How a piece of brain software helped the Valley escape incremental culture and learn to think exponentially.
Silicon Valley is not really a place. It is a rate of change. Elsewhere, a tenfold improvement is the achievement of a generation. Here, it becomes a product target—scale and speed-and soon the minimum acceptable result. The Valley’s most revealing number is 10.
Not 10 percent. Ten times.
Incremental thinking adds. Exponential thinking multiplies. The first produces a predictable staircase of improvements; the second creates a curve that looks harmless at the beginning and astonishing later. Ten successive 10 percent gains improve something by about 2.6 times. Three x10 leaps produce a thousandfold change. x10. x100. x1000.
A conventional company asks how to become 10 percent better, preserving its process and assumptions. An x10 question destroys that continuity. Polishing the present will not work; the system must be redesigned.
That mental jump can be written as a compact piece of “brain software”:
CVS × 10 = BVS
CVS is the current view of the situation. BVS is a better view of the situation. The x10 in the middle is an escape instruction: stop defending the present model and search for one so much better that incremental change cannot reach it. Then the BVS becomes the next CVS and the switch can be flipped again. That repetition of CVS × 10 = BVS × 10 = next BVS. It is exponential thinking rather than a single burst of ambition.
Nor is the operator limited to productivity. Written as x10 or 10x, it applies to any cognitive context: options, understanding, safety, clarity, empathy, revenues up or costs down: one-tenth the cost, waste or risk. The point is to change not only scale but also speed. Change until the current view breaks open and a previously invisible BVS becomes thinkable.
Four decades later, Silicon Valley’s leaders still speak the language on a daily basis. Larry Page wants products ten times better. Astro Teller wants moonshots ten times bigger. Peter Thiel wants technology ten times better than its substitute. Reid Hoffman asks what happens when AI makes everyone ten times more productive. Mustafa Suleyman says frontier AI has made us ‘accelerationists’ able to move ten times faster by using powers of ten.
This is a memeplex: mutually reinforcing ideas about scale, speed, cognition and escape. Its route into the Bay Area has a deliberate and human origin story. I know because I was there.
The switch arrives
In 1984, I published NewSell through Boardroom Books in New York. On page 137, I wrote: “The BVS is always ten times better than the CVS.” It introduced the idea of tenpower in thinking which is moving through information by powers of ten. The tool was the portable algorithm CVS × 10 = BVS.
The number was a cognitive forcing device, a neuro algorithm. Ask for a small improvement and the brain retrieves familiar options. Ask for an order-of-magnitude improvement and you must reverse an assumption, remove a bottleneck or invent a category.
I expanded the neuro-software algorithm in Software for the Brain in 1989. The human “necktop computer” was immensely powerful but frequently ran obsolete medieval cognitive software. By 2000, I had deep-dived the switch into an enterprise challenge in The x10 Memeplex: Multiply Your Business by Ten! Why settle for another 10 percent? What would have to be true to multiply your metrics by ten?
My first Bay Area intervention came through education. In 1984, San Francisco Unified School District superintendent Robert Alioto approved the introduction of SOT lateral-thinking skills and I was invited to train the district’s primary-school principals. By 1985, special thinking lessons were being delivered in schools. Subsequently the Valley later institutionalized the exponential x10 thinking software through Google, X and Singularity University.
Not only in SFUSD classrooms but local leaders, like Larry Page at Google, showed convergence around the belief that thinking can be trained and an order-of-magnitude target can produce a qualitatively different answer.
Silicon learns to compound
The Bay Area’s hardware was already teaching exponential psychology. In 1965, Fairchild Semiconductor’s Gordon Moore observed that components on an integrated circuit had been doubling roughly every year. A forecast became an industry timetable. Exponential change became something the Valley planned to deliver.
Intel CEO Andy Grove adapted it into management theory. His “10X force” was a technological, competitive or structural change powerful enough to invalidate the old strategy. In a 2000 Intel address, Grove warned that an organization could not “defer and deny” an inflection point carrying such force.
