Short, opinionated guides. From an MCP server to a multi-agent pipeline — each blueprint walks you through one project, end to end, with the boring decisions already made.
Three commands. A local LLM running on your laptop, with an OpenAI-compatible HTTP API ready to call from anywhere.
Build a personal bookmarks server that lets Claude save, search, and organize your links — Node.js, SQLite, and the official MCP SDK.
Build a document Q&A system with Python, LlamaIndex, and Qdrant — ingest your docs and query them with natural language.
Build a research agent that searches the web, summarizes articles, and compiles reports — deployed as a REST API.
Create a GitHub Action that reviews pull requests with Claude — catches bugs and posts inline comments automatically.
Build a content production pipeline with CrewAI — a researcher, writer, and editor that collaborate to produce articles.
Run Llama 3.1 locally with Ollama, benchmark it, then deploy a production API with vLLM and Docker.
Build a terminal assistant called "ask" — answer questions, explain files, generate shell commands, and pipe in data.
Build a research agent with Google's Agent Development Kit and Gemini — custom tools, sessions, and one-command deploy to Cloud Run.
Build a job application assistant where four AI agents collaborate via LangGraph — analyze postings, tailor resumes, write cover letters, and review everything.
Build a code-review swarm as a Claude Code plugin — sub-agents, hooks, custom slash commands, an MCP tool server, and a background audit worker, packaged as a publishable plugin.
A team snippet library exposed as a remote MCP server: Supabase OAuth 2.1 with dynamic client registration, workspaces with RLS-enforced sharing, and one `claude mcp add` to wire your whole team's saved prompts into Claude.
Three ADK agents — orchestrator, researcher, writer — each deployed as its own Cloud Run service and wired together with Google's open Agent2Agent (A2A) protocol.
Document Q&A end-to-end on GCP — Cloud SQL Postgres with pgvector, Vertex AI for embeddings and Gemini, FastAPI on Cloud Run. Task-typed embeddings, metadata-filtered retrieval, and optional contextual chunking. IAM auth all the way down, no passwords.
Serve Google's open Gemma 4 on a serverless Cloud Run GPU — one Dockerfile, one deploy command, unauthenticated behind a single HTTPS URL. Then call it straight from a static webpage with streaming, no backend of your own.
Go from idea to live website using AI — no coding required. Design, copy, and deploy in one sitting.
Connect your tools and let AI handle the busywork — email triage, data entry, and report generation using Make or Zapier.
Create a custom AI tailored to your job — with your documents, your tone, and your processes baked in.
Deploy an AI chatbot that answers customer questions using your FAQ and docs — live in under an hour.
Upload your company docs or notes and create an AI-powered search interface anyone on your team can use.
Set up a system that drafts blog posts, social media, and newsletters from your ideas — with your voice and brand.
Master the frameworks that get consistently great output — structured prompts, chain-of-thought, and few-shot patterns applied to real tasks.
Add an AI teammate to your Slack workspace that answers questions, summarizes threads, and triggers workflows.
Curate content from your favorite sources and let AI draft, format, and schedule a newsletter — no writing block, no coding.
Upload your notes and textbooks and get AI-generated flashcards, practice quizzes, and personalized study plans.
Generate on-brand posts, suggest hashtags, plan a content calendar, and schedule across platforms — all with AI.
Transcribe meetings, extract action items, generate summaries, and send follow-up emails — automatically.
Let AI write your copy, suggest layouts, optimize for SEO, and turn your projects into a polished personal site.