The Constant and the Current

Two clocks

Every few months the tools change. A new model arrives, a platform consolidates, a workflow that took a week now takes an afternoon, and a skill that felt like an edge last spring is a checkbox this fall. It is easy to feel behind, even when you are the expert in the room.

The work runs on a different clock. A brand still has to mean something to the person choosing it. A product still has to be found, trusted and bought, and a sales team still has to reach the right buyer before the quarter closes. Those objectives were true at the first market stall, and they will still be true when the next model ships.

We call these two clocks the constant and the current. The constant is the job: be known, be chosen, be bought, be remembered. The current is everything moving underneath it, the engines, the models, the channels and the costs. We hold the constant steady and put the strongest current available today behind it, knowing it will be stronger tomorrow.

Most of the anxiety we hear from clients comes from mixing the two clocks up. When the fast clock sets the strategy, every new release feels like a reason to start over, and teams spend their best hours evaluating tools while customers wait. When the slow clock sets the strategy, a new release becomes good news: one more way to do the job that was always there.

What holds steady

The constant is older than any channel we have worked in. A trader at a market stall had to be known for something, chosen over the stall next door, paid, and remembered the following week. A brand on a retail shelf faced the same tests, and so does a product named inside an AI answer today. The setting changed each time, and the job carried straight through.

Jeff Bezos made a version of this point at Amazon's re:Invent conference in 2012. He said people often asked him what would change over the next ten years, and he argued that the more useful question was what would stay the same, because a strategy built on stable customer needs keeps paying off for as long as those needs last. For a retailer, he said, customers would always want low prices, fast delivery and a wide selection.

Our version of that list is short. Be known for something specific. Be found and chosen by the right buyer. Earn trust and proof. Make the sale before the window closes. Keep the customer and grow loyalty. Every engagement we take on is anchored to one of those five objectives, and the plan we write on the first day names which one.

Marshall and Eric McLuhan offered another useful lens in Laws of Media (1988). They proposed that every new medium enhances something, makes something obsolete, retrieves something from an earlier time and, pushed far enough, flips into its opposite. AI answers are a clear case of retrieval. For most of history a buyer asked a trusted shopkeeper what to get, and the shopkeeper answered with one recommendation and a reason. Search engines turned that conversation into a page of links and an evening of homework, and answer engines are bringing the shopkeeper back.

That return is why we find this period exciting. Becoming the brand a trusted advisor recommends is a centuries-old objective, and earning that recommendation draws on everything strong brands have always done well: a clear position, real proof and a reputation that other people repeat.

What keeps moving

The current is everything underneath the job: the engines, the models, the channels, the formats and the cost of making things. It moves quickly, and it moves in every direction at once. Platforms open, consolidate and reverse. A tactic that worked in the spring can fade by the fall, and a capability that once took a production team and a month of work can arrive inside a tool for a monthly fee.

Stewart Brand gave us the clearest model we know for living with both speeds. In The Clock of the Long Now (1999), he described a healthy civilization as a stack of layers moving at different rates: fashion at the top, then commerce, infrastructure, governance and culture, with nature at the base. The fast layers experiment and learn. The slow layers remember, and they keep the whole system steady while the fast layers try things.

Marketing has the same structure. Tools, channels and formats live in the fast layers, where experiment is healthy and very little is meant to last. Customer needs, trust and reputation live in the slow layers, where change takes years and repairs take years too. Good work respects both speeds. It lets the fast layer move as quickly as the market allows, and it protects the slow layer from being rebuilt every time a new tool ships.

This is also why we never declare a winning technology. The tools we use this quarter are the best current available to us, and we fully expect to replace most of them. We choose them carefully, we use them hard, and we write our plans so that swapping one out costs a week of work and leaves the strategy intact.

Feeling behind is the normal condition

Nearly every leader we talk to says some version of the same thing. There is too much to learn, it changes too fast, and the people who are supposed to know feel just as behind. We feel it too, and the honest response is to say so.

Kevin Kelly anticipated this in The Inevitable (2016). He argued that technology would keep turning over so steadily that everyone, whatever their experience, would become a beginner again and again, relearning tools for the rest of their working lives. He described the direction of travel as protopia: steady, incremental improvement, each year a little better than the last, with no final state waiting at the end.

We take that as permission. If the experts are permanent beginners too, then nobody needs to memorize the field before acting, and nobody needs to make the perfect decision. The craft traditions have a word for this posture. Zen teachers call it shoshin, beginner's mind: meeting each problem with the openness of someone seeing it for the first time, even after decades of practice.

The practical result is a lighter load. Our clients pick the objective, use what works today and leave the tool watch to us. Our job is to track the current so their teams can spend their attention on customers, products and the decisions only they can make.

Every wave was supposed to end the work

Fear of replacement is the heaviest part of the overwhelm, and it deserves a direct answer. People worry that AI will take their jobs, and founders worry that someone with the same tools could copy their business in a weekend. Those fears are real, and history offers a steadier way to think about them.

