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For a few months now, I’ve been talking to my new neighbors here in California about my old friend Leo Villareal’s proposed epic installation on the Bay Bridge, commemorating the Bridge’s 75th anniversary and the completion of the new East Span in 2013. You can find more about it here, including some great visualizations, but the shorthand description from the promotional site is this:

Created with over 25,000 energy efficient, white LED lights, it is 1½ miles wide and 500 feet high... The Bay Lights is a monumental tour de force seven times the scale of the Eiffel Tower’s 100th Anniversary lighting.

There’s been a lot of buzz about this project, and it seems like it has a very good chance of being made thanks to the $3M challenge grant they’ve received. This would be terrific news. There’s no question in my mind that The Bay Lights would become an iconic example of grand urban art: a digital-age Gates or Wrapped Reichstag. Visually it will be intoxicating, I have no doubt. But I think there’s an important element to The Bay Lights that makes it uniquely appropriate to the Bay Area context. Leo is an environmental/algorithmic artist. Leo’s installations are, literally, programs. There are many interesting artists tinkering with software and human interfaces now, but most of their work lives on the screen or in a browser. Leo’s code lives outdoors, on a grand scale. He writes software for cities, not screens.

So I can’t think of a better way to celebrate the bridge at the heart of the Bay Area than with an immense work by one of the most acclaimed algorithmic artists of our time. The world capital of code should have a coder/artist as its Christo. Let’s make it happen.

People often ask me about my research techniques. You would think this would be a relatively straightforward question, but the truth is that I have to keep changing my answer, because my techniques are constantly shifting as new forms of search or discovery become possible. Right now, I'm in that thrilling stage of writing-while-still-researching my next book, and I just went through a little episode of discovery that I think might be worth mapping out, as a case study of how ideas come into being, at least in my little corner of the world.

The subject matter of the book is not all that important here, but suffice it to say that I am currently working on an introductory bit that contrasts old, bureaucratic models of state organization with some new network structures that are currently on the rise. So my mind has been primed for anything that seems thematically relevant to those topics.

This particular thread begins with a random encounter on Twitter: checking out my @ mentions a few weeks ago (vanity will get you everywhere), I stumbled across someone mentioning my book to a friend, and also recommending something called "Seeing Like A State." (I can't track down this tweet, so can't give proper credit here.) I wasn't fully sure what "Seeing Like A State" was, but it sounded up my alley, so a quick Amazon search revealed that it was, in fact, a very promising-sounding book written by James C. Scott, about the methods of state organization and control in modern history, and so within a matter of minutes, I was reading it on the Kindle iPad app. (I'm sure it is mentioned in many books that I've read already, but somehow I had missed it over the years.)

The book turned out to have a small discussion of the design of the French railway system in the early 19th-century, which reminded me of a map my old mentor Franco Moretti had showed me two decades ago in grad school, contrasting the heavily centralized French system with the more chaotic British rail lines. So that sent me into a quick exploration of French engineering history that culminated in downloading two PDFs of academic essays on the topic, each of which provided some key historical texture that was missing in Scott's book.

In the meantime, I was continuing to devour Seeing Like A State. Feeling a little guilty about missing a book that should have come across my radar before (it had been published in 1998), I googled around to see what responses the book had generated. As it happened, one of the top-ranking results was a blog post by the political theorist Henry Farrell, with whom I have been discussing the ideas in my new book for many years now. His post was part of a larger debate about the Scott book with the economist Brad DeLong, who had penned a detailed review on his blog. One of DeLong's main criticisms is the way in which Scott ignores the insights of Hayek, which sent me back to an essay of Hayek's that I'd been meaning to read for my book, but hadn't yet got around to. The Hayek essay opened up a whole approach to what I was writing about that I suspect will generate at least a dozen pages of material in the final book.

