AI Projects for Developers 2026: 10 Hands-On Ideas with Code

Build a chatbot that answers questions from your own PDF documents. This is the classic starter RAG project — it teaches document loading, chunking, vector embeddings, and LLM-powered retrieval in one build.

Build a CLI tool that accepts a code diff or file and returns a structured code review. Uses few-shot prompting to define the review format. Great for learning structured output and system prompts.

Build a ReACT agent that searches the web, fetches and reads pages, and writes structured research summaries. This project teaches tool use, the ReACT loop, and multi-step agent patterns.

Combine Whisper (speech recognition) with Claude to transcribe audio files and generate structured meeting summaries with action items. Teaches multimodal pipelines.

Build a RAG system over your own Obsidian notes or markdown files. Chat with your personal knowledge base using a local Llama model via Ollama — fully private, no API costs.

Fine-tune Llama 3 8B on a custom domain dataset (legal docs, medical text, code, etc.) using QLoRA on free Google Colab GPUs. Deploy locally with Ollama.

Build an orchestrator + worker multi-agent system. The planner agent breaks a complex research task into subtasks and delegates to specialized worker agents (web search, data analysis, summarization).

Build a tool that converts natural language questions into SQL queries for a database. The LLM reads the schema and generates accurate SQL. Teaches structured output and database integration.

Build a dashboard to evaluate RAG pipeline quality using RAGAS metrics: faithfulness, answer relevancy, and context precision. Compare different chunking strategies and LLMs.

Build a VS Code extension powered by Claude that reads your codebase, understands your code with AST parsing, and suggests context-aware completions and refactors.