If you’re interested in my work with tech companies, you’re in the right place! But if you’re interested in my work with sustainability related organizations, please check out one of those two links above.

Here are short descriptions, followed by the specific AI that I find most effective for each of these use cases.

• “What have I written in my notes over the years that’s most relevant to the following topic?” This is my #1 go to for things both fun and serious. (Claude Project, described here)
• Asking for counter-evidence to any text I’m reading. Also really helps me understand the original text more quickly. That recent Nature article on how AI is essential to solving climate change? ChatGPT took some steam out of that for sure. (ChatGPT with a javascript bookmarklet, described here)
• Create a set of synthetic personas that are relevant to a given topic and have them answer a question I have, thinking through step-by-step. The answer can be open ended on a topic, or specific like “what do you think of this email?” I do this every day and it always brings up points of view I am thankful to consider. (Claude)
• Make a briefing book about a person or an organization I’m about to meet. (Perplexity) Now make a personalized version of it for a person I’m going to introduce the first person to, highlighting similarities and differences between their work (Perplexity) and then turn that briefing book into an attractive one page artifact (Claude)
• Perform a combinatorial analysis of the X! ways that two sets of information could cross-pollinate; for example, consider a big set of updates from a set of organizations in a network, and ask “what could be done if update #1 were connected to update #2, etc?” (Google NotebookLM) Then score those combinatorial possibilities based on a set of criteria like “would this combination have transformative potential?” “Are these organizations geographically near each other?” And perhaps most importantly “is there a discoverable history of these organizations working together previously?” The combinations that score Yes, Yes, No to those three questions are rich opportunities. (Perplexity, see screenshot below for example)
• Summarize (for example) this email newsletter in an even more succinct fashion. (Comet, the AI browser from Perplexity)
• Out of this set of 1,000 updates from organizations in my business sector – which 10 should I highlight for the following email subscriber, and why? (Claude by API, followed by a mailmerge. See my green tech and sustainability newsletter, for example. Every subscriber gets their own personalized version.)

And I’ll sneak one more in: I often ask any of the AIs I’m working with what Azeem Azhar might say about a topic I’m thinking about. (I also ask about adrienne maree brown‘s POV.) Azeem has published so much online that all the AIs have a pretty good body of text to work with. And I really appreciate his… exponential view on things. Give it a try yourself!

Below: A slide I drafted based on the combinatorial analysis example below.

If you read a lot, and write down a lot, you can probably see (always just over the horizon) the potential power of AI to help unlock incredible value hiding inside our archive of notes.

At this point there are probably multiple tech solutions that are good enough from a tech perspective: Custom GPTs, Google Notebook LM, Notion, various startups. The remaining challenge is in human workflow.

I’ve been experimenting lately with a workflow and tech combination that is SO EXCITING to me that I wanted to write a blog post about it. And incidentally, when I work with organizations I always bring years of knowledge and experience to the table – but this feels like a big step up in how powerfully I’m able to do that.

Claude Projects + Obsidian + a Stopwatch

1. Each morning I start a timer for 5 minutes
2. Then I open Claude and go to a project called My Recent Notes. I click to add new content to the Project Knowledge section.
3. Then I open my note taking app of choice (it’s Obsidian) and I navigate to yesterday’s notes. Select all, copy, paste into Claude.
4. That takes 30 seconds, so now I spend the remaining 4:30 clicking the Random Note button in Obsidian and just bouncing around through years of notes archives I have, opening pages, select all, copy, paste into Claude.

Ta da! That’s it. After the first day or two, this was already my #1 favorite place to chat.

Is there a way to turn the whole markdown file of my years of Claude notes into one file I can upload into Claude? Put it all in Google Drive and let it get updated automatically? I don’t know. I’ve tried spending some time exploring options like that and honestly, I’d rather just spend 5 minutes a day re-visiting my notes – yesterday’s and random ones, and grow this “organically.” It’s already super useful.

A few tips for getting the most out of it:

1. Pro and con notes: I like just having normal chats there, after I edited the system instruction to say “please refer to specific notes wherever possible,” but I also really like asking two questions:
   • Which notes in this collection are most relevant to the following thesis?
   • Which notes in this collection contradict the following thesis? (this is a really good one)
2. One of several chats: Yesterday I had one tab open where I was asking my recent notes what they could contribute to a question I was wrestling with, but while that tab was thinking – I copied my prompt, opened up a second Claude tab not querying my Project and asked the same question there. Then a third tab to ask the same question of ChatGPT. In a quick minute, I had three distinct takes on my question. I quickly scanned over all three, picked out what I liked from each, and created an amalgamated answer to my question with pen and paper. And I love where we landed!
   

