Puma, Falcon, or Pitchfork? Choosing the right web server for your Ruby app is a big decision. In my @railsconf talk, I break down the key differences, performance trade-offs, and how to choose the right one for your specific application. piped.video/gLYx83CaCNw?si=s2zi…

If coding agents will write most of our code, what happens with our communities and sense of ergonomics? How does it impact our compilers and tools?

Anyone who know anyone working @WhatsApp or @facebook that can help please? RT for reach 🙏

Wrote down some thoughts on how to pivot a SaaS in 2026 (the AI era). But most importantly: Competing on features is dead bannerbear.com/blog/how-to-p…

One month to go for rubyevents.org/events/deccan… Lets go India @rails community! We want to see you there!

The revolt of the reader bcantrill.dtrace.org/2026/09…

We're excited to welcome Manu J to Deccan Queen on Rails 2026. A Rubyist since 2006, Manu has worked as a Rails and DevOps consultant, founder, and is now an Engineering Manager at Kipsu. Join us in Pune this October. 🚂 #DeccanQueenOnRails #RubyOnRails #RailsCommunity #Ruby

yrby is getting to a really strong place. I’m running it in production, and I’ve expanded quite a bit beyond my meager early ambitions I want it to be the first-class answer for realtime collaboration in Ruby/rails, without having to reach for node or any other tool

They are here🎉 The RubyConf 2026 talk recordings are officially live. Every keynote, every session, every moment you wished you could have been in two rooms at once. buff.ly/ui5I84d Which one are you watching first?

🔍 An AI agent trying to ignore a Ruby warning led to an unexpected discovery. How a little curiosity uncovered a problem with the AWS SDK and reduced memory usage by 60%. #Ruby mostlyobvio.us/2026/07/curio…

Sanest take yet.

AWS flat-rate networking future: "We know customers do not like rate-based network charges because it’s hard to predict their cost, which is why we are moving towards flat-rate pricing for new network products." theregister.com/networks/202…

💎 Balkan Ruby 2026’s talks are now online, with sessions on everything from Rails Engines and multiprocessing to SQLite, Fibers, and AI-powered Ruby apps. #Rails piped.video/playlist?list=PL…

An AI assistant with read-only SQL is a superhero. Until it fails privacy responsibilities and leaks sensitive data to everyone. We noted this possibility in an internal tool, moved the data boundary from prompt to Action Policy, and kept open-ended SQL: evilmartians.com/chronicles/…

Analyze your sending to make sure you are compliant with Google, Yahoo, and Outlook. Send a test email from your marketing, transactional, or personal emails and get a nice checklist to know where you stand — almost everyone finds an issue! Free tool: canisendthis.com

Most developers know that avg latency is misleading and they should use percentiles instead. They also know that if 90tile response time is 200ms, then 10% of the requests had response times higher than 200ms. Well, the last sentence is false. Or rather, true in theory. The only way to calculate true percentiles is by sorting and scanning all the data. Since this often means many millions of datapoints, we actually don't do that. We approximate. With histograms. How does that work? You create buckets of values: 0 to 0.05, 0.05 to 0.25, 0.25 to 1, 1 to 5, 5 to infinity. Then you accumulate: number of data points, sum of values and the number of data points that fall in each bucket. Now, if I ask you for the 90tile value, you start going over the buckets from lowest to highest latencies, and add the number of points in each bucket. Once you go past 90% of the data points, you know that your 90tile value is in this bucket. Then you give either the middle of the bucket or the upper bound as the estimate. Note that you don't know what % of the data is higher than the estimate. And also note that the quality of the estimate really depends on how the data ends up distributing between the buckets. It isn't uncommon for ntiles 90, 95 and 99 to all fall in the same bucket (if your distribution is "heavy tail"). And sometimes all or most of the data falls in one bucket and you can tell nothing. I recently had a case where we noticed the 99tile of response time for a specific request type was 10s. This was both high and suspicious - we have a 10s timeout in some places. But we couldn't find any request that hit these timeouts in our logs. Super weird! Until a smarter colleague realized (by looking at sample traces) that 10s was just the lower bound of the top bucket. The requests actually timed out at 60s. This allowed me to find the timeout they actually hit and fix the issue. So the lesson is: Averages are misleading. But percentiles are usually approximate and can be misleading too! Be careful not to trust the data blindly. #StatisticsSaturday

Damn it feels good to finally merge this one @rosapolis! Opened long ago, in a forgotten time of hand-coding in 2024. Thanks for unintentionally putting me on blast @jeremysmithco and kicking me into gear on finishing it out a year ago 😆 github.com/rails/solid_queue…

More and more code is written by AI. How do you know it follows your architecture? Today I released ArchSpec 1.0: executable architecture specifications for Ruby and Rails. It checked Discourse's 1,899 files in 2.5 seconds! Static analysis, no AI. paolino.me/archspec/ archspecrb.dev/

Application level WAL stored in postgres and served jointly by turbopuffer and postgres 🤯

A masterclass in both solving a hard problem and explaining it clearly!

This Independence Day 🇮🇳, I asked, "What will the next century of young Indians look like?" $0.01 Drone Deliveries. UAVs that never land. Groceries in under 10 minutes. Meet The 22nd Century Indian. A Documentary on a New India.