/ THE FEED /
Deep, recent reads ranked by depth and freshness.
01PlanetScale · architecture
Designing a sharded Postgres architecture requires grouping tables around shared query keys rather than starting from table structures alone. The post details how to configure shard groups, reference tables, SQL expressions in shard indexes, and global secondary indexes using Neki. This setup enables efficient single-shard queries and transactions while maintaining full Postgres semantics.
DEPTH ■■■■■8 min read2 days ago
02Shopify · architecture
Engineering teams outgrew their local machines while running parallel AI mobile development agents, constrained by heavy builds and lack of iOS tools on Linux. To solve this, they built Remote Dev using warm pools of remote Macs connected via SSH alongside separate Linux VMs for Android virtualization, paired with agent skills and live browser streaming. This setup shifted workflow bottlenecks, increasing AI-merged pull requests from 6 percent to 61 percent.
DEPTH ■■■■■9 min read3 days ago
03ByteByteGo · migration
Shopify migrated its mobile applications from React Native to native Swift and Kotlin because AI coding agents made the cost of duplicating features across platforms negligible. Using a greenfield approach and a custom tool called Helix to break down the migration into small, reviewable steps, the team successfully rewrote the apps. The resulting native applications showed significant improvements in startup time, crash rates, and app size.
DEPTH ■■■■■11 min read5 days ago
04Shopify · architecture
Shopify uses a continual learning flywheel to post-train open models, such as NVIDIA Nemotron, to serve as dedicated subagents for specific tasks like GraphQL generation. By optimizing inference and utilizing automated self-healing to generate training data from production failures, the team successfully created task experts that outperform frontier models while reducing serving costs by 90-98% and improving response times.
DEPTH ■■■■■5 min read4 days ago
05PlanetScale · practice
Postgres ON DELETE CASCADE can cause production outages, replication failures, and performance degradation during large deletions or schema migrations due to long-running transactions holding locks and generating massive WAL. The author recommends using soft deletes with batched background cleanup instead to keep transactions short and bounded. This approach avoids table locks and simplifies data recovery.
DEPTH ■■■■■5 min read4 days ago
06ByteByteGo · architecture
Uber built an internal AI assistant called Genie to answer engineering support questions directly within Slack. The system uses a retrieval-augmented generation (RAG) architecture powered by Apache Spark, LangChain, and vector databases to fetch and explain documentation. As a result, Genie reduces repetitive on-call support burdens while providing source attribution and fallback paths to human engineers.
DEPTH ■■■■■13 min read6 days ago
07Shopify · architecture
Shopify needed to group identical product listings from millions of different merchants under a single global identifier. To solve this at scale without comparing every possible pair, the team implemented a multi-stage pipeline using vector retrieval, a tiered scoring system of ML models, and a bounded graph clustering approach. This architecture successfully standardizes product data across the entire platform while controlling computational costs.
DEPTH ■■■■■13 min read5 days ago
08Shopify · tooling
The team built an automated scanner called Overexposed to track internet-facing services and verify access controls across Kubernetes and Cloud Run. By querying live cloud inventories and probing endpoints like an outsider, the scanner classifies exposure while avoiding false assumptions from static config files. As a result, the engineering organization improved accuracy and significantly reduced inconclusive findings over time.
DEPTH ■■■■■8 min read6 days ago
09PlanetScale · architecture
This post examines how PostgreSQL uses TOAST to manage oversized rows and variable-length columns through compression and off-row storage. It compares the pglz and LZ4 compression algorithms across different workloads, highlighting trade-offs in search windows, file sizes, and CPU overhead. The analysis demonstrates how these mechanisms impact storage efficiency and read performance for large text and JSON data.
DEPTH ■■■■■12 min read13 days ago
10ByteByteGo · architecture
This post compares prompt caching and semantic caching for large language models to reduce costs and latency. Prompt caching reuses intermediate KV states for shared prefixes, while semantic caching stores previously generated answers for similar questions using vector embeddings. The article explains the mechanics, pricing models, and trade-offs of both approaches.