I’ve tried a lot of things over the years and I’ve talked to a lot of people who have wanted something like this. The above system so far is fast, cheap, and good enough to prove very exciting to me.

It gets me excited about note taking again too, which is exciting.

You might also like my friend Alexandra Samuel’s approach, which she wrote about this week in her newsletter edition Give AI the Knowledge it Needs.

Techmeme, November, 2016

I’m excited to say that after 5+ years working at Sprinklr, the market leader for customer experience management and social media marketing for the world’s biggest organizations, I have resigned from my job and I’m soon on to my next adventure!

I thought I’d take this time to share some of the things I learned from my experience there.  I hope that some of the lessons I learned and some of the experiments I succeeded with will be useful for you, my friends, to help advance the practice of continuous, life-long, social-web-enabled, professional development and to support your success in work.  Let’s share and make the network smarter!

My time at Sprinklr consisted of helping the company grow from $100M in annual revenue to nearly $500M, from 1K employees to 3K, and through an IPO. That was amazing. I held VP level responsibilities for analyst relations, influencer relations, competitive intelligence, data journalism, social publishing, the customer community, live chat customer care (all at once), and some really cool custom market research projects to advise some of the biggest companies in the world.  (Don’t take on too many responsibilities at once, that’s one thing I learned.)  And of course I spent some time working on the influencer marketing product, but not that much. It’s been rebuilt inside of Sprinklr and I used it myself right up to my last day on the job.  Thanks to the Sprinklr product team for that. (I’ll be ok without it; my therapist used to ask all the time, and I’ll be fine.)

In a few weeks, I’ll write about what I’m doing next. I have an awesome new volunteer side-project that’s very important to me and a new job I’ll be beginning soon, which is so amazingly well-suited for my long running interests that I am beside myself with excitement about the opportunity.

But first, want to hear about my experience for the last 5+ years at Sprinklr?  Quick context: You may or may not know that I started my career as a journalist, the first writer hired at TechCrunch back in 2006, then co-editor of NYT-syndicated ReadWriteWeb for much longer, then after six years as a journalist, a team and I productized my data journalism and influencer marketing practices in the form of a startup called Little Bird.   We sold it to Sprinklr in 2016. I’ve met so many inspiring people online and offline along the way, thank you. I’ve been a lot more heads-down over the past 5 years than I was the prior 10+ so I appreciate you still caring enough to read this.

Here are ten things I learned while at Sprinklr that I hope you’ll find useful.

Analyst Relations

While this was my responsibility, we won 6 straight Forrester & Gartner reports as a leader or the only leader in various markets, from content marketing to sales social engagement to the entire social suite category. (If you’re unfamiliar with those firms, they do a combined $5B in annual revenue from companies subscribing to their research and advice.) AR was always a team effort, of course, with as many as 20 or more teammates working for 3 to 6 months preparing to compete in each report. (Wow!) And working with an experienced AR leader like Drew Tambling on the team was one of the biggest keys to our success.

Analysts may be less accessible to many readers here than some of the other learnings I’ll share below, but I have set up a public Google Custom Search Engine anyone can use to search across the free published work of the 7 leading tech analyst firms. Don’t start a new strategic initiative without scanning the prior art analyzed there.  I use it almost daily.

Key learnings:

