Thanks for following along through our six-part AI Cost Ripples series. In this article, we’re switching gears to something different. In my TPM career, I’ve attended countless post-mortem meetings and exercises. Each one has been a learning experience, almost like a living environment with constantly changing variables. Yet, within that dynamic setting, certain rules remain […]
Info Tech Incident Post-Mortem Theater Read More »
As we conclude our journey through ‘hidden cost ripples of AI’, we arrive at our final and perhaps most underestimated ripple of all: Engineering Complexity. In our previous episodes we explored visible infrastructure layers such as compute, data pipelines, vector systems, networking, and observability. Yet as organizations move from experimentation into large-scale operationalization, another challenge
Episode 6 Hidden AI Cost Ripple: Engineering Complexity Read More »
I hope you enjoyed our previous four episodes. As we continue our journey through these hidden cost ripples of AI, we now move into Episode Five. Fifth Ripple marks a critical shift from deploying AI systems to actively managing lifecycle in production. Early ripples focus on development and deployment, but this stage addresses hidden challenges
Hidden AI Cost Ripples – Observability & Model Evaluation – Episode 5 Read More »
If you’ve glanced at my About Me, you probably know, I have a soft spot for vintage automobiles. Old machines carry stories. And I’ve always had respect for the people who take their time to restore them, bringing them back from barns to the road, piece by piece. During a recent visit to Monterey, California,
Some Machines Carry Stories – This one does Read More »
Our description of first three cost ripples: compute infrastructure, data pipelines, and vector/retrieval systems, quietly built the foundation for modern AI hidden cost ripples. Each layer solved a critical constraint, enabling models to scale, learn, and respond with increasing sophistication. However, once those pieces are in place, a new constraint emerges: “how fast intelligence can
AI Cost Ripple: Networking & Data Movement – Episode 4 Read More »
Thoughts, observations, and reflections across evolving information technology landscapes. The ideas shared on this website come from personal experience, research, and observation across rapidly evolving information technology landscapes. They are not written to promote a fixed stance, pro or anti anything, but to explore how systems behave in practice, where they succeed, and where they
Tech Articles: My Perspective and Intent Read More »
Dusted off my DSLR camera last weekend Not everything that grows needs to be optimized. Spring runs on its own timeline, quiet, steady, and without urgency. Flowers don’t scale faster because we want them to; they bloom when conditions are right. Maybe balance isn’t about doing more, but about knowing when to step back and
Not Everything Needs to Be Optimized – A Spring Pause Read More »
In our previous two episodes, we explored some of less obvious but critical ripple effects of scaling AI systems. In Episode #1, we unpacked Hidden AI Cost Ripple #1: Compute Infrastructure Cost Explosion; how increasing model complexity and usage can rapidly drive-up compute demands, often faster than teams anticipate. In Episode #2, we dove into
Hidden AI Cost Ripple: Vector & Retrieval Infrastructure – Third Episode Read More »
While compute infrastructure forms a foundation of AI’s cost structure, it is only the first ripple. As organizations move from experimentation to production, a second, often larger wave emerges of data pipelines, where continuous movement and transformation of data introduce a new layer of complexity, scale, and hidden cost. If compute infrastructure is described as
Second AI Hidden Cost Ripple: Data Pipeline – Second Episode Read More »
Preface: After writing about Linux and seeing how people responded, I realized there’s a deeper shift worth unpacking. What started with Linux as a shift in infrastructure is now accelerating with AI and cloud, this time, these changes are less visible and more far-reaching. The biggest changes in AI aren’t loud, they’re subtle, and they’re
Hidden Ripple Effect of AI on Cloud Costs Nobody Talks About – First Episode Read More »
