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27 pages · Updated July 20, 2026
Pages
- The Tokenomics Problem With Coding Agents
- Introducing HoneyHive v2
- Trace and evaluate Microsoft Copilot Studio agents with HoneyHive
- Open-Source vs OpenAI: Is it Time to Move On?
- Our Open-Source Model Selection Guide
- What LLM Benchmarks Can and Cannot Tell You
- Product Update: Offline Evaluations
- The Agent Development Lifecycle
- The Evolution of Observability: From Monoliths to AI Agents
- Towards Evaluation Driven Development with MongoDB and HoneyHive
- Introducing Annotation Queues
- Scale Agent Governance with Microsoft's ASSERT and HoneyHive
- Product Update: Traces, Datasets, and Online Evaluation
- How to Escape the Eval Cold Start Problem
- How to Evaluate Compound AI Systems
- Tracing RAG applications in production with LanceDB and HoneyHive
- Introducing Role-Based Access Control
- How to evaluate AI applications
- Introducing HoneyHive Skills
- HoneyHive Recognized in the 2026 Gartner® Market Guide for AI Evaluation and Observability Platforms
- Search That Learns From You: Building Adaptive Retrieval Systems using Qdrant & HoneyHive
- Evaluations Across the Agent Development Lifecycle
- HoneyHive achieves SOC 2 Type II, GDPR, and HIPAA compliance
- Standardizing AI Observability Before It Breaks: A Case Study on 73,000 Agent Schemas
- Avoiding Common Pitfalls in LLM Evaluation
- Announcing HoneyHive
- 2025: A Year in Review