• Analysts have tons of great advice to share. There’s so much I want to remember that I learned from Forrester and Gartner over the last few years.  A few things that stick out:
  • (1) I loved Rick Parrish’s model of how to do something (anything) with discipline: he says you do it with
    • Rigor (following a documented practice),
    • Cadence (regularly scheduled activities),
    • Co-ordination (among people and other practices),
    • and Accountability (making sure there’s a senior person accountable for the work.)  You put those four qualities together and you’re doing work with discipline.How delightfully well-abstracted that is. What a great model!
  • (2) I loved Forrester’s advice that every change initiative can increase its odds of success if you understand that the first cohort of participants will include just a subset that are willing and able to put in the time to find success in the initiative; and then those people will be your case studies you use to market to the next cohort.  Forrester says successful change management initiatives often take five years to change a company’s culture and they’ve got tons of great tools for doing that work.
  • (3) And perhaps most of all, I loved Kristina LaRocca-Cerrone of Gartner’s model for democratizing data synthesis skills in organizations:
    • (a) make the implicit knowledge of your most-skilled people explicit, in well-documented toolsets
    • (b) tell stories of the most successful data synthesis practitioners scoring wins in their work, and
    • (c) map out the network of good synthesizers and their favorite sources of data, so that anyone can tap into those sources and the network.
• (4) The biggest value the analyst firms offer is not in their market leadership reports, but in their advisory services.  If your company has a subscription with one of these firms, you can schedule advisory and document reviews with them any time. The analysts are measured by how many advisory calls their customers sign up for, so they love it. And their knowledge of the industry, of best practices, of what b.s. smells like, and of customer needs is a great contribution to any strategy. The biggest, smartest companies in the world do inquiries with analyst firms all the time. When I was running AR at Sprinklr, we did more than 100 inquiry calls a year: we told everyone we could that this was an option – then we retold every happy story that resulted, to build interest in the next month’s calls. I’m really proud of that.

I will be forever grateful for the things I learned from Forrester and Gartner regarding maturity models, future-ready work skills, and so much more. What an amazing gift it was to get to lead the analyst relations team. Initially I said I didn’t want to do it; I’m glad I changed my mind.

Competitive Intelligence

Sprinklr’s competitive intelligence function, which I had the honor to be a leader in as well, was an incredible inspiration. Davin Galbraith, Elizabeth Closmore, and Asha Aravindakshan were other key leaders in that work. The breadth of their knowledge and the closeness of their collaboration with sales and product teams enabled us to win tens of millions of dollars every year in deals where competitive insights helped unseat incumbent software providers.  It was awesome.

My contributions to CI varied widely, but I’ll share two fun, simple little experiments I did that worked and I recommend to anyone else willing to do the work.

• (5) Watch YouTube subscription playlists of your competitive set; they are a simple but powerful way to learn about features and market positioning relatively early. I subscribed to 10 or 15 competitors, and I booked an hour each Friday to watch any videos they’d uploaded that week. Sometimes I was the first person to watch some of them, and I was then (as was my job) one of the most knowledgable people at the company regarding what our competitors were up to. I suspect in B2B this is an underutilized avenue for market intelligence.
• (6) Internet Archive comparisons of competitive product pages offered my team and I a great view into what new tactics a competitor was trying with a product now (things they hadn’t been doing 3 months ago), or what they tried a year ago that didn’t seem to work (so they removed it from their website.) Looking at the changes over time put me in a really good position to offer strategic advice on our own initiatives based on those market signals. (“Yeah, competitor X tried an idea a lot like that 2 years ago, but it didn’t seem to work for them so they took it off their website.”) I loved being able to see things like that.

Data analysis

I managed Sprinklr’s data analysis team for some time, which helps produce amazing industry reports for partners like Twitter, LinkedIn, Forbes, and more.

Two cool things I learned about data analysis that you might find useful:

• (7) Counting things is cool, but counting their percent change period-over-period is even cooler. I loved being able to say, for example, “when people on Reddit talk about your company, these are the 10 things say about you most often. You may not be surprised by the top 3, but let me flip this chart around and sort by which of these is rising the most month-over-month.  Turns out the 7th most-popular topic is rising very fast. That’s something you want to take a look at.“
• (8) Segmentation is magic.  My friend Justin Garrity used to say “at Sprinklr, we can tell you not only whether fans of the TV show The Walking Dead prefer eating popcorn or ice cream while they watch the show, but even more specifically, whether the ones who like ice cream like chocolate, vanilla, or Neapolitan ice cream the best!”  That’s cool, but the general principle is cooler: multi-layered boolean search queries are a non-intuitive and powerful way to learn about the dynamic constituent parts of any data set.

My favorite dashboards to build were ones that said “here are the top 10 things people talk about online when they talk about your brand, ranked first in sum total and second in percent change month over month.  Then for the top 3 topics, here are the top 10 sub-topics (eg when people talk about your toy brand, they talk about “learning” a lot, and when they do, that’s made up of conversation about mentorship, school, emotional intelligence, and more, in this ranked order), and here are some samples of the most-engaged content about learning and your brand over the last 90 days.” You can pull in a ton of useful intelligence that way and I loved when I could spend an afternoon using Sprinklr to do that.

But the general principle is universally available: multi-layered boolean search queries are a non-intuitive and powerful way to learn about the dynamic constituent parts of any data set.

