---
type: source
title: "The ONLY AI Tech Stack You Need in 2026"
description: "Cole walks through his stable, AI-first, mostly open-source tech stack for 2026, organized by category, arguing you should pick capabilities-focused tools that work for you and stick with them rather than obsessing over the tools themselves."
youtube_id: 21_k2St8bBI
url: https://www.youtube.com/watch?v=21_k2St8bBI
slug: the-only-ai-tech-stack-you-need-in-2026
published: 2025-11-05
duration: "0:34:26"
recency_rank: 56
raw: "../raw/the-only-ai-tech-stack-you-need-in-2026.md"
tags: [tech-stack, tooling, ai-engineering]
created: 2026-07-21
updated: 2026-07-21
---

# The ONLY AI Tech Stack You Need in 2026

This video is a full tour of Cole Medin's end-to-end tech stack for building AI software going into 2026, deliberately AI-first because he does not see another way to do it these days. He frames the whole thing around a single mantra: capabilities over tools. The point is not to obsess over the nitty-gritty of each tool but to have a stable, trusted default for every layer so you can get straight to solving the actual problem. For each choice he also names a couple of alternatives to show the tradeoffs.

He organizes the stack into layers. Core infrastructure: Postgres (via Neon or Supabase) as the default database with Redis or Valkey for caching, Claude Code plus Archon as the AI coding assistant, and n8n for no-code prototyping. AI agents: Pydantic AI as the single-agent framework, LangGraph for multi-agent orchestration, Arcade for agent tool authorization and security, and Langfuse for observability. RAG agents: Docling for file and document extraction and Crawl4AI for websites, Postgres with pgvector for vector storage, Mem0 for long-term memory (framed as a form of RAG), Neo4j plus Graphiti for knowledge graphs, Ragas for RAG evaluation, and Brave or Perplexity for web search. Web automation adds Playwright and Browserbase (Stagehand and Director).

The full-stack layer covers FastAPI, React with Vite, shadcn and Tailwind, Streamlit for quick Python UIs, Lovable for beautiful agentic frontends, Supabase or Auth0 for auth, Stripe for payments, and Sentry for monitoring. Deployment and infra: Render (with Google Cloud for enterprise, RunPod for GPU workloads, Digital Ocean for owned VMs), Docker for containerization, GitHub Actions for CI/CD, Pytest and Jest for testing, and CodeRabbit for AI code review. He closes with self-hosted and local options (Ollama, Open WebUI, SearXNG, Caddy), many bundled into his open-source Local AI package, and reiterates: find what works, stay adaptable, and stay a problem solver rather than a tool expert.

## Concepts covered

- [Capabilities Over Tools](../concepts/capabilities-over-tools.md)
- [Abstraction Distraction](../concepts/abstraction-distraction.md)
- [Agentic RAG](../concepts/agentic-rag.md)
- [Knowledge Graphs](../concepts/knowledge-graphs.md)
- [Memory Systems](../concepts/memory-systems.md)
- [Structured vs Unstructured Data](../concepts/structured-vs-unstructured-data.md)
- [Agent Observability](../concepts/agent-observability.md)
- [Multi-Tenant Agents](../concepts/multi-tenant-agents.md)
- [Local & Self-Hosted AI](../concepts/local-ai.md)

## Entities

- [Cole Medin](../entities/people/cole-medin.md)
- [Claude Code](../entities/tools/claude-code.md)
- [Archon](../entities/tools/archon.md)
- [Pydantic AI](../entities/tools/pydantic-ai.md)
- [LangGraph](../entities/tools/langgraph.md)
- [Arcade](../entities/tools/arcade.md)
- [Langfuse](../entities/tools/langfuse.md)
- [Docling](../entities/tools/docling.md)
- [Crawl4AI](../entities/tools/crawl4ai.md)
- [Graphiti](../entities/tools/graphiti.md)
- [Neo4j](../entities/tools/neo4j.md)
- [Mem0](../entities/tools/mem0.md)
- [Postgres](../entities/tools/postgres-pgvector.md)
- [Neon](../entities/tools/neon.md)
- [n8n](../entities/tools/n8n.md)
- [Browserbase](../entities/tools/browserbase.md)
- [Playwright](../entities/tools/playwright.md)
- [CodeRabbit](../entities/tools/code-rabbit.md)

## Key moments

- **[0:00:54]** States the core mantra: capabilities over tools; problems come first, don't obsess over tools
- **[0:02:26]** Core infrastructure begins: Postgres via Neon/Supabase, Redis/Valkey caching
- **[0:04:26]** AI coding assistant layer: Claude Code + Archon as the primary driver
- **[0:06:30]** AI agent framework layer: Pydantic AI (single) and LangGraph (multi-agent)
- **[0:08:42]** Arcade for agent authorization and tool security; MCP server SDK demo
- **[0:10:58]** Langfuse for agent observability, called a step you cannot skip
- **[0:12:12]** RAG stack: Docling (files), Crawl4AI (websites), Postgres+pgvector storage
- **[0:15:24]** Knowledge graphs: Neo4j engine + Graphiti library; agentic RAG over both vector DB and graph
- **[0:18:52]** Web automation agents: Crawl4AI live tools, Playwright, Browserbase/Stagehand/Director
- **[0:21:59]** Full-stack layer: FastAPI, React+Vite, shadcn/Tailwind, Streamlit, Lovable
- **[0:26:51]** Deployment/infra: Render, Google Cloud, RunPod, Digital Ocean, Docker, GitHub Actions, CodeRabbit
- **[0:31:54]** Local/self-hosted options: Ollama, Open WebUI, SearXNG, Caddy, all in the Local AI package

## Transcript

[Raw transcript](../raw/the-only-ai-tech-stack-you-need-in-2026.md)
