AI's Distributed Future

I've been an expert in and advocate of distributed systems for decades. I was lucky enough to find my way into the automotive world at GM where multiple computers cooperatte to make a car operational. From there, luck struck again as I stumbled into Grid Computing at IBM where I learned about enterprise distribution and the inherent challenges and the promises of moving compute and storage as close as possible to where data and decisions live. One of my greatest successes was getting Duke Energy to reverse course and push simple computations they had planned to put on their mainframe, and overload it, down to the smart grid controller. I proved to Todd Arnold, then SVP Smart Grid, that only through distribution could they even come close to providing their customers with the service they designed. 

I've been considering writing this post for a week, fearful it was too far out there for people to grasp. Thankfully Aravind Srinivas, the CEO of Perplexity gets it. He stated last Saturday that on-device AI threatens the massive data center build-out strategy employed by just about everyone in the AI space today. Remember, this is a company backed by Nvidia, the ones making billions by filling those AI data centers with their product. 

Why is AI's future distributed? Cost.

Time is money, and automated systems need answers faster than humans starting at a screen. It takes time for input data to be shipped out, a decision to be made, and for that decision to trek back. Data has a unidirectional trend: growth! The amount of data we generate and consume grows every year, and it's not just cat videos. All those billions and billions of Interent connected devices, the sensors and controllers being distributed everywhere to control everything, are generating data that AI will need to consume. There's too much data to move quickly enough to meet the millisecond needs of next generation systems.

Beyond speed, compared to the cost of moving data, everything else is free. There's a reason cloud hyperscalers charge nothing for data ingress but gleefully bill for data egress. 

As we see announcements of hundreds of billions of dollars being dumped into AI data centers, generating fear of a bubble, it breaks my core belief that success comes from leveraging other people's assets. That phone in your pocket is capable of MUCH more than you use it for beyond cat videos. As a thought experiment, I was challenged by the CTO of Wells Fargo a decade ago to come up with a solution to providing 100% uptime. It was a test. Would I BS him, or admit there is no such thing. What he didn't expect was me handing him a workable solution within 30 minutes: store an emergency copy of financial transaction data on each person's phone in the secure sandbox your app creates. Yes, it would work, and he knew it. We are surrounded by smart devices that are I/O bound, meaning they spend most of their life doing NOTHING! That's what Aravind gets.

Here's a wrinkle though. What if the price of RAM goes up so high that companies pull back on IoT deployments? What if they have to scale down the available headspace of their devices to keep the costs down? What if laptops and desktops surged in price by 50% or 100% because we're competing with IBM and Google for silicon? Perhaps that's why, despite the obvious business value of narrowing down to the AI market, Nvidia has maintained availability of it's products for consumers, unlike Crucial who is withdrawing to focus their silicon capacity on commercial products exclusively.

How it plays out will be interesting, but just as I advocated for what we now call Edge Computing over a decade ago, I'll advocate for pushing AI workloads out to the endpoints, onto devices that are ready now in ways people don't understand.

What Is Customer Success?

Customer Success (CS) represents the start of a revolution, not just an evolution. For decades, the post-sales support function has been owned by sales teams, heavily incented to view prior sales as a burden to be offloaded. Consistent delivery is tough, and as these weak structures ran into challenges, customer frustration would eventually overflow the vendor bond, leading to a disruptive and ultimately avoidalbe split. Today, Customer Success destroys the self-centereed approach in favor of a business outcomes focus, one in which strategic discipline focused on what the customer needs to achive drives retention, revenue growth, and long-term company valuation. 

At its core, Customer Success ensures that customers achieve their desired outcomes while using a company’s product or service, creating mutual, measurable value over time. It's a proactive, outcomes-focused approach to managing customer relationships. Unlike reactive support models that address issues after they arise, Customer Success anticipates customer needs, guides adoption, mitigates risk, and aligns product value to the customer’s business goals.

In practice, Customer Success sits at the intersection of product, sales, support, and strategy. Its mandate is simple but powerful: when customers win, the business wins. Successful organizations reduce churn, expand accounts, accelerate time-to-value, and turn customers into advocates.

Key outcomes of effective Customer Success include:

• Higher retention and renewal rates

• Increased expansion and lifetime value

• Stronger customer advocacy and referrals

• Deeper insight into product-market fit

The Most Important Attributes for Customer Success

While tools, playbooks, and data are essential, Customer Success ultimately succeeds or fails based on people, mindset, and execution. The following attributes are foundational.

1. Leadership with a Customer Outcome Obsession

Great Customer Success leaders focus relentlessly on customer outcomes, not features, not usage metrics in isolation, and not internal assumptions. They deeply understand what success looks like for each customer and continually align engagement, onboarding, and value realization to those goals. These leaders have made a fundamental shift, from telling to asking. Asking better questions, listening actively, and validating the defintion of success in the customer’s terms provide the structure for leaders to marhsal resources into teams, build the required programs, and shift the focus from "what can we sell" to "how can we help".

2. Strategic and Business Acumen

Modern Customer Success professionals must understand their customers’ industries, business models, and economic drivers. This allows them to move from tactical support to strategic partnership—connecting product capabilities to measurable business impact such as revenue growth, cost reduction, risk mitigation, or efficiency gains. Without business acumen, CS risks becoming order-taking rather than value creation.

3. Proactive Engagement and Risk Management

The most successful CS organizations identify risk before it becomes churn. This means using data, health signals, and qualitative insight to anticipate issues related to adoption, stakeholder alignment, or changing priorities and acting early. Even better, bringing ideas and innovations to the table, taking the risk of missing the mark to demonstrate an interest in the customer's future; proactively builiding trust and positioning CS as a guide, not a firefighter.

4. Strong Communication and Influence

Customer Success requires influencing without authority—internally and externally. CS professionals must communicate clearly with executives, align cross-functional teams, and translate customer needs into actionable insights for product, sales, and marketing. The ability to tell a compelling story, value driven and tailored to different audiences, is a critical differentiator.

5. Data Literacy and Operational Rigor

Successful Customer Success teams balance empathy with analytics. They understand how to interpret usage data, health scores, and lifecycle metrics while also applying structured processes and playbooks to scale effectively. Operational rigor ensures consistency, predictability, and the ability to grow without lessening quality.

6. Adaptability and Continuous Learning

Customer needs evolve, markets shift, and products change. High-performing CS teams embrace change, iterate quickly, and continuously refine their approach based on feedback and results. Adaptability is especially critical in fast-growing SaaS and technology-driven organizations where yesterday’s best practices may not apply tomorrow.

7. Cross-Functional Collaboration

Customer Success does not operate in isolation. The strongest CS organizations partner closely with sales, product, engineering, marketing, and support to deliver a seamless customer experience. This collaboration ensures that customer insights inform roadmap decisions, go-to-market strategies, and innovation priorities.

The Bottom Line

Customer Success is a team today, but it's influence on the company, building a philosophy anchored in long-term value creation, nests in the organization's DNA. Companies that invest in the right people and attributes, align CS to business outcomes, and empower teams with both empathy and rigor are best positioned to build durable customer relationships and sustainable growth.

In an increasingly competitive and subscription-driven world, Customer Success is no longer optional—it is a strategic imperative.