Coté

Enterprise AI apps (or lack thereof), ROI surveys, CFO budget pivots, agile’s stubborn relevance, platform engineering vs. private cloud, Heroku’s freeze, IRS tech cuts, and Europe hedging on AI tools Peter Klúcik's The Hobbit illustrations. Related to your interests Where are the enterprise AI apps? Part n + 1 - AI capacity demand is high, but it’s still “early innings” for enterprise AI use.

This week, we discuss personal AI hype cycles, bottoms-up adoption, and “The Modern Stack” simplifying cloud. Plus, thoughts on new cars and the dogs that ride in them. See the traditional podcast listing for links and more.

See the traditional podcast version for more and Heidi links.

This is a talk I give at the start of Spring workshops we do. Here is the recording. The point is to show people that being a Java and Spring developers is fantastic right now. Here’s the description: Spring developers are in a strange position in 2026: everything is changing: AI, platform engineering, enterprise architecture. And yet Spring keeps getting stronger. In this talk, Coté walks through why this is actually a great moment to be a Spring developer, especially in large organizations.

The real story lies “in collapsing headcount growth expectations, from 6% in 2025 to just 2% in 2026 with just 21% of CFOs planning staff increases of 4% to 9%, down from 31% last year,” Nauman Abbasi, vice president analyst in Gartner’s finance practice, said in the release. “This marks a structural pivot from labor expansion to optimization driven by automation and AI that deliver productivity gains without proportional increases in headcount.

Model Eats the Software: Why the Marginal Cost of Enterprise Software Approaches Zero More on agentic AI changing the software business from Jason Hoffman: Andreessen specifically predicted that Salesforce would disrupt Oracle. Fourteen years later, Oracle is roughly 2.5x the size of Salesforce. Salesforce sells application logic – workflows, configurations, business rules. Oracle sells infrastructure – databases, middleware, cloud compute. The application layer was always the vulnerable part. The infrastructure layer was always the durable part.

Here is one account of AI being shit at multi-step activate outside of coding: I think my request of “Hey Gemini, show me a list of all the articles I wrote over the last year and arrange them into categories by subject” is a straightforward one, and I came away from this experience surprised that Gemini shipped these features as bleeding edge AI to customers when it never really delivered for me.

Outside of programming, there’s still a dearth of enterprise AI apps, it seems. Palo Alto’s CEO: “Consumers are far outstripping enterprise for the moment, but we expect enterprise will surely and slowly get on that bandwagon,” he said on the company’s Q2 earnings call. … “Right now … tell me how many enterprise AI apps are you using which are driving tremendous amounts of throughput,” he asked, and answered himself “I can’t think of anything but coding apps.

From “CEO said a thing” journalism and sovereign payments to product teams in code-gen land, Deming vs. OKRs, sex recessions, Neanderthals, fonts, and hype cycles - a tour through power, productivity, and what actually holds systems together.