LLM Engineering8 min read
Retriever k-value tuning for RAG: the right top-k
How to pick the right k value for your RAG retriever. The 3-step tuning process, the failure modes of k=3 and k=20, and the sweet spot in between.
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136 posts in total
LLM Engineering8 min read
Combining vector stores in RAG: multi-source retrieval
How to combine multiple vector stores in one RAG pipeline. The merge pattern, the deduplication rule, and when multi-source beats a single index.
LLM Engineering8 min read
FAISS vector stores in production RAG
How to use FAISS for production RAG. Index types, persistence, memory trade-offs, and the 4 settings that decide if FAISS beats a managed vector DB.
AI Engineering in Practice8 min read
Real-time agent debugging with Langfuse traces
How to debug a live agent incident using Langfuse traces. The search patterns, the 5-minute workflow, and the post-mortem that catches the root cause.
AI Engineering in Practice9 min read
Agent cost optimization from trace data
How to use Langfuse trace data to find where your agent burns tokens. The 4 queries, the cost-per-user view, and the 50 percent savings patterns.
AI Engineering in Practice8 min read
Langfuse + Grafana: agentic AI monitoring
How to combine Langfuse traces with Grafana dashboards for agent monitoring. The integration, the panels, and the alerting that catches real problems.
AI Engineering in Practice8 min read
Prometheus performance analysis for agentic AI systems
How Prometheus metrics surface performance bottlenecks in agentic AI. The 3 queries, the alert rules, and the dashboard that finds hot loops fast.
AI Engineering in Practice8 min read
Stress testing agentic AI systems beyond the laptop
How to stress test an agentic AI service before it ships. Concurrency, tokens, latency budgets, and the load profile that simulates real traffic.
LLM Engineering8 min read
Automated evaluation pipelines for agentic AI systems
How to wire eval pipelines into CI so every agent change is scored automatically. The nightly job, the regression gate, and the dashboard that matters.
LLM Engineering8 min read
Dynamic evaluation metric loading in Python
How to load evaluation metrics dynamically in a Python eval pipeline. The registry pattern, entry points, and the test override that makes CI fast.
LLM Engineering9 min read
LLM judges: enforcing reasoning with explicit rationales
Why LLM judges without explicit reasoning drift, and how chain-of-thought rationales make their scores defensible. The prompt, the parser, the trust.
LLM Engineering9 min read
LLM-as-a-judge: production evaluation framework for agents
How to build an LLM-as-a-judge evaluation framework for agentic AI. The prompt, the rubric, the bias controls, and the loop that catches regressions.
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