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Building a multiplayer Tic-Tac-Toe backend in Go without a coding agent made Satyam Shree focus on the work around the game: API design, ownership of responsibilities, shared state, and live updates. The rules fit on a small board; coordinating two players over a network is where the engineering gets interesting. This is one developer’s project retrospective, not evidence that manual coding is better than AI-assisted development.
What the project does
Shree describes a Go backend for creating and joining games, starting matches, accepting and validating moves, tracking turns and game state, detecting winners, and broadcasting updates to players. Its example API includes POST /games to create a game, GET /games/{gameId} to retrieve one, routes for joining and starting a game and making moves, and GET /games/{gameId}/ws for a WebSocket connection.
The board and win conditions are deliberately familiar. That leaves room to consider questions that apply to many networked applications: which part of the code owns a decision, how clients learn about state changes, and what happens when connections or requests overlap.
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Shree’s design assigns different jobs to the HTTP handler, game logic, and connection manager. The point is to keep transport details from taking over the rules of the game, and to keep socket delivery separate from the domain model.
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| Component | Responsibility described in the project | Why keep it separate? |
|---|---|---|
| HTTP handler | Receives requests, calls the relevant application or game operation, and returns HTTP responses. | It translates between HTTP and the rest of the application rather than deciding game rules. |
GameManager |
Handles operations on the collection of games, such as creating or finding a game. | Collection-level work does not need to live in request parsing or board-rule code. |
Game and board logic |
Represent game state and apply rules, including turns, move validity, and outcomes. | The rules can be reasoned about independently from HTTP and socket delivery. |
ConnectionManager |
Registers WebSocket connections and broadcasts game updates. | Connection delivery and lifecycle are different concerns from deciding whether a move is legal. |
Shree captures the handler’s intended boundary this way: “A handler shouldn’t know how your business works. It should know how to talk to your business logic.” These are the project’s reported design choices; the implementation was not independently reviewed.
How WebSockets update both players
A WebSocket starts with an HTTP request and, if upgraded, becomes a persistent connection. Instead of having each player repeatedly ask the server whether the board changed, the server can send an update when a move changes game state. The client can then render the new board and turn information.
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Polling or server-pushed updates?
With polling, clients send repeated requests to check for changes. That can be straightforward to understand, but the server may receive requests when nothing has changed, and updates arrive only when the next request is made. A WebSocket gives the server a channel for sending changes as they happen, but it brings connection management into the design: the application must track connected players and deal with connections that close or stop responding.
Generic payload or a message envelope?
Shree considers broadcasting a generic payload or using a common message envelope. A generic payload may be adequate for a small project, but a shared envelope can make message types and their data more explicit as the protocol grows. The article does not report a measured comparison or establish one format as universally preferable.
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What changes when there are many games?
“What happens when there are 100 games?” is a useful design question even when the game itself is simple. It asks where game records live, how a request locates the right one, and whether state changes are safe when more than one request acts on the same game. In Shree’s project, game state is held in memory, so a server restart loses it. Persistent storage such as PostgreSQL or Redis is identified as a possible next step, not as an implemented feature; which choice fits depends on the application’s requirements.
More games also make the boundary between shared game state and concurrent requests important. The author notes that simultaneous requests could race over shared state. A robust implementation would need to ensure that competing actions cannot both apply as though they were first—for example, two move requests arriving near the same time. The project’s account identifies the risk but does not describe a completed concurrency solution.
Rank #4
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What remains unfinished
Shree presents the backend as a learning project, with several production-relevant concerns still open:
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- Persistence: in-memory games disappear when the server restarts.
- Identity and authorization: player identity and permission checks are basic.
- Reconnection: a player who loses a connection cannot yet rely on a described reconnection flow.
- Concurrent actions: shared game state could be subject to races if requests overlap.
- Socket lifecycle: registering and removing connections, and handling dead connections, need more robust treatment.
These are not minor details added after the “real” game. They shape whether the server can preserve a match, identify its participants, and keep both clients’ view of the board consistent.
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How to test the game rules
The author proposes unit tests for the core outcomes and invalid actions. A useful test set would check:
- Horizontal, vertical, and diagonal wins.
- A draw when the board fills without a winner.
- An invalid move, such as using an occupied cell.
- A move made by the player whose turn it is not.
- A move submitted after the game has ended.
These tests would make the rules easier to change without accidentally accepting an illegal move or misreporting an outcome. They would not, by themselves, resolve the separate concerns of concurrent requests, persistence, or WebSocket cleanup.
What building it without an agent meant to the author
Shree says, “I didn’t use an AI coding agent to implement this project.” He describes personally making and revising decisions as a way to make API design, domain modeling, separation of concerns, state management, WebSockets, event broadcasting, error handling, concurrency, Go, and debugging more tangible. That is a personal account of learning through a project, not a controlled comparison of manual and agent-assisted development.
His concise assessment is: “The game is simple. The engineering isn’t.” Tic-Tac-Toe gave him a small domain in which to explore backend responsibilities. The takeaway is not that everyone should avoid coding agents; it is that implementing a modest project can expose the decisions hidden behind a working feature.
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