You need to write SEO and enterprise research text for AIs now, in addition to humans. Does this mean separate pages, often hidden from humans like we see for search engine SEO? Probably.
A Gartner survey of 377 U.S. consumers, conducted in June and July 2025, revealed that rather than shortcutting decisions, AI features are lengthening the research journey. Thirty-one percent of consumers surveyed say AI summaries cause them to spend more time searching for information, compared to just 16% who spend less.
Where to stay in Amsterdam
For a fun, less touristy experience in Amsterdam, consider staying in the neighborhoods of De Pijp or Jordaan.
Enterprise ROI continues to be elusive
NICHOLAS LITTLE, from this IEEE article.Original ContentHere’s a summary of a new post on my weblog: Three years into the generative AI boom, enterprise ROI remains stubbornly hard to find. Survey after survey shows a familiar pattern: widespread experimentation, lots of “in production” claims, and very little impact on revenue, costs, or P&L. The usual explanation is “culture,” but that’s a dead end for IT - culture change belongs to executives, and most employees don’t believe leadership has a real plan anyway.
This week’s Software Defined Talk: This week, we discuss the end of Cloud 1.0, AI agents fixing old apps, and Chainguard vs. Docker images. Plus, the mystery of Dutch broth is finally solved.
I recommend the traditional podcast format.
This week’s Software Defined Interviews: we talk with Nathen Harvey, who leads the DORA research program at Google Cloud. They talk about what 15 years of DevOps and delivery data actually says about AI. The answer feels something like “it makes you even better at what you’re already good at.” High-performing teams get better, while struggling teams just move faster into bottlenecks. The talk about AI-assisted software development, why throughput is rising while stability drops, how culture still beats tools, and why “user-centric” work remains stubbornly hard despite being obvious.
There’s also the traditional podcast version.
This week’s Tanzu Catsup: AI tools have solved code generation, probably. But they’ve created a new constraint: Day 2 operations. When the volume of applications jumps 10x driven by a flood of “small” line-of-business apps manual “run teams” and traditional onboarding processes break down.
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Another go at LowCode
Another go at LowCode:
It is a new era of app creation that is sometimes called micro apps, personal apps, or fleeting apps because they are intended to be used only by the creator (or the creator plus a select few other people) and only for as long as the creator wants to keep the app. They are not intended for wide distribution or sale.
🔗 The rise of ‘micro’ apps: non-developers are writing apps instead of buying them
For a long time I foolishly scorned George Orwell. I think the prejudice is common among people of my generation (well among people of my generation who care about such things). Orwell is viewed as a fetish of boomer columnists – the types of people who sit in their houses in Hampstead being paid six figures by broadsheet newspapers not really trying with their prose and fondly imagining they are working in plain Orwellian sentences and fearlessly speaking truth to power."
The US needs, even wants China. From the revealed preferences files:
Aside from rhetorical commitments to restoring domestic industrial capacity and a variety of China Select Committee investigations that tend to go ignored, there’s near-weekly evidence that Congress and the current administration are not entirely serious about leading a whole of nation effort to eliminate regulatory bottlenecks to power abundance, bring pharmaceutical production onshore, mine and refine rare earths, and reduce the leverage that China has over the U.S. economy in about a dozen different areas. Absent solutions on any of those fronts, some of which will take years, Trump couldn’t even ban TikTok. Then, just before Christmas, the U.S. greenlit the sale of high-end Nvidia chips that could help Chinese companies narrow the gap with U.S. competitors in AI. If successfully navigating a prolonged competition with China requires not only acknowledging said competition but actually making the sacrifices necessary to win it, one could be forgiven for reading the news over the past 10 years and concluding that America simply doesn’t have the mettle to prioritize long term national interests over short term private interests (or political incentives)."
Also, pondering a sort of “chilly war” between the US and China.
From Notes from Schrödinger’s Cold War, Andrew Sharp.
SaaS businesses not looking good now:
Traditional estimates for this scope of work: Method Estimate COCOMO (lines-based) ~20,000 hours Feature decomposition ~9,000-12,000 hours Industry benchmark 5-6 years solo, 12-15 months with 5 junior engineers Traditional cost $750,000 – $1,500,000
What I spent: $1,800. That’s a 99.8% cost reduction. It’s also not a fair comparison—traditional development wouldn’t produce identical output. But the delta is large enough that precision doesn’t matter.
🔗 On Running a Startup of Claude Code Agents: What You Get For a Billion Tokens a Month