For example, and this is just an example of the coolness of slicing data into parts to tell a story: did you know that despite its history-making industry leadership (it’s the fastest-growing social network in history), the tech press has only written about TikTok 1.2% as much as it has the rest of the FAANG companies? And when the tech press does write about TikTok, 68% of the time they’re writing about it in the context of privacy, China, kids, or Trump.  Much more often China (40% of coverage) or Trump (28%), less often privacy (23%) or children (21%).  That’s just a bunch of boolean search queries with AND and OR in them, searching inside a bounded set of data (the Techmeme archives).   But it’s cool. Make a few bar charts out of it and spend the ten minutes it took me to do those queries, write down those numbers, and do a little division…and you’ve got some interesting data to share.  The hard part is thinking to do it in the first place.

Influencer marketing

• (9) Big companies will finally listen to and learn from influencers. I am happy to say that a decade after I got into the influencer relations game, at least some companies are now willing to relate to industry influencers as more than just a marketing channel or PR crisis protection. That’s the base level of the maturity curve, that way of looking at it.  Social media influencers are market intelligence gold mines!

For example, I was really proud when one of the biggest, most famous tech companies in history turned, at the onset of COVID, to our technology to find the most credible influencers across many different topics and bring them into an internal conversation about how that company should strategize around pandemic disruption.  That’s the way to do it!  The people we call “influencers” are often people at the center of highly connected networks, with incredible visibility into what the market is doing and lots of lessons learned on their way to the top. Treating them like nothing more than a distribution channel is absurd, and thankfully no longer universal.

At Sprinklr, we’d do things like hire an influencer to do a three part project with us: a webinar on a well-distributed channel like AdWeek, an e-book of our shared thoughts on the topic of the webinar, and an internal advisory video call where anyone on our team could join in and privately ask this external influential thought leader their questions about the market.  It was awesome!  It was also a fun way to share access with junior team members to the industry leaders whose work they read and admire.

Not everyone looks at it this way, but I was proud to be named one of the world’s top 20 B2B influencer marketing pros in 2020 while flying this flag.

A great boss makes all the difference

The tenth lesson I learned from my time at Sprinklr is that it’s amazing to work for a great boss. Sprinklr’s Chief Experience Grad Conn taught me so much, and brought so much kindness to the hard drive through an IPO.

Grad prompted me to start the Sprinklr Coffee Club video podcast, which we did almost 100 episodes of, with truly amazing guests, from Rachel Happe on community to John Hagel on innovation and many more. Someday I want to just make a list of notes from the wise things the guests on that show said. There’s so much there!

I took tons of notes from things Grad said over the years, like:

• “every B2B sale is someone buying a chance of career success.”
• “People lean back when they see powerpoint, lean forward when they see white boards.”
• “You can improve the inputs of a measurement all the time, but you don’t change the outputs – you keep them consistent.”
• P&G’s three parts of a good recommendation: Why it’s strategically justified, why it’s proven, why it’s cost effective.
• Any data you show must have a recommendation to go with it.
• “Don’t trash the past, there was nothing wrong with the past, we’re just adding more stuff.”

That last one’s one of my favorites. And there was so much more.

All in all, when I look back at my time at Sprinklr, I like to use my favorite model for a debrief:

• What did you hope would happen?
• What actually happened?
• What does that gap suggest you should:
  • Do differently next time?
  • Keep on doing in the future?

And when I look back over the last five years at Sprinklr, I am satisfied.

Forward we go, together, internet friends.  I’ll let you know what I’m up to next in a few weeks.  I’m really excited about it.  Let’s connect as nodes on the networks of Twitter or LinkedIn if you want to stay in communication.  Thanks for your interest and support. Let’s do this internet thing together, for ourselves, each other, and where possible, for the rest of the planet.

One of the ways I try to get more done inside the time, space, and energy I do have is to try to spend 5 minutes doing a lot of things.  Can I do that thing in five minutes?  Could a five minute version of that thing be good enough?  Very often the answer is yes.

I also turn it around and imagine my future self saying to my present self, “you couldn’t even spend 5 minutes on that??”  I don’t want that to happen.

One of the most productive things I do almost every day is sit and think through a single topic for five minutes, usually with pen and paper.  I will also read a book for 5 minutes if that’s all I can do.

You know the GTD advice that if something can be done in 2 minutes, then you should do it right away? I think this is a related concept.

And that’s five minutes of blogging on that.