Grove’s concept was diagnostic; mine was generative. One detected the tenfold force coming from outside. The other asked the brain to generate a ten-times-better view inside. Together they describe the Valley’s survival and growth trajectory: recognise when the world has changed by an order of magnitude, then change your thinking by an order of magnitude, too.
The gospel according to Google
Google converted 10x from a regional instinct into corporate doctrine.
By 2013, WIRED’s Steven Levy described Larry Page as living by the “gospel of 10x.” Page expected Google teams to create products and services “10 times better than the competition.” Page supplied the reason: “Incremental improvement is guaranteed to be obsolete over time.”
Search, Gmail and Maps did not merely compete inside categories. They altered their dimensions.
At Google X, Astro Teller helped turn ambition into process. His moonshot doctrine was “ten times bigger, not 10 percent bigger.” Ten times bigger demands a clean sheet.
X combined ambition with aggressive falsification: test hard assumptions first and kill weak projects early. Without disciplined experiments, a moonshot is merely a hallucination with a budget.
Google embedded the behaviour beyond the laboratory. Google Cloud disclosed that “10x thinking” became a category in twice-yearly employee reviews. WIRED filmed visitors entering a campus workshop where facilitators promised to teach them how to “10x” their projects. Founder language had become training, process and evaluation.
The x10 meme had become infrastructure.
Singularity University extended exponential literacy into executive education. Founded in Silicon Valley in 2008, it taught leaders to distinguish the intuitive linear future from technologies improving through repeated multiplication. “Thinking exponentially,” its curriculum states, “is core to everything we teach.”
Three dialects of x10
In 2000, Prentice Hall/Penguin published my book The X10 Memeplex: Multiply Your Business By Ten.
In the Valley, leaders adapted x10 thinking to at least three overlapping domains: product superiority, human amplification and civilisational acceleration.
Peter Thiel supplied the product test. In 2015 Penguin published Thiel’s Zero to One in which he argued that proprietary technology should be at least ten times better than its closest substitute in an important dimension. Anything less looks marginal in a crowded market.
Elon Musk uses the same scale across products and cognition. Discussing Neuralink, he asked listeners to imagine communicating at “10, or 100, or 1,000 times faster than normal.” He described memes as compression: if one word carries what normally requires ten, “you’ve got maybe a 10X compression.” Order-of-magnitude rhetoric has become a default Silicon Valley setting.
Reid Hoffman applies x10 to organizational design. If AI makes everybody “10x more productive,” the shallow response is one-tenth the staff. Hoffman instead asks whether customer service can become a relationship, sales or brand-building function.
Sam Altman applies it to executive cognition. An AI assistant can carry “10x the context any human executive can carry.” His advice: do not order transformation while leaving your own workflow untouched.
Marc Andreessen pushes amplification further: “The 10x engineer becomes the 100x engineer.” Work shifts from individual execution to orchestration of machine agents.
Desensitized to miracles
Mustafa Suleyman, cofounder of DeepMind and CEO of Microsoft AI, describes what this culture feels like from inside the frontier. Progress compounds so quickly that “we just get desensitized to 10 times.” A milestone is crossed, normalized and replaced by impatience: “Guys, why haven’t you done it yet?”
For decades, conversational AI passing something like the Turing test was imagined as a civilization-stopping event. Machines moved across much of that territory without a single ceremonial moment. There was no collective pause. Users complained about latency.
Suleyman connects the psychological effect to a scaling reality. He has described frontier-model compute as growing by roughly 10x each year across the modern deep-learning decade. Exact rates vary with the period and measurement, but the trajectory is indisputably exponential: huge increases in computation, speed, data and investment have repeatedly opened new capabilities.
This is the miracle effect. Each exponential result becomes the new baseline; every BVS becomes the next CVS.
