The Innovation Illusion: The Pace of Progress is the Same, but Our Perception Isn't
Or, Why the innovation plateau is a persistent lie fueled by hype, hindsight, and looking in the wrong places.
Welcome to this first post of 2026! I wanted to start the year with a case for optimism, or at least for a clear-eyed, hopeful perspective. It seems too many narratives today lead us toward a sense of technological stagnation and despair.
I do agree that mainstream tech innovation feels like it’s at a standstill. Over the last couple of decades, we’ve cycled through powerful hypes like AI and deep learning, crypto and blockchain, the metaverse, and now generative AI. So it’s easy to feel these are just refinements or desperate attempts to re-exploit old ideas.
And that feeling is partly correct. But what we’re witnessing isn’t a slowdown in innovation itself. It’s the relentless, noisy process of exploring and exploiting past innovations for profit. This isn’t inherently bad; it’s how we reap practical benefits. The problem is that marketing narratives label these iterative improvements as world-changing breakthroughs, distorting our sense of what true innovation looks like and how it arrives.
Truly transformative technologies like the internet, the smartphone, the automobile… never emerge fully formed. They diffuse over decades, not years. Their impact is measured in generations, not product cycles.
Why Does It Feel Like a Drought?
The sensation of stagnation comes from a perfect storm of impatience, distorted perception, and historical amnesia.
First, we exist in a feedback loop of our own creation. The very technologies we hail as revolutionary (specially the internet and smartphones) have engineered a hyper-informational environment. In this space, every claim is amplified, every technical paper is breathlessly reported as the “next big thing,” and venture capital narratives demand world-changing disruption narratives on a quarterly timeline. This creates relentless noise, exhausting hype cycles, and the pervasive, disillusioning impression that nothing ever lives up to its promise. We are drowning in the minute-by-minute commentary of the innovation process, mistaking the messy, incremental scaffolding for the finished cathedral.
Second, we fundamentally underestimate the slowness of foundational progress. Innovation at its deepest level, that is, understanding new laws of physics and translating them into reliable engineering, has always been a generational endeavor. Even the advent of AI, a powerful new tool, doesn’t change this core truth. AI excels at optimizing well-defined problems; it doesn’t magically shortcut the decades of trial, error, and insight needed to establish a new paradigm. Better tools allow us to tackle harder problems, not solve them instantaneously.
Finally, we are blinded by the tyranny of hindsight. Once a breakthrough is fully integrated into our world, its revolutionary nature fades, and its path seems obvious and inevitable. Consider gravity: Newton’s Principia was published in 1687, but it took until 1798 for Cavendish to first measure the force of gravity between masses in a laboratory. That’s over a century of gradual, painstaking work between theory and precise measurement. Today, we teach these concepts to teenagers in an afternoon. Everything looks simple once the answer is known. This powerful cognitive bias distorts and diminishes our understanding of the struggle required for genuine transformation. When you combine this with a culture hungry for the next shiny object and a fundamental misunderstanding of how science and technology actually advance, the feeling of a drought is inevitable.
Incumbents Are Focused on Optimization, Not Revolution
Our gaze is also fixed on the wrong actors. The tech narrative remains obsessed with the hyperscalers (Apple, Google, Meta…) companies that were once radical innovators. However, as with any organization that achieves massive scale, their focus has necessarily shifted. They are now in a defensive, scale-optimizing phase. Their immense resources are directed toward ecosystem lock-in, incremental product improvements, and leveraging existing monopolies. While they will loudly claim to be at the cutting edge of disruption, their structural incentives make them inherently conservative. True disruption, as Clayton Christensen’s Innovator’s Dilemma taught us, almost always comes from the edges.
This isn’t a moral failure; it’s an economic and organizational reality. A startup must shine with something radically different to survive. An established giant can, and should, focus on refining what already works to please shareholders.
The problem arises because the tech industry and media still look to these giants for guidance on the future. The conglomerates, in turn, are happy to oblige, using their platform to frame their latest iterative update as a revolutionary leap. It’s more palatable to call a new smartphone model “innovative” than to admit it’s a masterclass in iterative exploitation.
This symbiotic relationship functions as a powerful propaganda machine, obscuring where real, foundational work is happening. It’s understandable: it’s easier to watch a few glamorous keynotes than to sift through the output of millions of startups and thousands of monthly academic papers from global labs. The frontier of innovation is distributed, multidisciplinary, and often invisible to the mainstream cycle of hype and announcement.
