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Stack

AI Developer Stack - LLM APIs, Vector DBs and Deployment Tools

For developers shipping AI features without infrastructure overhead. This stack prioritizes API-first access and managed services—you pay for what you use, not for ops. Each tier trades cost for control: start with OpenAI's simplicity, graduate to Claude's reasoning, then self-host inference when LLM spend becomes your largest line item.

Prototype

Ship your first AI feature this week. Pick this if you're validating an idea, building a weekend project, or learning embeddings. You'll hit limits fast—but that's the point. Move to Production when you need reliability.

$0/mo
$0-$50/mo
  • OpenAI API (PAYG) · The industry standard LLM. Fast, reliable, and you only pay per token. No commitment needed.
  • Pinecone Free · Serverless vector search with zero DevOps. Free tier gives you 100K vectors—enough to prototype semantic search or RAG.
  • Vercel Hobby · Deploy your API in seconds. Free tier includes edge functions; perfect for wrapping LLM calls in a production-like environment.
  • LangChain (open source) · Glue between your app and LLMs. Handles prompts, chains, and memory so you don't reinvent orchestration.
Recommended

Production

You have users and need uptime. Pick this tier when your idea works and you're ready to optimize for reliability, better model quality, and observability. You're still on managed services; you're just paying for guarantees.

$0/mo
$100-$400/mo
  • Anthropic Claude API · Superior reasoning and longer context than GPT-3.5. Worth the switch when accuracy or nuance matters more than speed.
  • Qdrant Cloud · Self-hosted vector DB with managed hosting. Gives you filtering, metadata, and better latency than Pinecone at scale.
  • Helicone · Logs every LLM call, tracks costs, and alerts on failures. Essential for debugging production AI without losing money to bad prompts.
  • Railway · Postgres + APIs + background jobs in one platform. More flexible than Vercel for stateful AI services.

Scale

LLM API costs are now your biggest expense. Pick this tier to run your own inference, fine-tune models, or use GPUs for batch processing. You're trading managed simplicity for unit economics.

$0/mo
$400+/mo
  • Together AI · Run open-source LLMs (Llama, Mistral) at 10x cheaper inference than proprietary APIs. Use when throughput matters more than model quality.
  • Weaviate Cloud · Enterprise vector DB with hybrid search and reranking. Justifies the cost only when you need sub-100ms latency at massive scale.
  • LangSmith · Trace, debug, and evaluate every LLM interaction. Turns observability into a feedback loop for prompt optimization.
  • Modal · Rent GPUs by the minute for fine-tuning, batch inference, or async jobs. Pay only for compute time, not idle capacity.