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Saas for Startups
Playbooks and case studies covering saas for startups.
Rate-Limit LLM API Calls Per Tenant Without Dropping Requests
One noisy tenant is eating your shared OpenAI quota and 429-ing everyone else. Here is a runnable per-tenant token-bucket limiter in Redis that meters by estimated tokens and queues excess requests instead of dropping them.
Cache LLM Embeddings in Redis Without Stale Vector Drift
Caching OpenAI embeddings in Redis cuts cost, but naive keys leave stale vectors polluting your retrieval layer. Here's a content-addressed cache pattern that self-invalidates on every edit — with runnable code.
Supabase vs. PlanetScale vs. Neon: Pick the Right Serverless DB
Most Supabase vs PlanetScale vs Neon comparisons benchmark cold starts on toy workloads. Here's how each one actually behaves under multi-tenant SaaS load — and which choice will force you to re-platform when your first enterprise customer lands.
Stream LLM Responses to the Browser Without Losing State
Streaming LLM output to the browser looks trivial until you need per-user state, accurate token billing, and safe recovery when the client drops. Here is a working pattern with FastAPI, SSE, and React that gets all three right.
Rate-Limit LLM API Calls Across Workers Without a Queue
Your OpenAI feature works fine on one worker and dies on four. Here's how to build a distributed token-bucket limiter in Redis with an atomic Lua script — no queue, no broker, no rewrites.
Stream LLM Responses to a React Frontend Without Melting
Your ChatGPT-style feature stalls for 6 seconds before rendering a single token. Here is how to stream LLM responses to React properly — with auth, aborts, and partial JSON that does not double-render on flaky networks.
Rate-Limit an LLM API Without Dropping User Requests
Watching 429s spike in Sentry every morning? The fix isn't smarter retries — it's a sliding-window token ledger that holds requests locally until your budget refills. Here's a runnable Python tutorial.
Pinecone vs. pgvector: Which Vector Store Fits Your AI App
Filtered vector search is the query pattern that breaks most head-to-head Pinecone vs pgvector benchmarks. Here's how to pick the right vector store for your AI app based on the dimensions that actually matter in production.
What Is a BFF? Why Your Mobile App Deserves Its Own API
A shared API for web and mobile sounds efficient until your mobile team is making four round-trips to render one screen. Here's why the Backend for Frontend pattern is really about org structure, not network hops.
FastAPI vs. Django for AI Model Serving: Pick the Right One
Your p95 latency isn't creeping past 800ms because Django is slow. It's creeping up because a synchronous, GIL-bound model call is blocking your event loop — and FastAPI won't fix that on its own. Here's how to actually choose.
Microservices vs. Monolith for Your First AI Feature
Most architecture advice for shipping AI assumes you're either Google or greenfield. Here's the actual decision framework for a Series A team adding the first inference feature to a Django or Rails monolith.
Questions to Ask Before Hiring an AI SaaS Dev Partner
Most AI SaaS vendor pitches look identical until you ask the right questions. Here are the 15 a Series A founder should run through before signing — and the answers that separate operators from demo-builders.