I promise, I’m a very serious person.

All job search advice you’re getting today is wrong. The only effective strategy for your next job is to leverage nepotism.

This one is for @LinkedInLunat1c

I have always known that it’s the meetings that make a team faster. 👌

I host figure drawing in NYC every Monday and got this an hour before tonight’s session. I understand not everybody cares about my family who were refugees in Israel 🇮🇱, but this is very unprofessional. Thankfully someone stepped in on short notice - come draw with us! IG: artdblockdotorg.

Btw, does anyone know whether @PeoplesForumNYC want a used copy of “Atlas Shrugged” by Ayn Rand for its socialist literature collection?

“When 100% of code is generated by AI, can we lay off 13% of engineers?” - NY CTO Club discussion on DORA metrics today.

I used Copilot on my Copious Free Time™ to open 89 PRs (75 got merged) last month into a project at work. Coding with AI agents is now a baselines expectation for managers. code.dblock.org/2026/05/05/c…

Me and @Copilot working on some weekend coding for slack-gamebot. gamebot2.playplay.io

I remain @github user 542,335.

The new gig economy.

I made $360 in @monarch_money referrals by serving markdown to A.I. agents from my Jekyll blog. code.dblock.org/2026/04/11/h…

Before AI coding assistants, a typical engineering team built expertise with the years. Now, exploring a codebase takes a day. So, at work, I asked my team to actively seek contributions from our internal customers with an active engagement for our proprietary code. code.dblock.org/2026/04/08/o…

Finally got to adding AGENTS.md to a few projects. github.com/ruby-grape/grape/…

The lesson is that Claude Code should have been open-source in the first place.

Are you returning to office? @Copilot did some remote work for me while I was having coffee this morning. 🎮 slack-gamebot now supports 4 rating algorithms: adaptive tau-decay (default), standard Elo (K-factor), Glicko-1 (rating deviation), and Glicko-2 ( volatility). Switch per season, tune each algo's params. Serious rankings for your office games. Code is #opensource. gamebot2.playplay.io github.com/dblock/slack-game… Adaptive is the default and most forgiving for casual play - new players experience big rating swings that gradually stabilize as they accumulate matches, thanks to a per-player tau value that dampens volatility over time. Standard Elo is the classic textbook formula used in chess: a fixed K-factor scales every rating change equally regardless of experience, simple and predictable. Glicko-1 improves on standard Elo by tracking a rating deviation (RD) per player - a measure of how confident the system is in your rating. New or inactive players have high RD (big swings), frequent players have low RD (small, precise adjustments), which means beating a well-established strong opponent is worth more than beating someone the system barely knows. Glicko-2 goes further by also tracking per-player volatility (σ) - how erratically a player performs - so a consistent player and a streaky player at the same rating will experience different sized swings, with the streaky one remaining more sensitive to new results.

I wish I'd documented our explicit principles for building with AI when we started adopting it. Treating it as a simple tool rollout is a mistake. We need to be more strategic. I shared this with my team yesterday. It reflects my current beliefs, though some may be outdated in 4 weeks. Building with AI: blog.abuiles.com/blog/2026/0… TL;DR: 1. Start from intent, not code. 2. Better planning matters more when building gets cheap. (hat tip to @chintanturakhia on this and 1) 3. Optimize every PR for reviewer comprehension. 4. Small diffs are a quality strategy. 5. Faster builders make good reviewers more valuable. (hat tip to @dblockdotorg ) 6. The author still owns quality. 7. QA starts before the code is “done.” 8. AI should help us produce better code, not lower standards. (hat tip to @simonw) 9. Knowing what to ship matters more than just shipping. 10. Optimize the system, not just the individual. 11. Production is the only real test. 12. Do not outproduce your senior judgment. (@dblockdotorg ) 13. Leave the system better than you found it.

I wrote up the details in code.dblock.org/2026/03/12/a… I think it's a simple and practical example of how AI has almost introduced a hard to see catastrophic failure. For now, human oversight of A.I. assistants remains critical.

Great post by @dblockdotorg! A lot of people is buying into the idea that because you can then you should ship it all in one go. The increase in slop is real which is putting a huge cognitive overload on experienced judgment. “Teams are shipping more code, but a greater fraction of it is AI slop: plausible-looking, locally coherent, globally wrong.” I’ve seen this, big pull request end up introducing a lot of bugs or regressions that should have been easy to capture with a small/local change.

Blogged: Right-Sizing Engineering Teams for AI code.dblock.org/2026/03/11/r…