Looking to discuss cybersecurity or AI with an expert? I've blocked off a few slots per month where I'm doing 30 minutes for $30. Bring your topic or issue and we'll dive right in, if there's a bit to read beforehand, send and I'll make an effort to go through things. Need an NDA? There's one in the scheduling process, it's optional. You can click on my profile, and then follow the Calendly link (circled in red on the profile photo in this post).

With neatly 5,000 followers this post gets 72 views, bad content or bad algorithm?

I took 1.7 million photos over 6 days to catch this photo of a commercial jet in front of the sun. The moment it happened, TWO floating prominences were visible, making this not just my best aircraft transit photo, but one of the luckiest of my career! Videos of the transit 👇

1: Are you building rich content sites with perfect performance scores? 2: I can't, I'm using an AI coding tool. 1: You're using the AI tool or it is using you?

I just read a PM's post about automating their workflows with AI, so let me share some takes: 1. You can automate documentation all you want. You'll still spend 3 hours a week explaining it to people who won't read it anyway. 2. The biggest time sink in product management isn't creating artifacts. It's convincing others your idea was actually their idea all along. 3. I've seen PMs automate their entire PRD process. They still spend 80% of their time in meetings where nobody references the PRD. 4. AI can write your user stories in seconds. Getting alignment on those stories will still take 4 meetings, 12 Slack threads, and one awkward hallway conversation. 5. Most PMs spend more time writing angry Slack messages and then deleting them than they spend on actual product strategy. This is the emotional labor nobody talks about. 6. Every PM job description mentions "data-driven decision making." In reality, you spend most of your time cleaning up decisions your predecessor made based on vibes and executive opinions. 7. The irony of AI automation tools for PMs: They optimize the 20% of your job that's already efficient. The other 80% - managing up, sideways, and down - remains stubbornly human. 8. You know what takes the most time? Re-explaining the same strategy to different stakeholders who all think they're hearing it for the first time. 9. I automated my entire data analysis workflow last year. Now I spend that saved time defending the data to people who don't like what it says. 10. The best PMs I know aren't great at creating artifacts. They're great at navigating organizational dysfunction without losing their minds. 11. Here's the pattern I see: Junior PMs obsess over perfecting their templates. Senior PMs obsess over reducing the number of meetings where those templates get ignored. 12. You want to know where PMs really spend time? Writing diplomatic versions of "this is a terrible idea" in 15 different ways until one lands. 13. AI can generate a roadmap in minutes. Getting everyone to stop trying to add their pet feature to it is a quarterly battle. 14. The cruel joke: By the time you've automated your PM workflows, you'll probably be promoted to a role where none of those automations matter anymore. 15. If AI could automate stakeholder alignment, that would be the real revolution. Instead, we're automating the creation of documents that prove alignment never existed. Product management is 20% building products and 80% managing the humans who make building products complicated.

So many decisions in April that made the product worse with no version pinning or ability to avoid the regression releases. Bye @claudeai, if you ever return to your March 2026 self maybe we can be together again.

That's a team! #GoSpursGo

Had an interview with a “crypto” recruiter. We talked for about 40 minutes, and then they asked me to look at some code. Their first instruction was to clone the repo. I didn’t. They seemed surprised, so I told them I wanted a moment to check whether it was safe first. I ran a quick analysis with Claude. Turns out the code had a backdoor. It would copy my environment variables and send them to a remote server. The recruiter went speechless and ended the call pretty quickly. Be careful who you talk to. Scammers are real.

Sundar Pichai announced at Google Cloud Next 2026 that 75% of all new code created inside Google is now generated by AI and reviewed by human engineers. That is up from 50% last fall. However, I also want to point out to the back and forth between @Steve_Yegge and @Google on the AI usage inside Google. At this point, take the Google numbers with a pinch of salt as there is no way to verify if it is marketing or true numbers. Assuming it is true, I am continuing this analysis. Google is using Gemini models and internal agents for code generation. The company said agent-assisted workflows completed a complex code migration six times faster than a year ago. Google is now factoring AI adoption goals into some engineers' performance reviews and allowing select teams to use third-party tools including Claude Code. The 50% to 75% jump in six months is the number to focus on. If AI-generated code at Google is growing at that rate, the trajectory points toward 90% within the next year. But "generated" and "written" are different things. Human engineers still review and ship the code. The question is whether review becomes a bottleneck. If one engineer can review AI-generated code at 3x the pace of writing it, the math works. If review requires the same cognitive load as writing, the productivity gain is smaller than the headline suggests. Connect this to yesterday's GitHub Copilot story and today's SpaceX-Cursor deal. Google, Microsoft, and SpaceX/xAI are all racing to own the AI coding workflow. Google is doing it internally with Gemini. Microsoft is charging for it with Copilot. SpaceX is buying its way in with Cursor. The fact that Google allows some teams to use Claude Code is worth noting. It means even the company with the largest internal AI coding deployment does not think its own models are always the best tool. That is a signal about the state of AI coding models that no marketing claim can override.

The 2025-26 @Kia NBA Sixth Man of the Year is... Keldon Johnson!

Never seen something like this ever. This is incredible. Holy moly.

