AI Software & Tools
Updated 2 May 2025
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AI Software & Tools
The practical side. If the AI Learning Centre explains how AI works, this section covers how to build with it — the languages, frameworks, developer tools, and infrastructure that turn ideas into running systems.
This landscape moves fast. New tools appear weekly. What’s here is opinionated: we cover the things that matter, with clear guidance on what to learn first and why.
Programming Languages
The languages that power AI development. Short answer: Python dominates, TypeScript is rising for AI applications, Rust is emerging for performance-critical infrastructure.
Frameworks
The libraries you’ll actually use:
pytorch/— The foundation for research and traininghugging-face/— The ecosystem: models, datasets, training toolslangchain/— Chains, agents, RAG orchestrationllamaindex/— Data ingestion and retrieval frameworkvercel-ai-sdk/— Build AI features in web apps (SvelteKit, Next.js)
Developer Tools
What you work with day to day:
coding-assistants/— Claude Code, Cursor, Copilot, Windsurfvector-databases/— Pinecone, Weaviate, ChromaDB, pgvectorinference-servers/— Ollama, vLLM, TGI (run models locally or at scale)observability/— LangSmith, Weights & Biases, Arize (see what your AI is doing)
Infrastructure
The layer below:
cloud-providers/— AWS Bedrock, GCP Vertex AI, Azure OpenAImlops/— Deployment, monitoring, model managementcompute/— GPUs vs TPUs, spot instances, cost management
Protocols & Standards
The glue:
mcp/— Model Context Protocol. The universal plug for AI tools.openai-api-spec/— The de facto API standard everyone implements
Where to Start
If you’re a developer coming to AI fresh:
- Know Python — Non-negotiable. The entire ecosystem runs on it.
- Get Ollama — Run models locally in one command. Experiment freely.
- Use a coding assistant — Claude Code, Cursor, or Copilot. Learn by doing.
- Build a RAG app — ChromaDB + an embedding model + Claude API. Your first real AI application.
- Understand AI Agents — Where everything is heading.
Go Deeper
- AI Learning Centre — Understand the theory behind the tools
- AI Agents — The pattern these tools serve
- RAG & Retrieval — The most common application architecture
- AI Companies — Who builds these tools and platforms
- AI Intelligence Hub — Back to the hub home