As I was reading the Scott book, I was storing my highlights from it in the new service, findings.com, which we launched a month or so ago. Findings lets you organize important quotations from eBooks or the Web, but it also allows you to follow other users' quotations. (My introductory post about it is here.) One of the fascinating things it lets you do is see what quotations other readers found interesting in the books you've read. And so when I was reviewing my quotes from the Scott book, I discovered a few other Findings users were also reading it, and one them had picked out a quote that I had somehow missed, a quote that perfectly described the logic of state organization. That turned out to be the quote from the Scott book that I ended up using in my own chapter.

Sometime in the middle of this, I gave a talk at Google, and the speaker before me was the Internet legend Vint Cerf. Listening to Cerf talk about the origins of the Internet -- and thinking about the book project -- made me wonder who had actually come up with the original idea for a decentralized network. So that day, I tweeted out that question, and instantly got several replies. One of those Twitter replies pointed to a Wired interview from a decade ago with Paul Baran, the RAND researcher who was partially responsible for the decentralized design. When I clicked through the link, I discovered that the interview had been conducted by my friend and new neighbor, Stewart Brand, with whom I was having lunch that week. So when I saw Stewart I got to ask him about Baran, and try out this little hunch I was working on about the contrast between the French rail system and the design of the Internet. Meanwhile, one of the other Twitter replies had pointed me to Katie Hafner and Matthew Lyon’s Where Wizards Stay Up Late, released more than a decade ago but also available on Kindle, where I found a detailed history of the Internet's early days. And reprinted in that book was an early sketch by Baran of the network model that beautifully contrasted the centralized model of the French rail system, and the map that I had seen so many years ago as a grad student.  

And so after all that meandering, my vague introduction had turned into two distinct stories, with two perfectly contrasting diagrams to anchor them visually.

What's the moral of this story? I think there are a few:

1. The discovery process is remarkably social, and the social interactions come in amazingly diverse forms. Sometimes it's overhearing a conversation on Twitter between two complete strangers; sometimes it's the virtual book club of something like Findings; sometimes it's going out to lunch with a friend and bouncing new ideas off them. It's the social life of information, in John Seely Brown and Paul Duguid's wonderful phrase -- we just have so many more ways of being social now.

2. I find it interesting that there are certain kinds of questions that I now send out by default to Twitter, not Google. The more subtle and complex the question, the more likely it'll go to Twitter. But if it's simply trying to find a citation or source, I'll use Google. So trying to figure out who wrote Seeing Like A State was a Google query, but wondering about the origins of the Internet made more sense on Twitter. (I should add that the responses I'm looking for on Twitter are links to longer discussions, not 140 character micro-essays.)

3. Priming is everything. All these new tools are incredible for making rapid-fire discoveries and associations, but you need a broad background of knowledge to prime you for those discoveries. I'm not sure I would have jumped down that wonderful rabbit hole of the French railway design if I hadn't seen that map in grad school two decades ago. Same goes for the Hayek and the internet history as well. I had enough pre-existing knowledge to know that they belonged in the story, so when something about them got in my sights, I was ready to pounce on it.     

4. Very few of the key links came from the traditional approach of reading a work and then following the citations included in the endnotes. The reading was still critical, of course, but the connective branches turned out to lie in the social layer of commentary outside of the work.

5. It’s been said it a thousand times before, by me and many others, but it's worth repeating again: people who think the Web is killing off serendipity are not using it correctly.

6.  Finally, this simple, but amazing fact: almost none of this--Twitter, blogs, PDFs, eBooks, Google, Findings--would have been intelligible to a writer fifteen years ago.

The coverage of the deal thus far has focused on two primary angles: either Disney acquiring a "hipster" parenting site, or the vindication of the blogger-network content model. (Babble runs a large network of "mommybloggers," as they have come to be called.) But I think there's a simpler lesson here that's being overlooked. Babble was a cultural and commercial success because it took on a topic that was exhaustively covered by existing media, and wrote about it in a fresh, nuanced, and more complex way. It had a genuinely new voice that was far more in touch with the actual experience of parenting, and it featured talented writers who wrote about their lives with a sophistication that was simply nonexistent in traditional parenting sites or magazines. (They even asked me to write a piece about parenting that pulled in Jane Jacobs and complexity theory -- an invite that let's just say I would be quite surprised to receive from Parenting.com.) As Rufus and Alisa wrote in their initial mission statement: 

We created Babble for one very simple reason: we can't find a magazine or community that speaks to us as new parents. Every publication we encounter presents procreation as a cute and cuddly experience, all pink and powder blue, at best an interior decorating opportunity, at worst a housekeeping challenge. None of it is true to the experience we are having, and that we see around us.

