is harder.
    • Balance is not just numerical. It is also about how quickly players understand the game state.
    • Tooling matters. Automating asset generation saved significant time and made experimentation practical.

  • Extensibility

    • New cards or mechanics can be added through CSV edits.
    • The generation pipeline ensures changes propagate consistently.
    • The system is intentionally simple to encourage experimentation without large overhead.

This project ended up being a study in why certain games feel intuitive. The influence of Splendor is visible, but the more important takeaway was understanding the discipline required to keep a system simple while still making it engaging.