JimCarroll

The 26 Principles, Revisited — #14: Hype Immunity — What I Said, and What’s Actually Happening

October 9, 2026 by JimCarroll

Part of my “26 Principles, Revisited” series — checking my own math, nine months into the year I predicted.

Leadership today isn’t about what you chase. It’s about what you ignore.

Day 14 argued that the discipline of leadership in an accelerating world is knowing which shiny new thing to deliberately ignore — chasing every trend is as dangerous as chasing none of them.

This is close to a direct hit on where AI sits right now. Analysts widely describe generative AI as sitting in the “Trough of Disillusionment” through 2026 — the phase where early hype gives way to a harder reckoning with real ROI. The leaders who come out ahead this year aren’t the ones who chased every AI headline. They’re the ones who filtered hard and committed to fewer, better bets.

Verdict: Nailed it — the Trough of Disillusionment is Hype Immunity’s whole argument, with a Gartner chart attached.

Next up: Principle #15, Escape Velocity — revisited.

How Innovation Happens — Lesson #7: Invest in Experiential Capital

October 9, 2026 by JimCarroll

I’ve been covering the link between future trends and innovation strategies for 30+ years. I went back through my blog posts, stretching to 2002, to dig out the nuggets of innovation insight I’ve discovered along the way. This series revisits those stories, tests what still holds up, and turns them into practical lessons for what comes next.

“Do things that have a vague objective, unknown potential for success and an absolutely uncertain payback, simply to boost your experiential capital.”

I’ve come back to this idea repeatedly in my work because the mindset behind innovation usually changes before the results do. What people notice, question, challenge, and act on determines how ready they are for what comes next.

Most organizations understand financial capital. Far fewer understand experiential capital: the stockpile of knowledge you build by doing things you have never done before.

The future rarely arrives with a clean business case attached. New technologies, new business models and new customer behaviours usually begin in a fog. If you insist on certainty before you experiment, you guarantee that someone else gets the learning first. Small projects with uncertain returns can be extraordinarily valuable because they build the skills, intuition and scar tissue you will need when the trend suddenly becomes real.

Experiential capital compounds. Each experiment gives you a little more confidence about what to do next, and just as importantly, what not to do.

So what does that mean in practice? It means challenging the assumption, habit, or hesitation that is keeping you anchored to the present. Here are three places to start.

Action Items:

Set aside a small budget specifically for experiments with uncertain payback.
Measure what a project taught you, not only what it earned.
Ask where competitors are accumulating experience faster than you are.

Explore the full How Innovation Happens series.

Real-World Examples

These researched examples show the lesson at work in the real world.

Atlassian ShipIt: A 24-hour experiment becomes a product pipeline

In 2005, Atlassian began giving employees a concentrated period to work on projects beyond their daily assignments. The program eventually became known as ShipIt. Teams could use the time to solve a persistent annoyance, explore a speculative idea, or build something useful enough to demonstrate to colleagues.

The attraction was not just the chance to produce a clever prototype. It was the experience of forming a team, making a decision, building under a deadline, exposing unfinished work to feedback and learning what happened.

Two decades later, Atlassian described ShipIt as a continuing company-wide practice with more than 2,000 participants at a recent event. Its retrospective identified Jira Service Management as a product that originated in ShipIt, with co-founder Scott Farquhar involved in the early project.

Not every entry became a marketable product; treating the number of launched products as the sole measure would miss the point. The program accumulated a form of organizational capability that cannot be purchased through a conventional lecture on innovation. Employees repeatedly practiced shipping something uncertain while the cost of failure was bounded.

Why it matters: Experiential capital is built by the repeated act of trying, testing, explaining and learning, not by attending another presentation about the importance of ideas.

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The Sand Motor: The Netherlands lets a coastline experiment teach it

Most coastal protection work follows an engineering logic: move sand or build a defence where protection is needed, then repeat maintenance as conditions change. Dutch engineers asked whether they could instead place a very large volume of sand at one point and allow wind, waves and currents to distribute it gradually.

In 2011, the Netherlands built the Sand Motor near Kijkduin using approximately 21.5 million cubic metres of sand. The peninsula was deliberately experimental. Government agencies and researchers monitored currents, dune formation, recreation, ecology and swimmer safety over years, learning which expectations were right and which effects needed management.

A ten-year review by Deltares concluded that the coastline had widened, dunes had grown, and the project had produced useful evidence for future coastal management. This was experiential capital on a national scale. Designers did not learn only from a model or an expert committee.

They created a bounded real-world intervention and allowed nature to produce data that no conference-room simulation could completely replace. The experiment was also not frictionless: it required ongoing observation and careful management of environmental and safety trade-offs.

Why it matters: Sometimes the best way to know whether a future system can work is to build a carefully limited version and let reality answer back.

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From the Stage: Remember the Maytag Repairman?

October 8, 2026 by JimCarroll

From the stage

Remember the old TV ads about the loneliest man in the world? The Maytag repairman never had anything to do because Maytags never broke. On stage I used him to explain what connectivity does to a business:

“They understand that they are no longer an appliance company.”

