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AI Architect Academy

Architecture practice / deployment boundaries

Choose the lifetime.
Then choose the cloud.

A request, a job, an entity and a batch run have different failure modes. Make that decision before combining frameworks or opening a production tenant.

Vercel

A bounded front door

Source template; tenant deployment must be verified

Choose this sidecar when a portal needs a bounded API to admit work and return job status from a separate worker.

Portal → authenticated API → worker job → status

Keep durable jobs out of the request. Limit input, execution time, model spend and tool authority.

Evidence before production

Denied caller, oversized input, upstream timeout, failed model call, rollback and cost per successful request.

Open the sourceRead current platform docs

Railway

Work that outlives a request

Source template; durability requires an implementation

Choose a container worker when an agent needs its own process, dependencies and restart policy.

Portal → admitted job → worker → result; workflow and traces stay separate

The starter is an in-memory teaching fixture. Add a durable queue and store before promising recovery.

Evidence before production

Restart recovery, duplicate delivery, cancellation, terminal model failure, tenant isolation and trace redaction.

Open the sourceRead current platform docs

Cloudflare

One durable identity

Reference design; no Academy deployment receipt

Choose an entity boundary when a session or workspace needs coordinated state and connections.

Worker → named Durable Object → state and alarms

Map identity to a tenant-scoped entity. Keep retrieval authorization and irreversible tools outside model control.

Evidence before production

Cross-tenant lookup, reconnect, concurrent writes, alarm replay, storage recovery and revocation.

Open the sourceRead current platform docs

Google Cloud

A finite evaluation run

Reference design; no Academy deployment receipt

Choose a Cloud Run job for bounded container work that completes and exits; use a service for HTTP.

Approved run → Cloud Run job → evidence store → independent review

One service account per authority class. Bound retries, execution time, concurrency and data access.

Evidence before production

Partial task failure, retry safety, identity isolation, immutable fixture inputs and a failing exit code.

Open the sourceRead current platform docs

Compose after proving the boundary

A runtime is one part of the system.

Hermes or OpenClaw can be the agent runtime. n8n can orchestrate admitted workflows. Langfuse can record model traces and evaluation results. Keep credentials, job state, customer data and release authority explicit; adding a tool does not make the starter durable or multi-tenant.

A customer-owned deployment needs a version pin, an operating owner, a tested recovery path and a support boundary. These are source templates and reference designs, with no claim of a verified customer deployment.