It was a great long weekend, and I had a fun time with my family yesterday. During some downtime, I got to play with this new breed of text-to-app AI tools and shared some quick perspectives here. In today’s reading list, I have a lot of unintentionally related content!
[article] Make Better Strategic Decisions Around Slow-Developing Technology. Interesting insight. Seems important to identify which are actually slow-developing. I like the point around thinking about innovation via more than one technology.
[blog] 4 Lessons We Learned from Bringing AI to Our Company. Speaking of innovation, be very thoughtful in how you introduce and roll out AI tech.
[article] Deloitte: 74% of enterprises have already met or exceeded gen AI initiatives (but challenges remain). I find this surprising. But there’s some interesting results here. Software development is where ROI is captured today, but lots of ambition for more.
[blog] GKE delivers breakthrough Horizontal Pod Autoscaler performance. Scale faster, save money. And give more consistent performance to y our customers. These are great improvements to Kubernetes.
[article] Introduction to Go Programming Language. This is a good introduction to the language. Adopting another programming language is a big deal, so pieces like this can help you decide if it’s worth it.
[youtube-video] Build with Go in Project IDX. Speaking of Go, here’s one way to invest in it without installing a single piece of software on your local machine.
[article] Notes on Nix. And speaking of Project IDX, Forrest has a great introductory post on a key underlying technology, Nix. This provides a straightforward way to define consistent dev environments.
[blog] Cloud CISO Perspectives: Talk cyber in business terms to win allies. In my experience, smart tech folks who talk like smart tech folks don’t get the buy-in from the rest of the company. It doesn’t mean you have to “dumb it down.” It means you pick a more relevant vocabulary.
[blog] Apache Airflow Overview. I know Airflow, but haven’t actually used it. This piece offers a helpful introduction to this orchestration tool used by data folks.
[blog] Deployment of Serverless Machine Learning models with GPUs using Google Cloud: Cloud Run. I’m enjoying the increase in folks who are using Cloud Run to experiment with open LLMs.
[blog] Building Effective Agents with Spring AI (Part 1). Here’s a great set of examples of how to implement specific agentic patterns with the Spring AI library.
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