Saturday, October 31, 2026

Fall reading - 2026

Happy Halloween! It's been a while, but here's my list of "good reads" (As usual, a hat tip to Hacker News, Reddit, Youtube, Spotify, Twitter, Bluesky and my other feeds).

Tag(s)                      Link
aiOpen Source Is Dead. Long Live Open Source. — Saoud Rizwan, Cline - YouTube
aiSteer your RAG agent with Jev, Here’s How - YouTube
aiZ.AI And The Chinese Open Source Moment - YouTube
architectureSloc Cloc and Code 4.0 (scc) - Finding the files that need the most attention | Ben E. C. Boyter
dataEgres: A Postgres-compatible database for heavy, multi-tenant workloads — Manish R Jain
dataHow Razorpay refreshes its data warehouse 10x faster with graphs and indexes - YouTube
dataWhy DuckDB 2.0 is faster | MotherDuck
javaADTs (Algebraic Data Types) in Java | Rock the JVM
javaAlgebraic Data Types (ADTs) in Java - YouTube
javaClose to the Metal: Modern Low-Latency Development - YouTube
javaEmbracing Virtual Threads with Helidon [I/O] Inside Java Podcast 65 - YouTube
javaEscaping Java's Allocation Gravity with Value Classes By Clément de Tastes, Remi Forax - YouTube
javaEveryday JSON in Java - YouTube
javaHardwood: Building a Parquet Parser From Scratch With a Little Help From AI by Gunnar Morling - YouTube
javaImplementing Efficient Last Stream Elements Gatherer in Java
javaJava - The Year of the Runtime! - YouTube
javaJust-In-Time Compilation for Java Performance: Recent and Ongoing Improvements - YouTube
javaMaking Arena.ofConfined() Even Cheaper in JDK 28 - Inside.java
javaOOP vs. Data-Oriented Programming: Which One to Choose? - YouTube
javaQuarkus Insights #256: What is Floci? - YouTube
javaTeaching an Old Handle New Tricks: From Core Reflection to FFM by Maurizio Cimadamore, Viktor Klang - YouTube
javaTo Cache or Not to Cache Virtual Threads - Quarkus
javaTornadoVM v8.0.0: Meet TC, TornadoVM's Own Compiler
javaUnder the Hood: How Lucene 10+ leverages Java 21 features - Community Over Code Glasgow 2026 - YouTube
javaWill Valhalla Fix Tony's Billion Dollar Mistake? by José Paumard, Remi Forax - YouTube
rust,systemTokioConf 2026 - Zero-Copy Chaos. When everything you knew about tokio... by Wojciech Kargul - YouTube
systemAnnouncing blob-stream: a Kafka alternative for no fuss, low cost high volume streaming - bitdrift Blog
systemComputers are bad, actually | Kyle Kingsbury, Jepsen - YouTube
systemConcurrency vs. Throughput: why more parallelism can make databases slower — PlanetScale
systemGit at any scale · Cursor
systemHow Tailscale helped find the SQLite WAL-Reset bug
systemIntroducing Dogwood: runtime verification for AI agents | AWS Open Source Blog
systemIntroduction to property-based testing, by Antithesis & Alperen Keles - YouTube
systemOpen-Sourcing Streaming Proof: Verifying Ordering and Delivery Guarantees | StreamNative
systemReliability Lessons From SQLite - Richard Hipp | SSW 2026 - YouTube
systemThe lifecycle of a sharded Postgres query — PlanetScale
systemThe place where leaking abstraction, data races and security vulnerabilities all meet - YouTube
systemWe are replacing RocksDB with SurrealKV 1.0 | SurrealDB
systemWe won, what now? | Will Wilson | Bug Bash 2026 - YouTube

Until next time!

Saturday, August 01, 2026

Summer reading - 2026

Some reading before Summer wraps (As usual, a hat tip to Hacker News, Reddit, Youtube, Spotify, Twitter, Bluesky and my other feeds).

Tag(s)                      Link
aiAgent orchestration, simplified - YouTube
aiBenchmarking Coding Agents on Databricks’ Multi-Million Line Codebase | Databricks Blog
aiBeyond local tools: Deep dive into MCP with Spring AI by James Ward / Maximilian Schellhorn - YouTube
aiBurnout Will Go Up, and We’re Doing It to Ourselves with Nathen Harvey - YouTube
aiContributor Poker and Zig's AI Ban | Loris Cro's Blog
aiHarness Engineering is not Enough: Why Software Factories Fail — Dex Horthy, HumanLayer - YouTube
aiHow does Claude Code *actually* work? - YouTube
aiHow to Automate AI Evals (Correctly) - YouTube
aiHow to Prepare for Coding Interviews (with HackerRank) - YouTube
aiI Hated Every Coding Agent, So I Built My Own — Mario Zechner (Pi) - YouTube
aiNothing has changed about software engineering | Ben Eggers | Bug Bash 2026 - YouTube
aiSkill Distillation | Tomasz Tunguz
aiThe layoffs will continue till we learn to use AI
aiUber: Leading engineering through an agentic shift - The Pragmatic Summit - YouTube
aiUsing LLM in the shebang line of a script | Simon Willison’s TILs
aiWeek 2: Interning at a YC startup
aiWhat you need to learn from claw-code repo
ai,javaDevnexus 2026 - Keynote - Its Up To Java Developers to Fix Enterprise AI - Rod Johnson - YouTube
data30x faster than Prometheus: How we rebuilt Elasticsearch as a leading columnar metrics datastore - Elasticsearch Labs
dataApache Fluss: A Streaming Storage for Real-Time Lakehouse (Jark Wu) - YouTube
dataApache Gluten at Microsoft William Chen, Microsoft - YouTube
dataDataFusion + DuckLake — Zac Farrell | Data Debug SF - YouTube
dataDemocratizing Machine Learning at Netflix: Building the Model Lifecycle Graph | by Netflix Technology Blog | May, 2026 | Netflix TechBlog
dataDuckDB-Quack Announcement at AI Council 2026 - YouTube
dataFrom Storage Formats to Open Governance: The Evolution to Apache Polaris (Prashant Singh) - YouTube
dataHartmut Armbruster – What If We've Been Scaling Stream Processing Wrong All Along #bbuzz - YouTube
dataMatthias Niehoff – DuckDB beyond the notebook #bbuzz - YouTube
dataOpen Source Friday with Gunnar Morling with Hardwood - YouTube
dataScott Haines: Unifying Open Lakehouse Governance via Policy Portability, Seattle/Bellevue April 2026 - YouTube
dataThe Deconstructed Database at Datadog - YouTube
dataWriting Custom Table Providers in Apache DataFusion - Apache DataFusion Blog
data​Performant Interactive Queries | Jayant Shrivastava, Gene Bordegaray, Justin O'Dwyer, Datadog - YouTube
data,javaAnkit Jain – From Inverted Index to Columnar Vectorized Execution Search #bbuzz - YouTube
data,javaHardwood 1.0: A Fast, Lightweight Apache Parquet Reader for the JVM - Gunnar Morling
data,java,relnoteIntroducing Apache DataFusion Java 0.1.0 - Apache DataFusion Blog
golang,systemP99 CONF 2025 | Parsing Protobuf as Fast as Possible by Miguel Young de la Sota - YouTube
java#JavaNext Language Features - YouTube
javaHow Netflix Uses Java - 2026 Edition - YouTube
javaJDK 8 to 25 Without the Pain - Engineering a Modern Java Platform - YouTube
javaJava 26: Better Language, Better APIs, Better Runtime - YouTube
javaJava AOT in Production at Netflix - YouTube
javaJava Memory Management Best Practices - YouTube
javaJava is Memory Efficient - Inside Java Podcast 59 - YouTube
javaNative and AI Interoperability with JDK 25 and the FFM API - YouTube
javaOn HotSpot Error Files and Useful Tools - Mostly nerdlessMostly nerdless
javaPractical Python AI in Java with GraalPy - Sachin Pikle - YouTube
javaQuarkus Community Call: Quarkus 4 - Migration to Vert.x 5 & SmallRye Common I/O archive support - YouTube
javaReflecting on HAT: A Project Babylon Case Study - YouTube
javaSIMD Vectors in the HotSpot JVM - Auto Vectorization and the Vector API - YouTube
javaScaling ArchUnit with Nebula ArchRules | by Netflix Technology Blog | May, 2026 | Netflix TechBlog
javaSpring Native: The Future of Fast and Efficient Spring Applications by Alina Yurenko @ Spring I/O - YouTube
javaThe .join() That Should Be a Bug | Kronotop
javaThe Java Agent Skills Kit - by Markus Eisele
java,rust10 Things Rust Could Learn from Java (and 5 Things Java Should Probably Steal Back) by Scott Gerring - YouTube
java,systemAPI Gateway Performance Doubling in Practice (English) · GitBook
java,systemApache Cassandra Contributor Meeting | June 10th, 2026 - YouTube
java,wasmBytecode Alliance — Endive and the Next Chapter of WebAssembly on the JVM
java,wasmEndive: Java Virtual Machine meets WebAssembly on CNCF wasmCloud - YouTube
jvmConcurrency Patterns for Modern High Performance Kotlin Servers | Bowen Feng - YouTube
jvm,systemSandboxing Script Extensions with GraalVM | by Christian Humer | graalvm | Jul, 2026 | Medium
miscHow I Doubled eBay’s Productivity - And Still Got Fired - YouTube
rust,systemRust zero-cost abstractions vs. SIMD
rust,systemSlateDB: An Object-Native LSM for Online Systems — SlateDB
rust,systemTokioConf 2026 - Building a Production Control Plane with Tokio by Pooja Kale - YouTube
systemAWS re:Invent 2025 - Large-scale software deployments: Inside Amazon S3’s release pipeline (STG352) - YouTube
systemEveryone gets faster writes: We turned off FPW's in Neon
systemFinding zombies in our systems: A real-world story of CPU bottlenecks | by Pinterest Engineering | Pinterest Engineering Blog | Apr, 2026 | Medium
systemFrom fork() to Fleet: Designing an Agent Sandbox Cloud — Abhishek Bhardwaj, OpenAI - YouTube
systemHow OpenAI delivers low-latency voice AI at scale | OpenAI
systemMany Databases 1 LSM Engine - OpenData - YouTube
systemP99 CONF 2025 | Building a Fast Lock-free Queue for Trading Systems by Sarthak Sehgal - YouTube
systemP99 CONF 2025 | Squeezing Every Millisecond: How We Rebuilt the Datadog Lambda by AJ Stuyvenberg - YouTube
systemSupercharging Redpanda Streaming with profile-guided optimization
systemThe performance bug hiding in our billing settings | Oblique
systemUnlocked Conference — Towards Faster Inference, Daniela Miao (Momento) & Samuel Shen (Tensormesh) - YouTube
systemUnlocked conference - Beyond fork: Memory-Efficient Snapshots for Valkey - Jim Brunner (AWS) - YouTube
systemZero Bloat Postgres Queue | Scaling Postgres 416 - YouTube