So to me, the success of Babble should be a corrective for all those folks who think that the Web has lowered our journalistic standards, or that original, provocative writing online doesn't have a business model to support it. Yes, Babble was not a commercial success on the level of Facebook or LinkedIn or Zynga. Content sites don't have that kind of scalability. (Though they may well have an easier path to profitability.) But Babble did make a tidy return for their investors, led by Village Venture's Bo Peabody, who has long argued for the value of advertising-supported content sites. The commercial viability of the web shouldn't just be about a handful of billion-dollar IPOs. It should be about a thousand smaller-scale successes, where new voices can both find an audience and create sustainable business models. Babble managed to do both those things in just a few short years -- and that's great news for all of us.  

I have been dreaming about new tools that would help me capture what I was reading for almost as long I have been reading. During my college years, I lost a semester trying to build an epic Hypercard stack called "Curriculum" that would help me organize all my notes for the courses that I had stopped attending because I was too busy building the software. (Oh, the irony...) In my twenties I began keeping digital copies of influential quotations from books I had read so that they were searchable on my hard drive; during the next decade I stumbled across a brilliant application called Devonthink that enabled me to make interesting connections between those quotes. (I wrote a little lovesong to Devonthink for the New York Times Book Review in 2004.) While I was writing Where Good Ideas Come From, I found myself exploring the long and rich history of the commonplace book, one of the great intellectual engines of the Enlightenment: books of quotations assembled by hand by 18th-century readers, annotating and indexed and remixed by readers like Locke, Jefferson, and Priestley.

A few years ago, I had the good fortune of being re-introduced to John Borthwick, whom I had known slightly in the original dot-com years. We got to talking over lunch about our shared obsession with research and annotation tools. This was somewhere post-Friendster but pre-Twitter, so the idea of making these systems more social was very much in the air. A blog post I had written about Devonthink in 2004 had included this little riff:

The other thing that would be fascinating would be to open up these personal libraries to the external world. That would be a lovely combination of old-fashioned book-based wisdom, advanced semantic search technology, and the personality-driven filters that we've come to enjoy in the blogosphere. I can imagine someone sitting down to write an article about complexity theory and the web, and saying, "I bet Johnson's got some good material on this in his 'library.'"

John and I continued to nibble at the edges of that idea for next few years, until late 2010, when we began to talk about building something in earnest, under the wonderful umbrella of Betaworks, which had already incubated and launched a string of great services and apps: bit.ly, News.me, Tweetdeck, among many others. Early on we had the great fortune to bring in our co-founder Corey Menscher as head of product (well, let’s be honest, head of just about everything.) Today, I’m thrilled to announce that our collaboration has led to the launch of Findings.

The service is simple enough -- and draws upon a few social conventions that will be instantly recognizable. (So feel free to just go try it out and skip the rest.) At its core, Findings is a service that allows you to capture, store, search, and share small snippets of text from eBooks and web pages. It integrates Kindle highlights and web clippings (with more input options to come.) And it gives you the ability to share those quotes with your peers, as well as follow other people’s quotes through your timeline. 

There are plenty of other services and apps out there that clip and store text. (When John and I first met for lunch, he was using a modified WordPress setup to store his personal quotes.) But with Findings, we are trying to do something that is dedicated explicitly to the task of curating quotations. In other words, it’s not designed to be a broader publishing platform, or a more generic notebook app that happens to include quotes every now and then. It’s a social commonplace book.