How to multiply your own business x10
Begin with a precise CVS: what customers buy, how value is delivered, what takes time and which assumptions nobody questions. Do not confuse this description with reality. It is only your current view.
Choose a dimension that matters: customer value, trust, quality, safety, learning or simplicity. Do not make employees work ten times harder. Ask:
What would ten times better look like to the customer?
What if cost, delay, complexity or risk fell to one-tenth?
Ban incremental answers. “Hire more salespeople” usually scales the old machinery. Search for an answer that changes it: a new distribution model, an AI collaborator, a platform, partnership or the removal of an entire step.
Generate at least ten possible BVS ideas before judging them. Test the riskiest assumption cheaply and early. Keep the evidence, discard the theatre. When a BVS works, it becomes the next CVS. Flip the switch again.
Exponential culture is a repeatable habit of escape. It can be trained. Measure training as seriously as revenue. Multiply your training by ten. Reward people who reveal obsolete assumptions. Put x10 questions into planning, product reviews and leadership development. The formula becomes culture when people use it without permission.
Flip the switch
The Valley did not become x10 because someone distributed a single manual. The culture emerged from reinforcing systems. Moore supplied the hardware curve. Grove identified the strategic force. I published a cognitive escape switch. Page made tenfold ambition a leadership expectation. Teller made it an experimental discipline. Singularity made exponential thinking a curriculum. Thiel made it a product threshold. Hoffman, Altman and Andreessen applied it to AI-amplified work. Musk pushed it toward human bandwidth. Suleyman described the resulting psychological acceleration.
The next step belongs to every organization now confronting AI.
If intelligence becomes ten times cheaper, what happens to pricing? If an employee gains ten times more capacity, do you cut the team or attempt work previously beyond it? If AI carries ten times more context than the chief executive, which decisions and reporting layers become obsolete?
The real x10 question is confronting: if today’s technology had always existed, would anyone design the organisation you currently operate? Where will you be in 2028?
Silicon Valley’s great habit is not prediction. Its leaders are wrong constantly. The habit is treating the current view as temporary, building systems that reward escape and placing capital behind answers that redraw the category.
That is my School of Thinking reading of the Valley’s rhetoric. Its leaders use the powers-of-ten meme across products, understanding, human capability and civilizational change. They are not talking about working a little harder or making one heroic leap. They are talking about escaping the traditional medieval mindset, establishing a new current view, then multiplying x10 again. And again. And again.
The machines are now learning to search possibility space at a scale no unaided person can match. Artificial intelligence is turning a regional Valley habit into software.
Your business already has a current view of the situation. The only question is whether you will defend it or multiply it by ten.
That challenge matters now because Silicon Valley is attempting its most audacious act of leverage: designing machines that perform artificial x10 thinking.
The early large language models offered a glimpse.
2028?
For example, GPT-3, released in 2020, could certainly finish a sentence and sometimes produce pages of surprisingly fluent prose. But it often lost the plot, invented facts, mishandled multistep reasoning, and stopped at the border between saying and doing. The wonder was linguistic plausibility. Reliability was another matter.
Only six years later, after models 4 and 5, GPT-6 systems can browse, write and test software, operate computer interfaces, analyse data, and produce finished business artifacts. OpenAI describes GPT-6 Astra as capable of multistep professional work across browsers, documents, spreadsheets, presentations, coding environments, and scientific software.
“Miracle” is not a technical unit, but it is an understandable human reaction when a machine turns a sentence into a working product.
The progression from GPT-3 to GPT-6 is not literally three neat 10-fold jumps. Model names are not rulers, and intelligence does not increase on a single axis. Yet the compounding is real. More capable models combine with better tools, larger context windows, faster chips, richer data, improved training methods, and software that can plan, check, and retry. Each layer multiplies the usefulness of the others. The result is not merely a better chatbot. It is a new production system for cognition.
That raises a deliciously uncomfortable question: If GPT-6 can do this today, what might GPT-9 do in, say, 2028?