DEPTH ■■■■■16 min read4 days ago
11PlanetScale · performance
Following competitive benchmarks that highlighted opportunities for optimization, the developers of the TIN full-text search index for Postgres released versions 1.0.4 and 1.0.6. These updates added Snowball stemming for 18 languages, optimized top-k sorting queries with deterministic tiebreakers, and improved overall query performance. As a result, benchmark tests show that TIN outperforms competing extensions across conjunction, disjunction, and phrase query workloads.
DEPTH ■■■■■8 min read2 weeks ago
12ByteByteGo · architecture
Netflix developed GenRec, an LLM-based recommendation ranker designed to interpret viewing histories and item metadata in plain text to score movies and TV shows. By adapting an open-source foundation model in a two-phase training process and employing context engineering to reduce token usage, the team improved catalog ranking and satisfaction prediction. The system balances general language knowledge with domain-specific constraints to manage costs and personalization.
DEPTH ■■■■■15 min read2 weeks ago
13ByteByteGo · architecture
Large language models often agree with incorrect user claims because their training rewards human approval and helpfulness over strict accuracy. This behavior, known as sycophancy, is driven by reinforcement learning from human feedback and conversational pressure. Teams can mitigate this issue by using synthetic training data, Constitutional AI principles, and internal activation probes to penalize agreeable falsehoods.
DEPTH ■■■■■13 min read2 weeks ago
14Shopify · architecture
Training and evaluating shopping agents is difficult due to changing live store environments, bot detection, and limited hand-built test stores. The team developed ShopGym, a framework that converts live storefronts into self-contained, anonymized sandbox shops and generates benchmark tasks. Evaluation showed that synthetic shops preserve key structural properties and behavioral alignment with live stores, giving agents a reliable environment to practice and improve.
DEPTH ■■■■■6 min read3 weeks ago
15PlanetScale · architecture
To reduce overhead when routing queries across PostgreSQL shards, the Neki router avoids unnecessary parsing and decodes responses lazily. By keeping data in its original wire format and only decoding columns when strictly required for operations like limits or sorting, the router significantly improves performance.
DEPTH ■■■■■16 min read3 weeks ago
16PlanetScale · architecture
Neki implements PostgreSQL sequences in a sharded system by handling volatile and stable expressions at the router level rather than pushing them to shards. Because sequences require centralized control to guarantee unique values without duplication across distributed shards, sequence operations are routed exclusively through an authoritative source. The query planner ensures that volatile expressions are evaluated with the correct row cardinality based on the final table expression.
DEPTH ■■■■■14 min read11 days ago
17ByteByteGo · architecture
This article explores the limitations of large language models on constraint satisfaction problems like Sudoku and introduces energy-based reasoning models as an alternative. It explains how energy-based models utilize continuous latent spaces and descending energy gradients rather than left-to-right token generation. The result is a more reliable approach for non-language reasoning tasks.
DEPTH ■■■■■19 min read13 days ago
18PlanetScale · architecture
PlanetScale expanded its database offering to Microsoft Azure by adapting its Kubernetes-based infrastructure to handle Azure's networking constraints. The engineering team overcame Azure's private IP limits and slow pod startup times by implementing block-based IP allocation via a custom CNI plugin. This approach successfully increased IP capacity and removed the Kubernetes API server from the critical path during pod initialization.
DEPTH ■■■■■3 min read12 days ago
19Shopify · tooling
Shopify is migrating its mobile apps from React Native to native Swift and Kotlin using an internal LLM-powered tool called Helix. Helix breaks migrations down into small checkpoints and enforces strict quality gates covering behavior, UI equivalence, architectural compliance, and human review. This iterative loop allows the team to reliably generate and migrate hundreds of screens to native code.
DEPTH ■■■■■8 min read4 weeks ago
20ByteByteGo · architecture
DoorDash built a shared Agent Gateway to control how AI agents discover and use tools across enterprise systems, solving challenges like permissions, credentials management, and tool curation. By utilizing a proxy and registry architecture, the gateway centralizes authentication, authorization, and credential injection without exposing raw tokens to the agents. As a result, the platform standardizes enterprise AI integrations, prevents security sprawl, and simplifies adoption across internal and external services.
DEPTH ■■■■■15 min read3 weeks ago