That narrowness of focus has allowed us to concentrate on a couple of key features that make Findings particularly useful. First, because we are focused on quotations, we have built a number of smart systems that pull metadata from the sources, which allows you to seamlessly organize your quotes around authors and titles and sources (and other organizational schemes we are going to dream up in the months ahead.) And the social component means you can do the kind of “searching someone else’s library” that I was dreaming of seven years ago. The combination of sharing and metadata means that we can start pinpointing the exact pages and passages that people are fixating on right now.

In the next few months, we plan on expanding the ways in which you can organize and navigate through your findings. (We are also expanding the team, so if you’re interesting in helping in a more direct way, give us a shout.) We want to make Findings the best service out there for people who have very rigorous organizational needs, and at the same time make it an engine of serendipitous discovery as well. But reaching those lofty goals will require feedback from you: how are you using Findings? What do you want it to do better? So go check it out and and let us know what you think.

[More in the series of excerpts from the conversations in my new collection, The Innovator's Cookbook. This is part of my exchange with the brilliant Ray Ozzie, who recently stepped down as Microsoft's Chief Software Architect. Ray has been thinking about social software for as long as just about anyone, so I had to ask him how those ideas had evolved over time.]

SJ: How did the idea for Lotus Notes come about?

RO: The Lotus Notes is story is one of those situations where I and several other people––the people who ended up being my cofounders—were exposed to a system that we couldn’t shake. It became an itch that we needed to scratch. And the thing that we ultimately built, both the ethos and the name itself, came from that thing that we were exposed to. The product we ultimately built was actually a lot different. But the original experience was the common thread between us.

This was in 1974 through 1977, and there was a group of us who were exposed to this Plato system at Urbana-Champaign in Illinois. This was on the early side of computer science; we were still using punch cards in our computer-science classes. But this Plato system was built by this creative eccentric, Don Bitzer, who believed that computers could change education. He didn’t know what couldn’t be done. He wanted to build graphics terminals with multimedia, audio. He invented the plasma panel, in order to have a graphics terminal. He built an audio device for it. That left an imprint in and of itself. I love being around people who just don’t believe things can’t be done, or don’t know that they can’t be done, and just build whatever the concept requires.

But on the software side, we were all exposed to things that ultimately we’d get used to in the Internet. It was the emergence of online community. And there was probably a community of ten thousand people, five thousand at Urbana, Illinois, and another five thousand around the world. There were online chats, online discussions, interactive gaming, news. It was a full-fledged community. And there was this thing called Notes that did e-mail, personal notes, and discussions, group notes. And after we left, and went into the real world and got our jobs (they went to DEC, I went to Data General), that was the thread that we kept coming back to. We were like: these are interesting computers, but where are the people? And so basically we would get together weekend after weekend, month after month, year after year, and say: “We have to bring the people back into the equation.”

SJ: So it ends up taking you six, seven years before you actually start building that thing in your head. It reminds me so much of something in my own life, although I didn’t do anything nearly as epic. I was in college from ’86 to ’90 and HyperCard came out in ’87. I’ve never really been a programmer, but I lost a whole semester trying to build this HyperCard application basically for keeping all my notes and research. (Which eventually fed into my interest in applications like DEVONthink and the commonplace-book tradition.) But the main thing I got out of HyperCard was that it really prepared me for the Web, by working in that hypertextual environment. So I dabbled with HyperCard and then I kind of put that experience away for seven or eight years—but then in ’94, when the Web started to break, I was just prepared for it. The first time I saw it, I was like: oh, I know exactly what this is going to be.

RO: That’s a reoccurring theme also. You are the sum in many ways of your experiences and you get these success patterns, failure patterns, sometimes those patterns help—like what you just described. But sometimes those patterns hurt, because they constrain your outlook. Something that might not have worked before might work now, because the environment has changed. But the innovators that I know that are successful keep testing those patterns over and over and over because people around them change and the technology environment changes. And so you might look at somebody and say: “You’re a one-trick pony. You keep building the same thing over and over.” But it’s a good thing! That means you’re taking those patterns and just recasting them continuously against changes in the environment. And if you believe passionately in a pattern, it’s great. Go for it!