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Best practices for developing on Vercel

These defaults are optimized for AI coding agents (and humans) working on apps that deploy to Vercel.

  • Treat Vercel Functions as stateless + ephemeral (no durable RAM/FS, no background daemons), use Blob or marketplace integrations for preserving state
  • Edge Functions (standalone) are deprecated; prefer Vercel Functions
  • Don't start new projects on Vercel KV/Postgres (both discontinued); use Marketplace Redis/Postgres instead
  • Store secrets in Vercel Env Variables; not in git or NEXT_PUBLIC_*
  • Provision Marketplace native integrations with vercel integration add (CI/agent-friendly)
  • Sync env + project settings with vercel env pull / vercel pull when you need local/offline parity
  • Use waitUntil for post-response work; avoid the deprecated Function context parameter
  • Set Function regions near your primary data source; avoid cross-region DB/service roundtrips
  • Tune Fluid Compute knobs (e.g., maxDuration, memory/CPU) for long I/O-heavy calls (LLMs, APIs)
  • Use Runtime Cache for fast regional caching + tag invalidation (don't treat it as global KV)
  • Use Cron Jobs for schedules; cron runs in UTC and triggers your production URL via HTTP GET
  • Use Vercel Blob for uploads/media; Use Edge Config for small, globally-read config
  • If Enable Deployment Protection is enabled, use a bypass secret to directly access them
  • Add OpenTelemetry via @vercel/otel on Node; don't expect OTEL support on the Edge runtime
  • Enable Web Analytics + Speed Insights early
  • Use AI Gateway for model routing, set AI_GATEWAY_API_KEY, using a model string (e.g. 'anthropic/claude-sonnet-4.6'), Gateway is already default in AI SDK needed. Always curl https://ai-gateway.vercel.sh/v1/models first; never trust model IDs from memory
  • For durable agent loops or untrusted code: use Workflow (pause/resume/state) + Sandbox; use Vercel MCP for secure infra access