A product discussed on AI Engineer.

Building Turbopuffer: Gergely Orosz (@pragmaticengineer ) × Simon Eskildsen (CEO)
Aug 3, 2026 · 56:30
Gergely Orosz talks with Turbopuffer CEO Simon Eskildsen about how napkin-math engineering took him from high-school Shopify hire to building the S3-based vector database that cut Cursor's bill by 95%. Eskildsen recounts scaling Shopify's infra to 1M RPS, building failure-injection proxy ToxyProxy, and launching Turbopuffer at $1 per million vectors on S3 with an Nginx cache. Cursor became the first customer after he helped debug Postgres/autovacuum issues; he also tells how Jensen Huang ribbed him for choosing CPUs over GPUs. He argues RL workloads are gobbling CPU capacity, making CPU SKUs scarce, and lists six reasons to raise capital, noting his first raise funded R&D and the second let employees cash out. He closes on Turbopuffer's remote culture of campfires and turbo credits for business-class flights.

GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem
Aug 28, 2024 · 19:15
Emil Eifrem, Neo4j co-founder and CEO, argues that GraphRAG—combining knowledge graphs with vector search—significantly improves RAG application accuracy, ease of development, and explainability. Citing studies, he reports accuracy gains of 3x (Data.org), 75-77% (LinkedIn), and Microsoft's finding that GraphRAG enables answering entirely new question types. He demonstrates Neo4j's Knowledge Graph Builder, which auto-generates graphs from PDFs, Wikipedia, and YouTube, making graph creation accessible. Eifrem frames this as the next evolution in search after PageRank and Google's knowledge graph, urging developers to adopt GraphRAG for richer context and better AI outcomes.
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