Bhu Srinivasan's Americana: A 400-Year History of American Capitalism (2017) tells the story of the American economy through the industries and technologies that reshaped it, one era at a time. A pattern runs through it that we return to often. New technologies arrived with predictions that they would put large numbers of people out of work, and they went on to create industries, companies and jobs that nobody at the start could have named.

The printing press, desktop publishing and digital video each arrived with predictions that an industry would end. Each one widened who could make things and raised the standard of what got made. More people wrote, designed and filmed, and the best work found larger audiences than its makers could have reached before. AI belongs to that line.

The same history shows where lasting value sits. Code and copy have always been easy to imitate. Trust, proof, customer relationships, proprietary data and the speed at which a team learns from its market compound over time, and they belong to the people who earned them. We help clients build those assets on purpose, and we keep them moving faster than a copy can follow.

AI takes on tasks. Judgment, taste, relationships and accountability stay with people, and so does the courage to say something specific. A model that repeats what everyone else says will be passed over by people and machines alike, so the message matters more as the tools get stronger. We keep strategy, taste and judgment in human hands, and the machines carry the weight at speeds that used to be impossible, so ideas reach the market while they still matter.

Revision is the method

Donald Schön studied how professionals actually work in The Reflective Practitioner (1983). He found that skilled architects, engineers and managers seldom apply a formula and walk away. They read the situation, act, notice how it responds and adjust in the middle of the work, a skill he called reflection in action. Expertise, in his account, is that loop done well.

The military strategist John Boyd described a similar loop: observe, orient, decide and act, then run it again faster than conditions change. Lean startup methods brought the same idea to new companies as build, measure and learn. Three different fields arrived at one discovery: the team that learns fastest from real responses tends to win.

James Carse gave the loop its widest frame in Finite and Infinite Games (1986). He separated games played to win and end from games played to keep the play going, where the rules can change during play. Markets are the second kind. A brand is never finished being chosen, and the technology will keep opening, collapsing, consolidating and reversing for as long as we work.

So we treat revision as a skill to practice. Revision is planned for from the first day of every engagement, every release is a question put to the market, and every response tells us what to do next. Musicians, chefs and athletes have always worked this way. Nobody has ever finished music, and the joy is in the practice.

Proof from our own chapters

This philosophy comes from more than twenty-five years of building companies across several waves of technology. Each chapter served the same constant, putting a product in front of the person who will choose it, with the strongest current of its moment.

Lunchbox won the store shelf. Our team built it into a shopper marketing, original content and retail technology company that served nearly all of the top ten retailers and about eighty brands, and WPP acquired it in 2015. Retail programs such as Hot Wheels Race Rewards returned a 16:1 sales ROI, and every project was priced by the result, with any extra hours ours to absorb.

Zero Labs reengineered the road. For nine years the team took the most loved vehicle forms of the last century and gave them electric power, award-winning engineering and software-defined systems. A classic Bronco kept its shape and its meaning, and its drivetrain came from the future. The program produced more than 4,000 designs, won Best SUV and Best Pickup at Electrify Expo 2024, showed at CES in 2025 and 2026, and earned hundreds of press features and more than 88,000 signed order requests worth over $3.5 billion in sales demand, all with no advertising spend. Zero Labs Automotive concluded manufacturing in 2024, and its design and engineering practice continues inside ZLABS.

BigEV mapped the market in real time, modeling whole categories across electric vehicles, transport, marine and defense, and BigEV.news turns more than fifty thousand sources into a daily briefing. LBOX.com now wins the newest shelf, the AI answer, by measuring how answer engines describe each product and building the content and authority that move it up.

Lunchbox won the store shelf, Zero Labs reengineered the road, BigEV mapped the market, and LBOX wins the shelf that is now an answer. Four different currents carried one objective, and the objective never moved.

What this means on Monday

A philosophy earns its place when it changes what a team does this week. Here is how we put the constant and the current to work at the start of an engagement, and how any team can do the same with the tools it already has.

1. Name the constant. Write down which of the five objectives this work serves and how you will know it moved.
2. Choose today's best current. Pick the strongest tool available for the job and set the date you will review it, so replacing it later is routine.
3. Ship early and read the answer. Treat each release as a question to the market, and put the day you will read the response on the calendar.
4. Keep the message human. Let the machines carry the volume, and keep strategy, taste and the specific claim only you can make in human hands.
5. Build what compounds. Put part of every week into trust, proof, relationships and data, the assets that grow with time.

Each step works with what you have today, and each one gets easier with practice. Start with the first one this week: write the objective at the top of the plan, along with the date you will check it.

What comes next

Every issue of ZLABS University follows the same rhythm. We name a feeling we hear from clients, state the constant underneath it, show one current that helps today and close with a move you can make, with a date attached.

We are practitioners. There is nowhere to arrive, and we find that freeing. What we offer is the discipline of showing up every day with the best tools of the moment, aimed at the objectives that do not move.