Mastering AI agent observability: From black-box to traceable systems
On this page What is AI agent observability? The shift from, “Is it up?” Agent vs traditional observability For multi-agent systems The 5 pillars of agent observability Security, privacy, and compliance Implementing AI agent observability OpenTelemetry integration Best practices for implementation Common pitfalls Closing words AI agent observability is the practice of collecting, analysing, and […]
Exploring LLM-as-a-Judge
On this page What is LLM-as-a-Judge? Types of LLM-as-a-Judge How LLM-as-a-Judge works Why use LLMs as judges Designing prompts/rubrics/scoring Building reliable systems Mitigating bias and failure modes Pros, cons and alternatives Choosing models and tools Using LLM judges Future directions Closing LLM-as-a-judge refers to using large language models to evaluate the outputs of other AI […]
Architecting Alpha: The modern quant lifecycle
On this page The shift from micro-scale tomeso-scale Research Backtesting Execution Post-trade analytics Conclusion An overview of how modern quant research is shifting toward large-scale AI agents, and why GPU-native infrastructure, unified scheduling, and rigorous experiment tracking are becoming foundational to turning exploration into deployable trading systems. In this report, we explore how Weights & […]