When our own washer broke, the repairman showed up with a laptop instead of a toolbox. “It was already a computer.” Then I pushed it further, to the day the doorbell rings unannounced:

“well I didn’t call you. Well no you didn’t but your washer did.”

It’s the same shift I’d seen with truck makers. Once you can predict a breakdown, you’re not selling the truck anymore:

“We’re selling a service level uptime guarantee.”

Why it matters

Once a product can report its own health, the business model quietly changes from the thing you sell to the outcome you guarantee. Appliance makers now offer technicians diagnostics that show which part has failed before they arrive. GE Appliances’ SmartHQ Service is one example. Any company whose product is getting smarter should ask the same question Maytag had to: what are we really selling now?

The takeaway

If your product can talk, you’re in the service business, whether you planned to be or not.
Uptime and outcomes, not hardware, are what customers will pay a premium for.
What’s your “your washer did” moment?

Source for the SmartHQ example: https://www.smarthqpro.com/blogs/service-technicians-reduce-downtime-boost-first-time-fix-customer-satisfaction

From the Stage is a weekday series of short clips from more than 30 years of keynotes, and the leadership lessons that still matter.

The 26 Principles, Revisited — #13: Wisdom Inversion — What I Said, and What’s Actually Happening

October 8, 2026 by JimCarroll

Part of my “26 Principles, Revisited” series — checking my own math, nine months into the year I predicted.

Know when to get your age out of the way.

Day 13’s idea: seniority and tenure, once automatic sources of authority, can become a liability when the newest, least-experienced person in the room has the clearest read on a fast-moving tool or trend.

Nothing has reversed that dynamic this year — if anything, the people most fluent in agentic AI workflows and prompt-native thinking in 2026 skew younger and less credentialed, not more. The organizations getting real value out of AI are disproportionately the ones willing to let that expertise lead, regardless of who holds the title.

Verdict: Held up — the inversion is still running the right direction.

Next up: Principle #14, Hype Immunity — revisited.

How Innovation Happens — Lesson #6: Think Big, Start Small, Scale Fast

October 8, 2026 by JimCarroll

“Think big, start small, scale fast.”

This has been one of my core innovation mantras for years because it solves three problems at once. Thinking big forces you to look beyond today’s operating issues and understand the five- or ten-year transformations that could reshape your market. Starting small lets you build experience without betting the company. Scaling fast prevents successful experiments from getting stranded in pilot mode.

I once used banking as a simple example. Mobile, text-based and location-sensitive banking were clearly going to matter. The right response was not to build the final system in one giant leap. It was to identify the long-term customer shift, run small experiments that built capability, learn what worked, and then scale the successful pieces quickly.

Innovation is not choosing between boldness and caution. It is sequencing them properly.

So what does that mean in practice? It means challenging the assumption, habit, or hesitation that is keeping you anchored to the present. Here are three places to start.

Action Items:

Write down one five-year transformation that could fundamentally alter your business.
Launch one small experiment specifically designed to teach you something about it.
Define the evidence that will trigger scale before the experiment begins.

Explore the full How Innovation Happens series.

Real-World Examples

These researched examples show the lesson at work in the real world.

Kessel Run: A $1 million software bet on a military whiteboard

At the US Air Force’s combined air operations centre in Qatar, planners once coordinated aircraft refuelling with magnets, markers, spreadsheets and a large whiteboard. Improving the entire military command-and-control system was a daunting, slow-moving acquisition challenge. A small team chose a narrower starting point: digitize the tanker-planning problem that airmen confronted every day.

With early funding reported at around $1 million, the project developed Jigsaw by working alongside the actual planners and putting usable software in their hands within months. Air & Space Forces Magazine reported that a process requiring six people for about eight hours could be reduced to around three hours.

The tool saved fuel and planning effort and helped demonstrate the viability of the Air Force’s Kessel Run software approach. An official Air Force acquisition report later described fuel savings far beyond the initial software cost, and NATO subsequently adopted the application.

The ambition was substantial: change the way critical military software is produced. The starting point was remarkably specific: one whiteboard, one painful workflow, one tool. The scaling happened because the limited experiment produced real evidence that a different delivery model could work.

Why it matters: A large transformation becomes believable when a small, well-chosen experiment removes a concrete problem people face every day.

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India UPI: A small payment interface that became national infrastructure

India did not need another isolated payment application. It needed a way for existing banks, new consumer apps and merchants to move money across institutional boundaries. In April 2016, the National Payments Corporation of India piloted the Unified Payments Interface with 21 participating banks.

The interface allowed payment requests and transfers to work through a common infrastructure, rather than relying on every company to build its own incompatible network. A public launch followed later in 2016, with more consumer-facing applications arriving as the system developed.

The national ambition was large, but implementation came through a bounded platform, bank integrations and successive additions. By the 2025–26 financial year, Indian government figures reported more than 240 billion UPI transactions, although official historical summaries differ slightly about initial transaction counts. The numbers are extraordinary, but the transferable lesson is architectural.

India made it possible for thousands of businesses and services to scale on top of a common standard without waiting for every future use case to be specified in 2016. The infrastructure started as a practical, technically constrained arrangement and grew through participation, standards and trust.

Why it matters: The most scalable ideas often begin with a narrow capability that makes many other people’s experiments possible.

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