Data Tinkerer

What the Data Crowd Was Reading in April 2026

Tools, techniques and deep dives worth reading that I came across in April 2026.

May 7 • Data Tinkerer

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April 2026

The Bitter Lesson (of Decision Making)

Why simple rules often beat human judgment over time

Apr 30 • Data Tinkerer

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How Airtable Saved Millions by Cutting Archive Storage Costs by 100x

Airtable moved petabytes of cold log data out of MySQL and built a cheaper archive layer on S3 and Parquet without sacrificing fast queries.

Apr 23 • Data Tinkerer

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How Pinterest Used Multimodal AI to Help Millions of Shoppers

Inside the multimodal AI pipeline that converted images, metadata and search behavior into scalable shopping discovery.

Apr 16 • Data Tinkerer

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What the Data Crowd Was Reading in March 2026

Tools, techniques and deep dives worth reading that I came across in March 2026.

Apr 2 • Data Tinkerer

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March 2026

How Notion Scaled AI Q&A to Millions of Workspaces

Kafka, Spark and Ray powering low-latency, high-throughput search pipelines

Mar 26 • Data Tinkerer

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What the Data Crowd Was Reading in February 2026

Tools, techniques and deep dives worth reading that I came across in February 2026.

Mar 12 • Data Tinkerer

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February 2026

How Shopify Scales Taxonomy Evolution Across 10,000+ Categories With Multi-Agent AI

From reactive manual curation to continuous taxonomy evolution grounded in merchant reality.

Feb 26 • Data Tinkerer

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How LinkedIn Built a Pipeline That Scales to 230M Records/sec Without Breaking SLAs

From partition strategy to adaptive throttling, the playbook behind Venice’s ingestion evolution.

Feb 19 • Data Tinkerer

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What the Data Crowd Was Reading in January 2026

Tools, techniques and deep dives worth reading that I came across in January 2026.

Feb 5 • Data Tinkerer

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January 2026

How to Build a Recommendation System at Scale: Insights from Instacart

A Senior ML Engineer on production constraints, rules vs ML and the workflow behind large-scale recommender systems

Jan 29 • Data Tinkerer and Ahsaas Bajaj

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How DoorDash Saves Tens of Millions of Dollars Per Year by Detecting Fraud 30× Faster

A daily anomaly detection system that cut discovery time from 100+ days to under three.

Jan 23 • Data Tinkerer

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