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Inspect AI : Writing Reproducible Evals and Safety Tests for LLM Systems
Trex Team
LiteLLM Proxy : Building a Multi‑Provider LLM Gateway with Routing and Budgets
OWASP for LLM Apps : A Practical Security Checklist for GenAI Product Teams
Modern OAuth Security : OAuth 2.1, PAR, RAR, and DPoP for API Engineers
OpenAI Agents SDK in Production : Architecting Reliable Tool‑Using Assistants
Vertex AI Agent Development Kit : From Prototype Agents to Governed Enterprise Deployments
Mastering the Model Context Protocol (MCP) : Standardizing Tool Access, Context, and Permissions for AI Agents
Smolagents : Minimalist Agent Engineering with Tools, Code, and Guardrails
BeeAI Framework : Building Agent Swarms with Open Protocols and Enterprise Controls
LlamaIndex Workflows : Data‑Connected Agents with Repeatable Retrieval Pipelines
AWS Bedrock AgentCore : Memory, Tools, and Event‑Driven Agents on AWS
Haystack 2 Pipelines : Modular RAG, Agents, and Evaluation in Practice
PydanticAI Cookbook : Typed Agents, Validated Outputs, and Schema‑First Reliability
DSPy Prompt Programming : Data‑Driven Optimization for LLM Pipelines
LangGraph : Graph‑Orchestrated Agents with Stateful, Testable Workflows
AutoGen Teams : Designing Multi‑Agent Collaboration Patterns That Don’t Collapse
Semantic Kernel Skills : Plugin‑First Copilots for Enterprise Apps
CrewAI for Real Work : Role‑Based Agent Teams, Delegation, and Safe Autonomy
Continue.dev for Teams : Private Coding Assistants with Repo Context and Policy Controls
Aider in the Loop : Patch‑First AI Pair Programming with CI Safety Nets
OpenHands : Building Task‑Executing Agents for Real Repos, Tickets, and Toolchains
OpenDevin Engineering : Self‑Hosted Software‑Dev Agents for Private Codebases
Langfuse : Open-Source LLM Observability, Tracing, and Prompt Versioning
OpenLIT for GenAI : OpenTelemetry‑Style Observability for LLM Apps
DeepEval : Building an Automated LLM Evaluation Harness That Engineers Trust
Ragas for RAG : Measuring Retrieval, Faithfulness, and Answer Quality at Scale
Phoenix for RAG Debugging : Traces, Retrieval Quality, and Hallucination Triage
Weave by W&B : End‑to‑End Experiment Tracking for LLM Products
Giskard for LLM QA : Detecting Harmful, Biased, and Broken Behaviors Before Launch
Helicone Playbook : Monitoring, Caching, and Cost Controls for LLM APIs
PromptLayer Ops : Managing Prompts, Experiments, and Releases Like Code
promptfoo in CI : Regression Testing Prompts, Tools, and RAG Pipelines
TruLens in Production : Feedback Functions, Scoring, and Continuous Evals
OpenAI Evals Cookbook : Designing Benchmarks for Product‑Grade LLM Features
LM Evaluation Harness : Measuring Model Quality with Reproducible Benchmarks
OpenTelemetry for GenAI : Tracing Token Costs, Tool Calls, and RAG Latency
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