AI Tools & Resources
34 external tools + 2 interactive demos — curated for AI engineers and product builders.
Interactive Demos
Hands-on tools built into this site — no sign-up needed
Try Models4
Playgrounds and chat interfaces to explore LLMs directly
OpenAI's flagship product. Best starting point for understanding what LLMs can do.
Anthropic's assistant. Exceptional at long documents, coding, and nuanced reasoning.
Test Gemini models with full API access. Free generous quota for development.
Run Llama 3 and Mistral at extraordinary speed. Best for latency benchmarking.
Build with APIs4
SDKs and platforms to integrate LLMs into your applications
GPT-4o, o1, embeddings, DALL-E 3 and Whisper — the most widely used AI API.
Claude API with 200K context window. Strong tool use, vision, and safety controls.
Open-source model hub. Run Llama, Mistral, and thousands of specialised models.
Fast, affordable API for open-source models. Good for cost-sensitive applications.
RAG & Vector Search4
Store and search embeddings to ground your AI in real knowledge
Managed vector database. Easiest to get started, scales to billions of vectors.
Open-source vector DB with hybrid search (vector + keyword). Self-host or cloud.
Lightweight local vector DB — the fastest way to prototype a RAG pipeline.
High-performance vector engine with rich filtering. Great for on-premise setups.
Frameworks & Orchestration5
Build pipelines, agents and multi-step AI workflows
The most widely used LLM framework. Chains, RAG, agents, and 100+ integrations.
Build stateful agent workflows as graphs. Best for complex multi-step reasoning.
Data framework for LLMs. Specialises in connecting models to documents and databases.
Multi-agent framework with role-based agents. Simple API for collaborative AI teams.
Microsoft Research's multi-agent conversation framework. Good for code generation flows.
Observability & Evals4
Trace, evaluate and improve AI quality in production
Tracing, prompt management and evaluation for LangChain apps. Best-in-class UX.
Open-source LLM observability — traces, evals, prompt versioning, cost analytics.
Evaluation platform for LLM apps. Run evals, track regressions, compare prompts.
ML experiment tracking and model monitoring. Widely used in fine-tuning workflows.
Fine-tuning & Training4
Adapt pre-trained models to your domain and style
Parameter-efficient fine-tuning library — LoRA, QLoRA, and adapters in one package.
2x faster fine-tuning with 70% less memory. Supports Llama 3, Mistral, Gemma.
Serverless GPU compute. Run fine-tuning jobs with a simple Python decorator.
Managed fine-tuning for GPT-4o mini and GPT-3.5. No GPU setup needed.
Multimodal AI4
Work with images, audio and video alongside text
OpenAI image generation — best prompt adherence of any commercial model.
Open-source image generation. Run locally on a laptop GPU or via API.
OpenAI open-source speech-to-text. Best-in-class transcription, 99 languages.
Realistic text-to-speech and voice cloning. Best quality for production voice AI.
Learn Deeper5
Courses, papers and references to go beyond this curriculum
Andrew Ng's short courses on LLMs, RAG, agents and fine-tuning. Practical and fast.
Practical deep learning — top-down, code-first. Best for understanding model internals.
Build GPT from scratch in Python. The best video series for understanding transformers deeply.
The 2017 paper that introduced the Transformer architecture. Essential primary source.
OpenAI researcher's deep technical posts on agents, RAG, RLHF, and diffusion models.