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Practical AI Evals in Production
How to create evaluation loops that improve reliability without slowing product iteration.
AI OpsEvaluationProduct
Signal Data
LevelEasy
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AI Engineering Journal
Building practical AI systems with clear product outcomes and resilient architecture.
Deep dives on retrieval systems, evaluation loops, and execution tradeoffs that matter in production.
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Featured Writing
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RAG Latency Tradeoffs That Matter
A practical guide to balancing retrieval depth and response speed in user-facing AI systems.
RAGPerformanceArchitecture
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Prompt Versioning for Product Teams
Prompt changes should be auditable, tested, and tied to business metrics.
PromptingTeam ProcessProduct
Builds
Selected Projects
2025
AI Support Copilot
Built a retrieval-augmented assistant for high-volume support workflows with human-in-the-loop controls.
Reduced average support resolution time by 34% while improving first-response quality.
Next.jsRetrievalLLM Ops
2024
LLM Guardrails Dashboard
Built a metrics dashboard for hallucination rate, safety policy adherence, and response quality drift.
Enabled policy violation alerts and weekly quality trend reporting for prompt changes.
TypeScriptMonitoringEvaluation
2024
Research Digest Automation
Implemented a ranking and summarization pipeline that produces executive-ready research digests.
Cut manual curation workload by 70% for weekly internal AI briefings.
Workflow AutomationSummarizationData Pipelines