Agents & AI engineering
Agents & AI engineering
- agent skills & protocols (45)
- agent-readable web standards (18)
- coding agents (73)
- connectors & integrations (147)
- frameworks & SDKs (109)
- harness & fleet engineering (14)
- observability (5)
- prompt & context engineering (14)
- training & fine-tuning (16)
441 resources · page 10 of 14
Hugging Face Blog
by Hugging Face
Hugging Face blog with posts on open model releases, libraries, datasets and training techniques.
IBM Granite agent cookbook
IBM Granite agent cookbook GitHub repo: notebooks on building agents with Granite models.
IBM Granite legal cookbook
IBM Granite legal cookbook GitHub repo: notebooks applying Granite models to legal research and analysis.
NPI: How to ensure your agent is ready every time you ship (Intercom)
by Intercom
Intercom post on the product-introduction process that checks its Fin agent is ready for each product launch.
Kling AI app
Kling AI web app: workspace for generating videos, images, audio, avatars and effects with Kuaishou's Kling models.
LangChain blog
by LangChain
LangChain blog with tutorials, case studies and technical posts on LangGraph, LangSmith and Deep Agents.
Context Engineering (LangChain)
by LangChain
LangChain post defining context engineering for agents as writing, selecting, compressing and isolating context.
Context Engineering for Agents (LangChain Blog)
by LangChain
LangChain post on context engineering for agents: write, select, compress and isolate strategies.
Docs by LangChain
by LangChain
LangChain documentation home covering LangChain, LangGraph and LangSmith for building and evaluating agents.
LangChain docs: Context engineering
by LangChain
LangChain documentation source on context engineering in agents: controlling model context, tools and state.
LangChain docs: Deep Agents overview
by LangChain
LangChain documentation source on Deep Agents: planning, subagents and a filesystem for long-running agents.
Langfuse blog
by Langfuse
Langfuse blog with product announcements, engineering posts and guides on LLM observability and evals.
Langfuse documentation
by Langfuse
Langfuse documentation: open-source tracing, evaluation and prompt management for LLM applications and agents.
LangGraph docs
by LangChain
LangGraph overview documentation: library for building stateful, graph-based agent workflows in Python.
Lelapa / Vulavula documentation
by Lelapa AI
Lelapa AI Vulavula documentation: speech-to-text and translation API for isiZulu, Sesotho, Afrikaans and other languages.
Agent Memory: How to Build Agents That Learn and Remember (Letta)
by Letta
Letta post on agent memory design: how stateful agents store, edit and retrieve memories, from the MemGPT team.
Linear Docs
by Linear
Linear documentation: guide to the issue-tracking tool's features, including its AI and agent integrations.
Linear Docs: Start Guide
by Linear
Linear start guide for setting up a workspace and working with teams and agents.
Linear Developers: Interaction Best Practices
by Linear
Linear developer guide on interaction best practices for agents that work inside Linear.
Llama Cookbook
by Meta Llama
Meta Llama Cookbook GitHub repo: recipes for Llama inference, fine-tuning, RAG and integrations.
Context Engineering Guide: Techniques for AI Agents (LlamaIndex)
by LlamaIndex
LlamaIndex guide to context engineering, covering memory, tool selection and context window techniques for agents.
Lovable Documentation
by Lovable
Lovable documentation: platform for building and deploying web apps from natural-language prompts.
Machine Learning Systems textbook
by Vijay Janapa Reddi (Harvard University)
Machine Learning Systems: open-access textbook on engineering ML systems, from foundations to hardware and deployment at scale.
Make developer documentation
by Make
Make developer hub with documentation for building custom apps and integrations on the Make automation platform.
Make AI Agent (New) best practices
by Make
Make Help Center best practices for designing AI agents: tools, prompts and testing.
Mastra documentation
by Mastra
Mastra documentation: TypeScript framework for building AI agents, workflows and applications.
MCP docs: Client best practices
MCP documentation on client best practices for surfacing tools and obtaining user consent.
Meta cookbooks
by Meta
Meta Model API cookbook: recipes for building on Meta's API and running Muse open-weight models locally.
Microsoft Agent Framework docs
by Microsoft
Microsoft Agent Framework documentation: building agents and multi-agent workflows in .NET, Python and Go, succeeding AutoGen and Semantic Kernel.
Mistral Cookbook
by Mistral AI
Mistral Cookbook GitHub repo: example notebooks for Mistral models and services from staff, community and partners.
n8n Docs: Advanced AI
by n8n
n8n documentation on AI workflows with LLM providers, agents, tools, memory and MCP servers.
n8n Docs
by n8n
n8n documentation: setting up n8n, building workflows and integrating apps.