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 14 of 14
NAVER D2
by NAVER
NAVER D2 Hello World: Korean engineering blog from NAVER developers.
Notion Help: Guides
by Notion
Notion Help Center guides to workflows, integrations and features.
OpenAI API Skills guide
by OpenAI
OpenAI API skills guide: creating reusable skills for Responses API shell tools and Agents API sandboxes.
PennyLane documentation
PennyLane documentation: Python library for differentiable quantum computing and hybrid quantum-classical ML.
PyGOD
by PyGOD team
PyGOD documentation: Python library for outlier and anomaly detection on graphs.
ReAct
by Shunyu Yao et al. (Princeton University and Google Research)
arXiv paper (2022) "ReAct: Synergizing Reasoning and Acting in Language Models", introducing ReAct, interleaving reasoning traces and tool actions in language models.
Refactoring Hermes with 1,393 agents
Nous Research case study of Hermes Agent refactoring its own codebase with 1,393 subagents, with cost and results.
Roo Code docs: Context poisoning
by Roomote
Roo Code documentation on context poisoning: recognising and recovering from corrupted context in long agent sessions.
Scaling Managed Agents: decoupling brain from hands
by Anthropic
Anthropic engineering post on the architecture of its hosted Managed Agents harness, separating model reasoning from execution.
SHAP documentation
SHAP documentation: game-theoretic method and library for explaining ML model predictions.
Building production-ready agentic systems: Lessons from Shopify Sidekick
by Shopify
Shopify Engineering post on lessons from building the Sidekick agent: architecture, LLM judges calibrated to human labels and RL pitfalls.
Durable AI (Temporal Documentation)
Temporal documentation on durable execution for AI applications and agents that resume after crashes or timeouts.
Texterra
by Ivannikov Institute for System Programming (ISP RAS)
Texterra from ISP RAS: Russian text-analysis system for information extraction built on open structured knowledge.
Training language models to follow instructions with human feedback
by Long Ouyang et al. (OpenAI)
arXiv paper (2022) "Training language models to follow instructions with human feedback", describing InstructGPT and the RLHF post-training pipeline.
TRL documentation
by Hugging Face
Hugging Face TRL documentation: trainers for SFT, DPO, GRPO and other post-training methods.
Universal Commerce Protocol (UCP)
by Universal Commerce Protocol project
Universal Commerce Protocol site: open standard for agents and platforms covering catalogue, checkout and orders.
AI SDK docs: Loop control
by Vercel
Vercel AI SDK documentation on loop control: stop conditions and step control for agent loops.
How we made v0 an effective coding agent (Vercel)
by Vercel
Vercel engineering post on v0's coding-agent pipeline: dynamic system prompts, streaming fixes and autofixers.
Berkeley Advanced LLM Agents (SP25)
Berkeley CS294/194-280 Advanced Large Language Model Agents (Spring 2025): lectures on reasoning, coding agents and agent safety.
EASA AI Concept Paper Issue 2
by European Union Aviation Safety Agency (EASA)
EASA AI Concept Paper Issue 2: guidance on assuring Level 1 and 2 machine-learning applications in aviation.
Context Engineering for AI Agents: Lessons from Building Manus
by Manus
Manus post on context engineering lessons: designing around the KV cache, masking tools and using the filesystem as memory.
Model Context Protocol Specification 2025-06-18
MCP specification version 2025-06-18, covering authorisation, elicitation and structured tool output.
OpenTelemetry generative AI semantic conventions
OpenTelemetry page on generative AI semantic conventions for LLM and agent telemetry, now moved to a dedicated repository.
SpikingJelly
by SpikingJelly team (Peking University)
SpikingJelly documentation (in Chinese): PyTorch framework for deep learning with spiking neural networks.
Tülu 3
by Nathan Lambert et al. (Ai2)
arXiv paper (2024) describing Tülu 3, a fully open post-training recipe that introduced RLVR.