Another week on the road meeting with a couple dozen IT and AI leaders from large enterprises across banking, media, retail, healthcare, consulting, tech, and sports, to discuss agents in the enterprise. Some quick takeaways: * Clear that we’re moving from chat era of AI to agents that use tools, process data, and start to execute real work in the enterprise. Complementing this, enterprises are often evolving from “let a thousand flowers bloom” approach to adoption to targeted automation efforts applied to specific areas of work and workflow. * Change management still will remain one of the biggest topics for enterprises. Most workflows aren’t setup to just drop agents directly in, and enterprises will need a ton of help to drive these efforts (both internally and from partners). One company has a head of AI in every business unit that roles up to a central team, just to keep all the functions coordinated. * Tokenmaxxing! Most companies operate with very strict OpEx budgets get locked in for the year ahead, so they’re going through very real trade-off discussions right now on how to budget for tokens. One company recently had an idea for a “shark tank” style way of pitching for compute budget. Others are trying to figure out how to ration compute to the best use-cases internally through some hierarchy of needs (my words not theirs). * Fixing fragmented and legacy systems remain a huge priority right now. Most enterprises are dealing with decades of either on-prem systems or systems they moved to the cloud but that still haven’t been modernized in any meaningful way. This means agents can’t easily tap into these data sources in a unified way yet, so companies are focused on how they modernize these. * Most companies are *not* talking about replacing jobs due to agents. The major use-cases for agents are things that the company wasn’t able to do before or couldn’t prioritize. Software upgrades, automating back office processes that were constraining other workflows, processing large amounts of documents to get new business or client insights, and so on. More emphasis on ways to make money vs. cut costs. * Headless software dominated my conversations. Enterprises need to be able to ensure all of their software works across any set of agents they choose. They will kick out vendors that don’t make this technically or economically easy. * Clear sense that it can be hard to standardize on anything right now given how fast things are moving. Blessing and a curse of the innovation curve right now - no one wants to get stuck in a paradigm that locks them into the wrong architecture. One other result of this is that companies realize they’re in a multi-agent world, which means that interoperability becomes paramount across systems. * Unanimous sense that everyone is working more than ever before. AI is not causing anyone to do less work right now, and similar to Silicon Valley people feel their teams are the busiest they’ve ever been. One final meta observation not called out explicitly. It seems that despite Silicon Valley’s sense that AI has made hard things easy, the most powerful ways to use agents is more “technical” than prior eras of software. Skills, MCP, CLIs, etc. may be simple concepts for tech, but in the real world these are all esoteric concepts that will require technical people to help bring to life in the enterprise. This both means diffusion will take real work and time, but also everyone’s estimation of engineering jobs is totally off. Engineers may not be “writing” software, but they will certainly be the ones to setup and operate the systems that actually automate most work in the enterprise.

Terence Tao proposes what he calls a "Copernican view of intelligence". Instead of buying into the common, one-dimensional narrative that artificial intelligence will simply evolve from "subhuman" to "superhuman" and ultimately make humanity entirely redundant, Tao urges us to look at the bigger picture. Much like the Copernican revolution proved the Earth is not the center of the universe, Tao suggests we need to realize that human intelligence isn't the only, or necessarily the highest, form of intellect. Historically, we have treated other forms of storing or creating knowledge—like animals, books, and computers—as secondary. However, we actually exist within a much richer universe of intelligence. Both human intelligence and computer intelligence possess their own distinct strengths and weaknesses. The true potential lies not in viewing them as direct competitors, but rather in focusing on collaboration. By working together, humans and computers can achieve additional things that neither could accomplish on their own, requiring us to think in much wider terms than just what humans or computers can do alone.

Super annoying @AnthropicAI that you decide to use "-prefix" on a directory name in your file path so if I'm sitting in that directory and try to use Linux cd command without special regex escaping I get a syntax no such arg error.

The "AI job loss" narratives are all fake. AI = massive ramp in productivity = massive ramp in demand = massive jobs boom. Watch.

Day of the week: Sunday Time of the day: Afternoon Type of project: Fun side project Type of testing: [A picture is worth 1,000 words, and well in this case 985 more than written on it]

Hey @AnthropicAI, keep up this set of behavior changes and you'll need to rename it from Claude to Leeroy, specifically Leeroy Jenkins... youtube.com/watch?v=hooKVstz…

Hey I love dumping on my company as much as the next guy, because Microsoft does some dumb stuff, but sometimes it's just check emails and verify your accounts. Not every "WTF micro$oft" moment is a slam dunk. I've emailed VeraCrypt personally and we'll get him unblocked. I've already talked to Jason at WireGuard. Not everything is a conspiracy, sometimes it's literally paperwork.

Is it just me or are y'all getting commit messages from Claude Code today that are as long as this book? #EverythingIsBiggerInTexas including git commit messages?

Nothing says confidence to me louder than seeing "version: '0.18.0'" as the current version of a plugin I'm looking at using.... ...and it is just past 10am today!

Can we please call Base64 and XOR obfuscation and not encryption, especially in a popular blog post that likely becomes future training data? Sigh. I guess it is good for my gainful employment. buchodi.com/chatgpt-wont-let…