As a dabbler in startup punditry (I've written a couple of books on startup positioning), I find Jerry's take very thought provoking.

The crux of the issue for me is what Dr Iain McGilchrist highlighted — we attend to the world in two very different ways. One mode of attention is a broad, open awareness to what's 'out there' and the other mode is a much more narrow focus on the parts and pieces.

For startups, when you look at the actual cases, many successful founders, almost by definition, had to stumble across their insight in some emergent fashion. They either experience some pain and set about solving it (Dropbox); see some opportunity on the horizon (OpenAI); or stumble onto some idea while working on something else (Slack).

If you want to do a startup, or your current idea isn't working, and you don't have that vision of emergent opportunity, then what do you do? "Just look for some emergent opportunity" isn't very compelling advice (even if it's probably the most accurate).

This is where the punditry emerges. You have to use your other mode of attention in an attempt to brute force some insight through narrow-focused analysis, and that analysis is inherently constrained to your (by definition) barren environment. That gives you the Lean Startup, customer development, etc etc. This far more analytical approach requires (a) intense discipline; (b) a lot of luck because you're starting from a point of no opportunity; (c) enough volume to actually do the interrogation of reality.

And it may not work because it's simply using the wrong mode of attention, anyway!

Nevertheless, frameworks that exist in this realm all sound reasonable because, on one level, they are: what else can you do but interrogate reality in some methodical way? But the question TFA raises (in my mind) is whether shaking the tree like this — IF you even can with appropriate discipline — reveals emergent opportunity for startups at a scale that's reflected in the broad outcome data, and the answer appears to be no.

Interestingly, the book The Heart of Innovation[1] tries to tackle this by going to the extreme. It's not about finding some clues in fast iteration or mapping out a canvas with a nice value prop, it's about finding 'authentic' demand that's so compelling it's something users can't not do. (The 'not not' concept is hard to explain but creates a much more rigorous bar for innovation IMO.)

That's their backward-looking observation for innovations that stick (and reflects most of the cases in the book), but they're still faced with the same dilemma of what to do if you aren't blessed with emergent opportunity.

In that case, their solution is to ramp up the analysis even harder, with 150-200 "Documented Primary Interactions" observations. I.e., brute force observations even harder. Some of the authors are part of a startup accelerator with an (apparently) high hit rate, so it's not just speculation.

All told, it's amazing that billions and billions of dollars are allocated to startups and so little is invested in studying innovation itself, especially given how slight the predominant frameworks are. Yet new ways of thinking exist (like McGilchrist, or the Heart of Innovation approach), so I wonder if frameworks for innovation are still in their absolute infancy, really, where the ones that succeed suffer the memetic curse: simple enough to travel; too simple to be effective.

[1] Excellent overview here: https://commoncog.com/the-heart-of-innovation-why-startups-f...