How to Implement a Seeded Random Number Generator

A seeded random number generator—producing the same sequence from the same seed—is essential for reproducible randomness, enabling consistent procedural generation, replays, and deterministic behavior. Understanding seeded RNGs is key to making randomness reproducible when you need it.

A seed makes randomness reproducible

A seeded RNG is initialized with a seed value, and from the same seed it produces the same sequence of random numbers every time. This reproducibility is the key property: with a seed, the 'random' sequence is deterministic and repeatable, so the same seed always yields the same sequence. This is essential for several things: reproducible procedural generation (the same seed generates the same world/level, so a seed can recreate a specific generation, which is why games share 'world seeds'), replays and determinism (a seeded RNG advanced identically produces the same randomness, which determinism requires, as discussed in determinism), and any case where you need the randomness to be reproducible. A seed making randomness reproducible—the same seed yielding the same sequence—is the core of a seeded RNG, providing the reproducible randomness that consistent generation and deterministic behavior require.

Managing the seed and the RNG state enables reproducibility where you need it. Using a seeded RNG effectively means managing the seed and the RNG's state. Managing the seed means controlling the seed value—using a specific seed to reproduce a specific sequence (a shared world seed, a saved seed for a generation), or a random seed for variety—so you can choose reproducible or varied randomness as needed. For reproducible generation, you save and use specific seeds; for variety, you use random seeds. Managing the RNG state means controlling the RNG's progression—for determinism, the RNG must be advanced identically (the same calls in the same order) to produce the same sequence, so managing how and when the RNG is used matters for reproducibility, especially for determinism. For determinism (replays, lockstep), the seeded RNG must be the sole source of randomness, advanced identically, so its state stays synchronized. Managing the seed (choosing reproducible or varied) and the RNG state (advancing it consistently for determinism) is what enables the reproducibility a seeded RNG provides where you need it. Combining a seed making randomness reproducible (the core reproducibility) with managing the seed and the RNG state (enabling reproducibility where needed) is what makes a seeded RNG provide the reproducible randomness that consistent procedural generation, replays, and determinism require. Using a seeded RNG this way—reproducible from the seed, with managed seed and state—gives you reproducible randomness when you need it (consistent generation from seeds, deterministic behavior for replays), while still allowing varied randomness (random seeds) when you don't, which is essential for procedural generation, replays, and determinism.

Default to the boring, robust choice

It's tempting to reach for the clever, novel, or technically impressive solution, but in production the boring choice — the well-understood approach, the proven pattern, the simple implementation — is usually the one that ships and keeps working. Cleverness has a way of becoming the bug you're debugging at 2am six months later.

Save your novelty budget for the things that actually make your game distinctive, and be conservative everywhere else. A game built on robust, unremarkable foundations is one you can keep building on, while one built on clever fragility is one that fights you the whole way.

Make the common case effortless

Most of what a player does, they do over and over, and most of what you build will be exercised in a handful of common situations far more than in the edge cases. Optimising the rare and neglecting the frequent is a reliable way to make a game that's technically complete and practically annoying.

So spend your polish where the volume is: the action repeated a thousand times, the menu opened constantly, the path every player walks. Making the common case smooth and satisfying does more for how the game feels than perfecting the corners almost nobody reaches.

Protect the thing that makes it special

Every game that connects has some core spark — a feeling, a mechanic, a tone — that's the real reason people love it, and that spark is fragile. In the rush to add content, fix problems, and respond to feedback, it's easy to sand away exactly the quality that made the game worth making in the first place.

Know what your spark is, and guard it. When a change threatens the thing that makes your game distinctive, that's the change to question hardest, because a game can survive plenty of rough edges but rarely survives losing its soul.

Why finishing beats perfecting

The hardest skill in indie development isn't any particular technique — it's finishing. Most games that never ship didn't fail on talent; they failed on scope, polished forever, or chased one more feature. The developers who build a real body of work are almost always the ones who got good at choosing something small enough to complete and then completing it.

That's worth keeping in mind here, because it's easy to let any one part of development expand to fill all your time. Decide what 'good enough to ship' looks like, protect that line, and treat the endless list of possible improvements as a backlog rather than a set of obligations.

Plan for the parts you can't see

Once a game leaves your machine, a lot of what happens to it becomes invisible by default. Players run it on hardware you don't own, hit problems you never reproduced, and most of them never tell you — they simply move on. The gap between 'it works for me' and 'it works for everyone' is where a surprising amount of churn quietly lives.

So plan to see what you otherwise couldn't. Watching real players, capturing the bugs and crashes they hit with the context to fix them, and paying attention to where they drop off all turn invisible problems into ones you can actually act on — which protects the reviews and retention everything else depends on.

A seeded RNG produces the same sequence from the same seed, making randomness reproducible—essential for consistent procedural generation, replays, and determinism. Use a seeded RNG and manage the seed and its state, so randomness is reproducible from the seed where you need it.