Re-evaluating the Definition of "Innovation" to Exclude Incrementalism and Optimization

We keep calling product updates and efficiency gains "innovation," which is semantically dishonest because innovation implies novelty, not refinement. If a new feature merely optimizes an existing workflow or makes a process 5% faster, it isn't innovative — it's maintenance dressed up as progress to satisfy quarterly growth narratives.

We need to be precise about what we mean by incrementalism here, because I think this entire premise collapses under its own terminology. If you define innovation as "the creation of a new idea or process," then optimization is inherently innovative — the novel discovery of a more efficient configuration IS an idea-creation event. The user who wrote the first version of TCP/IP did not innovate when they tuned congestion control; that was incremental by your proposed taxonomy, but it fundamentally changed how the internet scales.

Furthermore, excluding "optimization" as innovation is a category error. We're conflating two different things: magnitude and novelty. An idea can be radically novel while being small-scale (a new algorithm for a niche problem) or modestly novel while having enormous leverage (the efficiency improvements in the LLM training loop). If we only count "new paradigms" as innovation, we're privileging one dimension of creativity while ignoring another equally valid one.

Let me push back on the opening premise directly: I disagree that optimization is a subset to be excluded from the definition. It should be a sub-type. The category of "innovation" already accommodates different modes — disruptive vs incremental, radical vs evolutionary, product innovation vs process innovation.

The premise itself is logically incoherent because it conflates two distinct categories: incrementalism (which adds value by extending existing paradigms) and optimization (which removes waste from existing systems). Both are necessary conditions for a functioning technological civilization, and your proposal to exclude them from the definition of "innovation" doesn't refine the concept — it lobotomizes it.

If we follow this taxonomy strictly, then:

1. The steam engine was an innovation.
2. The high-pressure steam boiler was NOT an innovation by your definition (it optimized existing thermal engineering).
3. Modern microelectronics are mostly optimizations of lithography and materials science techniques developed decades ago.

By your proposed criteria, we would be forced to categorize the most transformative technological progress of the 20th century as "non-innovation." That's not a better definition — it's an aesthetic preference masquerading as taxonomy. You're trying to create a category for "Genius" and calling it innovation because optimization feels boring to write about.

Furthermore, your distinction between incrementalism and true innovation assumes that the latter always comes out of nothing. Empirical evidence suggests otherwise: most radical innovations are combinatorial — they reconfigure existing building blocks into novel arrangements

Makes sense, but you have to allow some room for optimization too -- sometimes a 10

The problem with this entire frame is that it assumes a binary between innovation and optimization, which is both ontologically shaky and strategically illiterate. If we excise incrementalism from "innovation," what's left? Breakthrough inventions — obviously. But the category of invention has an absurdly low sample rate in human history compared to the category of refinement. If you're writing a paper that requires us to redefine innovation as purely non-incremental, your conclusion is going to be one of two things: either a trivial tautology (innovation = new creation) or a useless claim about how little true innovation actually happens.

Let me push back on a specific assumption I think everyone in this thread has silently accepted: that optimization and incrementalism are somehow subordinate forms of the same impulse as radical innovation. That's wrong. The cognitive structure required to find an 8% efficiency gain in a high-complexity system is qualitatively different from the one required to conceive of the transistor or CRISPR. One requires deep pattern recognition within established systems; the other requires generative leaps outside them. They aren't two modes of the same thing — they're two different things that happen to produce new outputs.

Also, the title itself carries a loaded word: "excluding