Until next time!

Thursday, May 21, 2026

An obligatory post about vibe coding

(An obligatory post about vibe coding - everyone needs to make at least one, they say.)

I've been using my $20 Claude subscription to tinker on some side projects in my personal time.

It's astonishing how much can be done with the basic plan, which makes me wonder how much it will actually cost once the VC subsidies end.

I've also gained quite a bit of insight without going neck deep into multi-agent, spec driven, ralph loop, <insert latest buzzword> and such bleeding edge techniques or tools. 

I've stuck to a simple workflow 

  1. It involves Claude code on my Macbook, an architecture.md, a backlog.md and a simple claude.md. I also get the AI to create a more detailed but transient plan-<complex-feature>.md for complex, work in progress features
  2. I use Claude in the browser for learning, research and brainstorming

I've iterated on my personal workflow over multiple projects. It's been "productive", meaning I've created many experimental projects, including some that may have legs. Some have been purely personal and custom productivity type of tools. I've not really read the code it has produced because all of it was done while I was watching TV or doing chores. Some even in programming languages I have no prior experience with.

Learnings (using Claude as of May 2026):

  • Despite having Claude.md and tests it can make subtle mistakes. On occasion
    • It leaves docs in an inconsistent state and requires a reminder/instruction to find and fix them
    • It forgets to read some of the instructions in Claude.md
    • It writes docs in incorrect folders ignoring the designated docs/ folder
    • It accidentally deletes features as part of larger changes, esp if those changes cannot be tested (UI)
    • It freezes
    • (My work related/professional experience is different which I won't speak about here)
  • Judgement and Taste absolutely matter
    • Identifying problems worthy of solving, brainstorming potential solutions and implementing them in the correct order is really where a good human engineer does really well
    • Producing a usable application that is based on the most popular frameworks, on which the AI is trained on is a shockingly easy and delightful experience. Can't say the same about juggling multiple agents and reviewing lots of AI generated PRs from multiple team members though 

Here are some of my older experiments: https://github.com/AshwinJay/ai-experiments

Here is one that I may actually use one day: https://github.com/AshwinJay/project-tracker 

Until next time.