See the traditional podcast version for more and Heidi links.
Why it's great to be a Spring developer now, and how to make it even better - State of Spring, 2026
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.
Best review of The Sound and The Fury, in Mad Men, s2e11: “Sex is good. This book is just OK.”
Management is always eager to "reduce costs."
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.
Say you love business logic without saying "business logic."
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.
AI still not good at basic knowledge worker workflows, which is likely an apps problem
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.
Where are the enterprise AI apps? Part n + 1
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.
Attention, Autonomy, and AI in the Critical Path - Related to your interests - February 17th, 2026
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.
Your Boss Doesn’t Know What to Do With AI
Enterprise AI Has a Product-Market Fit Problem. Enterprise AI isn’t stalled because the models are weak. It’s stalled because we haven’t discovered product-market fit inside the enterprise yet.
You don’t find real AI value by theorizing in workshops. You find it by running experiments for months inside your actual systems - against real data - in a governed environment.
That requires a platform.
Without one, AI pilots turn into disconnected experiments, shadow infrastructure, and compliance risk. With one, experimentation compounds into institutional learning.
In this video, I break down:
- Why enterprise AI is still in discovery mode
- Why experimentation must be long-running, not one-off
- How governance enables innovation instead of blocking it
- Why a secure platform foundation is the baseline for AI ROI
If you’re thinking about AI strategy, platform engineering, or how to make AI experimentation safe and scalable, this is where to start.
Featured:
There's a lot of business logic in Java, decades worth...
We have invested a lot in domain models, some of which are even very good. And, to be able to leverage that as we move to the new world is really, really important." Rod Johnson.
Source: “GenAI Grows Up: Building Production-Ready Agents on the JVM," Rod Johnson, GOTO, October 1st, 2025.
That reminds me of this gem: