1. Start with an internal pilot

Ship AI first to admins or staff—draft helpers, classification, search summaries—where wrong answers are annoying, not legally risky. That forces you to add logging, rate limits, and feature flags before customers see the button. Customer-facing chat can come after the seam is boring.

2. Laravel: service class, HTTP client, queues

Wrap the vendor API in a dedicated class (or package) injected where needed. Use Laravel’s HTTP client with timeouts and retries; store API keys in config / env only. Anything over a few hundred milliseconds belongs in a queued job with status polling or notifications—not a blocking web request.

Expose features through routes you control (web or API) and policies you already trust. If a Next or mobile client needs streaming, Laravel can still own the upstream call and stream or chunk the response outward.

3. WordPress: plugin, not theme

Put integration code in a must-use or standard plugin so it survives theme changes. Use wp_remote_request() (or a small Guzzle wrapper) with the same timeout discipline as Laravel. Register REST routes for editor or front-end consumers; check capabilities with current_user_can on every mutating endpoint.

Long work should run via Action Scheduler, WP-Cron, or a real queue on the host—never a synchronous page load in functions.php on every view. Blocks and shortcodes should call thin REST endpoints, not embed keys or call vendors directly.

4. Shared rules for both stacks

  • No provider keys in JavaScript bundles, theme assets, or public repos.
  • Redact or avoid PII in prompts where possible; log metadata, not full transcripts, unless policy allows.
  • Version prompts and model IDs in code or config so rollbacks are possible.
  • Cache idempotent reads (embeddings, summaries) with clear invalidation when source content changes.

5. When to stop and split services

If PHP workers are constantly tied up on LLM latency or your host forbids outbound AI calls, extract a small sidecar service (still your code) that Laravel or WordPress calls over HTTP with auth. The CMS or framework stays the system of record; the AI worker scales independently.

Integrating AI into existing Laravel or WordPress projects is mostly discipline at the edges: one integration layer, async by default, and permissions you already use everywhere else. The model is interchangeable; the seam is what you maintain for years.