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reopt Handbook
reopt Handbook
Vercel Enterprise AI Platform

Platform Foundation

Platform ArchitectureAI SDK RuntimeAI Gateway Control Plane

Execution Runtime

Workflow Durable ExecutionSandbox Tool RuntimeMCP Enterprise DataQueues and Async Jobs

Prompt and Quality

Prompt Engineering and GuardrailsRAG and Retrieval-Augmented GenerationObservability and Evaluation

Operations

Security GovernanceCost and ReliabilityDeployment and AI CI/CD

Scenarios

Customer Support Agent ArchitectureInternal Research Agent ArchitectureApproval Backoffice AutomationCoding Orchestration

Orchestration Patterns

Graph-Centric OrchestrationPractical Orchestration PlaybookMulti-Agent Architecture

Appendix

Migration GuideReferencesVerificationUpdates
Handbook›Vercel Enterprise AI Platform›Verification
한국어KOEnglishEN

Verification

A checklist for validating an enterprise AI platform on Vercel.

Written and reviewed by Eric Han · Co-founder & CTO, reopt

2026-10-23 primary-source review

Compared official migration, limits, runtime, npm metadata, and the Gateway model catalog.

CheckResult
Security and development MCPSeptember–October advisory conditions and fixes, 16.3+ managed instructions, MCP client example reviewed
RuntimeNode.js 24; Next.js 16.3+ Node-only routes/pages
SDKai 7.0.148; workflow 5.2.3; @ai-sdk/workflow 2.0.80
APIisStepCount; instructions; telemetry integration; stateless streaming
Limits300s default; 800s / 1800s Beta distinction; 4.5 MB payload
ModelsGateway catalog: openai/gpt-6.1-sol; anthropic/claude-sonnet-5.5

This is a primary-source and example review. It does not claim execution against production accounts, Windows devices, or paid services.

AI SDK 7 migration · Workflow 5 changes · Functions limits · Node.js versions · Global Config rename.

Earlier verification records

The following content records the earlier review.

Use this checklist before treating the platform as ready for enterprise AI workloads.

Platform

CheckPass condition
ArchitectureExperience, control, runtime, async, and governance planes are named
GatewayModel routing, fallback, and cost attribution exist
WorkflowLong-running tasks and approvals are durable
SandboxRisky tool execution is isolated
QueuesBatch and fan-out work has retry and poison handling

Quality

CheckPass condition
Prompt contractsRole, task, constraints, tools, and output schema are explicit
RAGRetrieval respects permissions and freshness
EvaluationQuality metrics run before release
ObservabilityTraces connect model, tool, latency, cost, and errors

Operations

CheckPass condition
SecurityIdentity, secrets, WAF, provider policy, and approval gates are governed
CostBudget alerts and workload classes exist
DeploymentPreview, canary, rollback, and kill switch are ready
IncidentOwners, runbooks, and escalation paths are documented

Related docs

Platform Architecture

Split enterprise AI systems into experience, control, runtime, async, and governance planes.

References

Source categories for adapting the Vercel enterprise AI platform handbook.

Verification

Enterprise Project Architecture · A checklist for validating enterprise project architecture and operations.

Verification

New Brand Marketing Strategy · A checklist for validating the brand marketing handbook before use.

Verification

AI Security and Compliance Operations · A checklist for validating AI security and compliance operations.

References

Source categories for adapting the Vercel enterprise AI platform handbook.

Updates

Change log for the Vercel Enterprise AI Platform handbook.

On this page

2026-10-23 primary-source reviewEarlier verification recordsPlatformQualityOperations