cartero Tuesday, August 11, 2026 · No. 25887
Meta

Podcast: If AI Is Sentient Then So Is 'Age of Empires II'

A surreal but compelling LLM experiment with Age of Empires II; how a Texas city sold land meant for a park to a data center company; and the Madison Square Garden hack.

X / Twitter

Behind the Blog: Salesforce Beach

This week, we discuss talking aloud to computers, Cannes, and “Engineering Creativity: Guac Is Extra."

MySQL

Database

Qualcuno esperto di database potrebbe darmi un parere su un progetto? Dettagli in dm submitted by /u/ReflectionNo3897 [link] [comments]

PostgreSQL

Lætitia AVROT: Stop Punishing Your Postgres for a Crash That Won't Happen

There is a misconception I keep running into, and it causes real harm in production. People are afraid to increase checkpoint_timeout. They think a longer timeout means a longer recovery after a crash. So they set it to 5 minutes. Some set it to 1 minute. And then they wonder why their Postgres is struggling. Let me dismantle this fear, argument by argument. First: serious people have a replica 🔗If you care about availability, you have at least one replica you can fail over to.

PostgreSQL

Christophe Pettus: All Your GUCs in a Row: enable_hashagg

PostgreSQL 13 made hash aggregation memory-safe by allowing it to spill to disk — but that safety introduced a surprise regression for some queries on upgrade.

MySQL

Migrating Etsy’s database sharding to Vitess

Etsy has maintained a sharded MySQL architecture since around 2010. This database cluster contains most of Etsy’s online data and is made up of ~1,000 tables distributed across ~1,000 shards. Over the last 16 years, it has grown significantly: combined, these tables have over 425 TB of data and receive roughly 1.7 million requests per second. Etsy engineers access our MySQL data through a proprietary object-relational mapping (ORM). The ORM has a corresponding model for each MySQL table. W...

Artificial Intelligence

Making Ads Count: Using MMoE and Auxiliary Tasks to Better Connect Buyers & Sellers

When buyers search on Etsy, they need to quickly and easily find the perfect item. At the same time, sellers need to be confident their unique products are being seen by the right customers. Our Ads Search ranking model, which is built on a multitask learning foundation, is the critical link in this connection. Recently, we identified an opportunity to drive more meaningful buyer engagement by enhancing our model’s ability to predict purchase intent. We achieved this via a dual-pronged impr...

RAG

Shaping Product Understanding with Contrastive Reinforcement Learning

Etsy’s marketplace is defined by the creativity and craftsmanship of our sellers and the hundreds of millions of highly diverse products they offer. You can find silversmiths who cold-forge recycled sterling silver, weavers who dye raw fleece with indigo and black walnut, and ceramicists who throw stoneware on a kick wheel. These details define each product and often determine whether it matches a buyer’s taste, style, and interests. Sometimes buyers know exactly what they want, searching...

PostgreSQL

Andrei Lepikhov: A Generative Postgres Digest: From Noise to Signal

Why do we still waste time browsing YouTube and news sites looking for interesting content? Why rely on someone else's algorithm — when Claude, for instance, retains conversation history in one form or another and can therefore assess our actual interests? Maybe it's time to take control of shaping our own "information bubble"?In systems programming, reliability, maintainability, and extensibility usually matter more than new features. That makes AI agents genuinely hard to apply well. If I...

Caching Strategies

I’m building evict-benchmark — a C++ playground to implement and benchmark cache eviction policies

I have been learning database internals recently, especially buffer pools and page replacement policies. Instead of only reading about them, I started building a small C++ project called evict-benchmark where I implement eviction policies from scratch and benchmark how they behave under different access patterns. Then I want to run them against workloads such as: Uniform random accesses Sequential scans Zipfian / skewed accesses Hot-and-cold workloads Looping scans Mixed OLTP-style patterns ...

MySQL

Migrating Etsy’s database sharding to Vitess

Etsy has maintained a sharded MySQL architecture since around 2010. This database cluster contains most of Etsy’s online data and is made up of ~1,000 tables distributed across ~1,000 shards. Over the last 16 years, it has grown significantly: combined, these tables have over 425 TB of data and receive roughly 1.7 million requests per second. Etsy engineers access our MySQL data through a proprietary object-relational mapping (ORM). The ORM has a corresponding model for each MySQL table. W...

Artificial Intelligence

Making Ads Count: Using MMoE and Auxiliary Tasks to Better Connect Buyers & Sellers

When buyers search on Etsy, they need to quickly and easily find the perfect item. At the same time, sellers need to be confident their unique products are being seen by the right customers. Our Ads Search ranking model, which is built on a multitask learning foundation, is the critical link in this connection. Recently, we identified an opportunity to drive more meaningful buyer engagement by enhancing our model’s ability to predict purchase intent. We achieved this via a dual-pronged impr...

RAG

Shaping Product Understanding with Contrastive Reinforcement Learning

Etsy’s marketplace is defined by the creativity and craftsmanship of our sellers and the hundreds of millions of highly diverse products they offer. You can find silversmiths who cold-forge recycled sterling silver, weavers who dye raw fleece with indigo and black walnut, and ceramicists who throw stoneware on a kick wheel. These details define each product and often determine whether it matches a buyer’s taste, style, and interests. Sometimes buyers know exactly what they want, searching...