FiveM development guide

FiveM AI script generator: what a production-ready workflow should include

A useful FiveM AI script generator should do more than return a Lua block. Real resources have dependencies, a manifest, client/server boundaries, configuration, framework integration, failure cases and a private testing process. This guide explains what to ask for and what to verify before a resource reaches your live server.

1. Start by naming the framework and dependencies

State whether the resource targets QBCore, ESX, ox_lib or standalone FiveM. Mention inventory, targeting, database and UI dependencies that matter. If the AI guesses your stack, it can produce code that looks plausible but calls exports your server does not use.

2. Ask for the complete resource shape

my-resource/ ├── fxmanifest.lua ├── config.lua ├── client.lua ├── server.lua ├── shared.lua -- only if genuinely useful └── README.md

Not every resource needs every file, but requesting the structure forces the system to think about what belongs on the client and what must remain on the server.

3. Treat the client as untrusted

Money, inventory, permissions and rewards should be calculated or confirmed server-side. A client event may ask to complete an action, but the server should verify the player's state, permissions, relevant inventory and position before accepting it. Never trust a client-supplied payout just because the normal UI would not send a strange number.

ClientPrompts, markers, animations, UI and local effects.
ServerPermissions, rewards, inventory changes and authoritative checks.

4. Make configuration explicit

Locations, payouts, cooldowns, item names and framework options should be configurable where appropriate. This keeps balance changes out of core logic and makes the resource easier to maintain across servers.

5. Test failure paths

A generated resource that only works on the happy path is not production-ready.

6. Ask AI to review the result after it runs

Bring back console errors, resource warnings and unexpected behavior. A second pass with actual runtime evidence is more useful than repeatedly regenerating the whole script.

7. A better prompt

Build a FiveM resource for [QBCore/ESX/standalone]. Requirements: - Produce the complete resource file structure. - Keep rewards, permissions and inventory changes server-side. - Validate every network event. - Put balance values in config where practical. - Document dependencies and install steps. - Include a private test checklist. Do not invent exports without clearly labeling assumptions. After implementation, review the resource for duplicate-event exploits, missing permission checks and failure cases.

8. Use the result as a starting point, not blind production code

AI can save time on scaffolding, repetitive logic and debugging, but you still own the release. Review the files, understand the dependencies, test privately and keep a rollback.

Stellar workflow: start from a focused resource brief, generate the related files together, test on your own server and return with errors or requested changes.

9. Version control and rollback should be part of the workflow

Even a small FiveM resource can break a live server when a dependency changes or an event path behaves differently under real player load. Keep generated resources in version control, make focused commits and preserve the last known-good version. If an AI-assisted change touches several files, review the diff before deploying it. A rollback is much easier when the previous working manifest, configuration and server logic are still available.

For larger systems, separate experimental work from production. Test in a private development server with representative dependencies enabled. If the resource changes database tables, inventory items or framework configuration, document those migrations so a rollback does not leave the server in a half-updated state.

10. Performance matters after correctness

Do not optimise a resource before it works, but do not stop at “no console errors” either. Check whether client loops run every frame unnecessarily, whether server callbacks perform repeated expensive work and whether network events send more data than needed. Measure before changing code. An AI assistant can help identify suspicious loops and repeated lookups, but profiling on the actual server is stronger evidence than a generic claim that a rewrite is faster.

11. What to check before calling the resource finished

This checklist is intentionally boring. Production reliability usually comes from boring checks done consistently rather than one clever code generation.

Official references

Before shipping, check the current platform documentation: FiveM event security guidance; FiveM events documentation.