awesome-artificial-intelligence

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
https://github.com/owainlewis/awesome-artificial-intelligence

Last synced: 8 days ago
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Agentic software engineering
- Agent skills and workflows
  - Blueprint - source set of focused agent skills for designing, implementing, testing, reviewing, and shipping software changes.
- Coding agents
  - Codex CLI - source terminal agent with sandbox and approval controls.
  - Gemini CLI - source terminal agent built around Gemini and extensible tools.
  - Cursor CLI
  - Aider - source pair programmer with Git integration and broad model support.
  - OpenCode - source, provider-independent terminal agent with a client-server architecture.
  - Cline - source coding agent available as an editor extension, CLI, and SDK.
  - Continue - source coding agents for IDE and CI workflows with source-controlled configuration.
  - GitHub Copilot coding agent
  - Neo - source, workflow-first terminal coding agent with subagents, skills, sandboxed tools, and multiple model providers.
  - Build Your Own Coding Agent Like Pi
- Deployment and observability
  - SWE-bench - Bench](https://www.tbench.ai/leaderboard/terminal-bench/2.1).
- Software factories and agent orchestration
  - Harness Engineering
  - Codex Orchestration with Symphony - agent runs.
  - How We Built Our Multi-Agent Research System - worker agents, parallel search, evaluation, and operational reliability.
  - Factory - preview control plane for scheduling and coordinating Pi, Codex, and Claude Code workers across Git repositories.
Build AI systems
- Agent frameworks
  - Google Agent Development Kit
  - Pydantic AI
  - LangGraph - level orchestration for long-running, stateful agents.
  - OpenAI Agents SDK
  - Microsoft Agent Framework - based workflows.
- Deployment and observability
  - Langfuse
  - LiteLLM
  - vLLM
- Durable and asynchronous agents
  - Effective Harnesses for Long-Running Agents
  - Running Agents - execution patterns in the OpenAI Agents SDK.
  - Human-in-the-Loop
  - Gemini and Temporal Durable Agent
- Evals and reliability
  - OpenAI Evals - source framework and registry for evaluating language models and systems.
  - Demystifying Evals for AI Agents
  - Promptfoo - team checks for LLM applications.
- Guides and playbooks
- LLM application engineering
  - OpenAI Cookbook
  - Anthropic Prompt Engineering
  - Effective Context Engineering for AI Agents - running agents.
  - 12-Factor Agents
  - OWASP Top 10 for LLM Applications
- Protocols and interoperability
  - Model Context Protocol
  - Agent2Agent Protocol - neutral specification for agent discovery, task delegation, streaming, asynchronous updates, and cross-platform communication.
- Retrieval and data
  - Docling
  - Haystack
Contributing
- Software factories and agent orchestration
  - AI Engineer YouTube channel
Learn
- Books
  - Designing Machine Learning Systems
  - AI Engineering
  - The 100-Page Language Models Book
  - Artificial Intelligence: A Modern Approach
  - Deep Learning
  - Reinforcement Learning: An Introduction
  - Build a Large Language Model from Scratch
  - Hands-On Large Language Models
  - LLM Engineer's Handbook - tuning, serving, and production workflows.
  - Deep Learning: Foundations and Concepts - grounded treatment by Christopher and Hugh Bishop.
  - Understanding Deep Learning
  - Speech and Language Processing
  - Machine Learning Bookcamp - based introduction to building and deploying machine learning systems by Alexey Grigorev.
- Courses
  - Google Generative AI Learning Path
  - Hugging Face LLM Course - tuning, datasets, and modern NLP tooling.
  - Fast.ai Practical Deep Learning - first introduction to deep learning.
  - Full Stack Deep Learning
  - MIT 6.S191: Introduction to Deep Learning
  - DeepLearning.AI Short Courses
  - Stanford CS336: Language Modeling from Scratch
  - Made With ML
  - AI Engineer
- Foundational papers
  - Attention Is All You Need
  - Scaling Laws for Neural Language Models
  - Language Models are Few-Shot Learners - context learning at scale.
  - Constitutional AI
  - Training Compute-Optimal Large Language Models
  - Retrieval-Augmented Generation - intensive tasks.
  - LoRA - rank adaptation for parameter-efficient model fine-tuning.
  - Training Language Models to Follow Instructions with Human Feedback
  - ReAct - using language-model agents.
  - Direct Preference Optimization

Programming Languages

TypeScript 3 Rust 2 Python 2 Go 1 Jupyter Notebook 1

ecosyste.ms

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Tools

Indexes

Applications

Experiments

Awesome

awesome-artificial-intelligence

Agentic software engineering

Agent skills and workflows

Coding agents

Deployment and observability

Software factories and agent orchestration

Build AI systems

Agent frameworks

Deployment and observability

Durable and asynchronous agents

Evals and reliability

Guides and playbooks

LLM application engineering

Protocols and interoperability

Retrieval and data

Contributing

Software factories and agent orchestration

Learn

Books

Courses

Foundational papers