Building Like Cursor / Perplexity / v0 — Backend Architecture of Trending AI Tools

Manish Garg
Manish Garg Associate of (ISC)² · RingSafe
Apr 29, 2026
9 min read
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Cursor, Perplexity, v0, Claude Artifacts, Lovable — the products defining 2026 AI UX. Their backends share patterns: streaming LLM gateways, smart context windows, agentic loops with tool use, observability-first design. This module reverse-engineers the architecture and shows how to build similar.

The most interesting AI products of 2025-2026 are not chatbots — they are productivity tools with deep AI integration. Cursor for code, Perplexity for search, v0 for design, Lovable for full-stack generation. They share architectural patterns. This module is what you would build if you were building one of these.

The shared core architecture

All of them have: (1) Frontend with optimistic UI + streaming, often Next.js for SSR + React Server Components; (2) Edge function for low-latency request routing and rate limit; (3) LLM gateway (multi-provider, caching, retries); (4) Context assembly — pulling relevant data from various sources into the LLM prompt; (5) Agentic loop with tool use for multi-step tasks; (6) Storage — Postgres for users + history, vector DB for semantic search, Redis for cache; (7) Observability — every LLM call logged for debugging, cost analysis, eval; (8) Eval pipeline — automated regression testing on prompt/model changes. Each tool customises this, but the spine is consistent.

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