Who Even Are You People? Part 2: John Cain

Ian Belknap (IB): So you’ve founded a number of different companies - tell me about those.

John Cain (JC): I co-founded (with Rick Robinson) E-Lab LLC (an at the time revolutionary research and design consulting firm that relied on the ethnographic tools and frameworks of the social sciences, an approach that’s come to be codified today under the banner of UX design) in the 90s (full disclosure - this is where John and I met - I worked for him at E-Lab for a few years, as a kind of uncredentialed court jester) which got bought out by Sapient. I stayed on a Sapient for a few years - on the one hand it was gratifying to see projects incorporating the approach developed at E-Lab carried out on a larger scale, on the other, I chaffed a little bit feeling like a cog in a machine. I left there, did some consulting. Then my friend Des from Sapient called me to help turn around this data informatics company in Portland, Maine, of all places - It was overpayment detection. It used data and analytics to look for patterns of fraud, waste, and abuse in Medicaid claims. After a few years, that company got bought by United Health Group, where I stayed till the day of my earn-out. Not a day longer. No love lost, there.

But the thing that  was kind of cool was I learned a lot about Big Data - this was before it was even called Big Data. And I learned this word “algorithm,” and I hired people that wrote code, And I kind of geek on that stuff because I went to engineering school as an undergrad.

This was around 2010. And there were all kinds of new f***-ed up sensors out there. Things on your wrist, things in your hand on your phone, the iPhone came out, 2007. It was all kinds of accelerometers and crap on your phone and car companies are reading accelerometer data off your phone and they're saying, “Hey you're a fast driver, we got to up your rates,” and that's a really interesting shift in the way the world works. And I became fascinated with this change.

And I wondered if you could do an E-Lab-style company from the basis of capturing and analyzing streams of data? So, I started this thing called Iota Partners with Rick (Robinson), and a couple of other E-Lab veterans. I found this guy named T.J. McLeish, and lo and behold a freakin’ miracle happened. I'm in Chicago - not Cambridge or Silicon Valley, or any of those places. I need some kind of Thomas Edison-meets-wizard type of person that can build sensor boards and we can deploy them on Windex bottles and put them on dog food, bowls and s*** like that because everything's miniature and Wi-Fi… we put them on packs of gum and we put them on Skittles bags. We put them in Target stores and we put them in homes and on boxes and bags. And we start generating all this data, like a huge amount. And we start playing around with the data like, “Hey, T.J., we need some people that can monkey with the data.” And he goes “Oh, I'm teaching a class at IIT (Illinois Institute of Technology) in the Architecture Department about using sensor data, I got a couple of students I could bring them in.” And I'm like, “Great! " because we have very little money. And one of these students is a guy named Peter Binggeser. And I pay him some piddly wage and feed him all my weird ideas, and Pete's always like “Yeah, I could make a visualization like that.”

Then eventually Sapient steps back in to acquire Iota Partners. And then we do even more s*** because we now have huge budgets to waste on cabinets full of lithium-ion batteries, just frickin’ Looney Tunes s*** - it looked like the MIT Media Lab in there. And we got all kinds of kids soldering up circuit boards, and putting Google glass on robots, and hollowing out Mr. Potato Heads and putting cameras in them to observe the way people wash dishes, and stuff. And I’m like “This Pete kid is an absolute wizard.”

Pete has got this speed and pragmatism. But he's also got this open-ended creative component, like his former instructor T.J. does, but T.J. gets lost in it, whereas Pete can direct his creative problem-solving towards the solution to a thing and make it overnight, and that's astonishing quite frankly.

IB: Why’s he like this, do you think?

JC: Pete tells a story about this one Christmas  his grandfather gave him this footlong piece of rope along with this little Xeroxed paper, like three inches square, with instructions for tying various knots. This was obviously an assembly line/”same gift for every grandkid” kind of deal. So, where most kids would be like “thanks for nothing, Gramps” and toss it aside, Pete studied the little square and took the rope and mastered that group of knots. His grandfather's German, so there's this ribbon of ascetic pragmatism that’s like “ you have to learn to be curious about the simple thing because it's really complex, and you have to learn how to tie a knot, and you have to learn how to get something done completely.” He likes the act of creation but he's got this, just remarkable ability to turn the creative act into a finished thing. Usually in a super elegant way. It's quite rare.

So, anyway, after a while of doing Iota-within-Sapient, we kind of conclude that there’s way bigger players and we probably can’t make the kind of impact we hope to, so I go off to work with Bill Kendrick (who’d engineered the Iota buyout,) who’s gone on to start Material, and Pete goes off and works at Twitter. But we stayed in touch and did little projects here and there.

And then like any observer, I see AI bubbling up everywhere. And what I see in this shift towards AI is both amazing upside potential, but the possibility for horrifying dystopia, as well, if we don't get after shaping it differently. So, there’s this seismic societal and technological shift taking place, akin to the one that led to the blending of disciplines at E-Lab. A kind of shift that one really doesn't deserve to see twice in one's lifetime, but here I am watching another one happen. I want to get attached to it…

So after I got bored enough by consulting gigs that were essentially very similar, and Pete quit Twitter, we got together and started thinking through some of the implications and applications of this stuff. And we immediately began seeing all this potential for this impossibly potent tool that was not getting widely utilized, and starting noodling on how to unlock some of that. The more we delved into, though - the more we concluded that AI’s real power would get unleashed if we built this ongoing, constantly expanding set of tools where people could monkey around with it themselves - not just feeding scripts to chat-bots, which seemed mostly what LLMs were getting used for - but in real-time prototyping, in interrogating and modifying concepts on the fly, in building and testing processes for almost no cost. So, while we’re obviously grateful for the consulting work we get, the real legacy we’re trying to put in place is a nimble, adaptable, easy-to-use set of modular components that put the power of this frankly astonishing technology in the hands of just about anybody.

That’s what the ZeroWidth Workbench is.

Next Up:

A Story of Foosball Overkill with Pete Binggeser