The Optimistic Reality
The belief that we have reached “peak innovation” is not a new phenomenon, it is a recurring failure of imagination.
Consider the famously apocryphal quote attributed to Charles H. Duell, Commissioner of the U.S. Patent Office around 1899: “Everything that can be invented has been invented.” While likely a myth, it perfectly captures a sentiment that was in the air at the dawn of the 20th century. A century, in case that you have forgotten, that would later see the invention of aircraft, radio, television, antibiotics, and computers.
The real historical irony is even richer. In his 1902 Annual Report to Congress, Duell actually argued the exact opposite, writing: “...all previous advances... will appear totally insignificant when compared with those which the present century will witness.” Meanwhile, the renowned physicist Albert A. Michelson declared in 1894 that the major fundamental laws of physical science had all been discovered. This was barely a decade before Einstein published his theory of relativity, a work that Michelson’s own earlier experiments would help to prove and ended earning him a Nobel Prize.
If leading minds on the eve of history’s most transformative century could be so profoundly wrong about the limits of discovery, we should be deeply skeptical of anyone today who claims we’ve reached our own innovation plateau. The feeling of an ending is often just a sign that we are looking in the wrong place.
Why the “Ends” Are New Beginnings
It is true that certain specific, well-trodden technical paths are maturing, and maybe show exhaustion. This is not evidence of stagnation, but of evolution. Let’s examine the common arguments.
1. The “Low-Hanging Fruit” is Gone.
The argument goes as follows: the 20th century’s bonanza of inventions like transistors, lasers, electricity, global networks… was a one-time event, providing easy applications. Now, the foundational work is exponentially harder.
This confuses scientific discovery with technological diffusion and application. The “low-hanging fruit” of applying the digital layer (internet, smartphones, ubiquitous computation) to every physical industry, from agriculture to construction to medicine is still very much being picked. What we are seeing is not a lack of fruit, but a shift from picking it from the ground to needing new tools to reach the higher branches. The work is more complex, but the potential scope is still vast.
2. Moore’s Law is Ending.
First, Moore’s Law was an observation, not a physical law. Its slowing was always inevitable. But this doesn’t spell the end of computational progress; it forces it to evolve elsewhere. When we can no longer simply shrink transistors, innovation redirects to novel architectures (chiplets, neuromorphic computing), specialized silicon (TPUs, GPUs), photonics, and software-level breakthroughs. The end of one paradigm is the catalyst for the next.
3. Regulation Stifles the “Move Fast” Ethos.
Increased scrutiny around privacy, safety, and market power is often blamed for slowing disruptive pace. This is a shallow reading. Regulation doesn’t stop innovation; it matures and shapes its subsequent form. The automobile’s diffusion was “slowed” by the introduction of seatbelts, traffic lights, and emission standards, which are measures that ultimately made the technology sustainable and integrated into society. The real innovation was a completely new way of transportation, with far less limitations that what existed at the time.
4. The Smartphone Plateau is a Local Maximum.
Yes, the smartphone form factor is a mature platform. This leads some to wrongly assume the “next big thing” must be an equally ubiquitous object (glasses, a headset). This misunderstands transformation. There is no reason for the next paradigm to be a single device. There could be for example an ambient layer consisting in a seamless mesh of AI, sensors, and interfaces embedded in our environment. Its impact could be more profound, yet its arrival will be even more gradual and less tied to a dramatic product launch.
In short, the perceived end of a specific technical road doesn’t mean the journey is over; it indicates the need of switching vehicles.
Conclusion
The convergence of an absurdly fast-paced information ecosystem and the distorting power of hindsight has trained us to expect the “next big thing” on a quarterly basis. We have forgotten that genuine transformation is, and always has been, a matter of decades.
We stand amidst a silent explosion of progress. If you look beyond the hype cycle and check the relentless pace of scientific publication, the convergence of biotechnology with computation, the nascent experiments in sustainable energy and novel materials.. you don’t see a barren landscape, but a vast amount of possibilities. These are the threads slowly, inevitably, being woven into the fabric of our future.
Our impatience, ironically fueled by the very technologies we await to surpass, clouds our vision. Progress is being made, often hiding in plain sight within academic papers, niche startups, and engineering labs. The “innovation drought” is a mirage. The truth is simpler: we have been staring at the same few, well-lit stages while the next act is being prepared in the wings, out of view.
The story of technology is not one of dramatic leaps announced on a Tuesday, but of relentless, collective climbing. The summit we see today is never the last; it is merely the vantage point from which we finally spot the next, higher range.