David Gurteen talks about truncated “Knowledge Cafes” with five minute talks.  That reminds me that I learned how much could be done in five minutes when I was in high school and won many speech and debate tournaments in Impromptu Speaking.  In that event, you’d be given three philosophical quotes, pick one, take 30 seconds to prep, and then give a 5 minute speech about it.  I would apply the perspectives of 3 different interesting thinkers or other people in history to the quote I’d picked, analyzing it from 3 different perspectives.  That was probably where I learned too about Symphonic Thinking, Daniel Pink’s term for the ability to generate connections between seemingly disconnected things.

And that’s five more minutes.  Cheating? Maybe.  Now if you’ll excuse me, I’m off to spend 5 minutes thinking through an important life matter.

When I read Dan Pink’s book A Whole New Mind and learned about what he calls Symphonic Thinking, or the ability to find connections between seemingly disparate entities, as a key thinking pattern for the future of work, I thought “wow, that’s what I’ve been doing already! I’m going to do it more deliberately!”  And so I regularly cite research, reading, things I’ve heard on podcasts and more in my day job and my work outside of work.  It’s one of my superpowers, but I really believe it’s something far more people could help the world with. I recently changed my Twitter bio to read: “Sharing thoughts for growth-oriented people about how information can be synthesized to build power to make the world a better place.”

My notes come from a wide variety of sources, but most commonly from things I’ve stopped and typed up into Roam Research after I’ve heard them read aloud to me either by Pocket, which I feed with links from Twitter using an IFTT applet that sends the links in any tweets I favorite to pocket, as well as a few key RSS feeds. I also read a lot of PDFs by text to speech using hte Voice Aloud PDF to speech iOS app on my phone. I “read” with my ears and clean my kitchen a lot, or jog. I’ve also been experimenting lately with spending 5 minutes scanning through Feedly RSS reader to find things to toss into Pocket and listen to read aloud.

So I read a lot (I also miss a lot, it’s ok) and then I stop when I hear something really good and I write it down in Roam. (Or if I’m jogging, I associate each thing I want to remember with one of my limbs, then I go through them one at a time “left arm, left leg…” when I’m done running and I write them down.)

These are some of the things that came to mind when my friend asked about my note taking and review system.

• Make it easy to take notes when you can. The Roam unofficial mobile interface has been essential for me.
• Failure to cite your sources can be a real pain – finding an easy and repeatable way to cite where a note came from can make a big difference. I have notes from years ago where the insight is good but I didn’t record the source and it’s a real bummer.
• Make it easy to review your notes, Anki flashcards are super helpful. Anki tells me I’ve been adding the equivalent of one card per day to my “lessons being learned” deck since late 2015.
• Make it easy to recall half-remembered flashcards, Roam’s search or my personal wiki control-F have been really helpful. I search in Anki sometimes too.  I regularly have a hazy memory of something but search can bring it up in the background while I’m on a call for work.
• Review as much as you can, as often as you can. It’s just like an athlete practicing. I try to spend 10 or 15 minutes on my flashcards each day. I wish I spent more time, I’d love to double that. Or more.  That’s something I’m actively working on right now.  You can see my scorecard there on the right. Lots of room for improvement, but that’s better than a poke in the eye. If I could consistently review 20 flashcards a day and really integrate the acquired wisdom with my life…that would be amazing.
• As I review the flashcards, I try to think about a real life scenario I could apply that concept to. That makes it far more real and stick in my mind.
• After each review session, there’s often one flashcard in particular that I really dig into. I might spend 5 minutes writing about it. I might just think about it while going about my day.

Those are some of the things I’ve been doing for the past few years. I’d love to hear anyone else’s tips and tricks you use as well. Ultimately, I think a lot of it is just about showing up. Being imperfect, coming back to the path, and applying what you’ve learned and reviewed in the real world.

Below, some examples of 3 of my most recently added flashcards.  These ones Anki is going to show me again in a couple of days, but in time it will space them out over years.  Good luck to you in your studies and their application!

Data apprentice sought.

I’m going to try an experiment, but I can’t do it alone. I believe this is a chance to have a horizon-expanding experience that makes a meaningful impact on climate change.  Maybe this is of interest to you – or maybe you know someone it would be a good fit for.

Goal: to help increase the capacity & impact of people working on climate change by building, sharing, and teaching how to use a collection of online research tools for ongoing learning and topic tracking. I believe that access to great streams of knowledge can help people make a bigger impact on the world. We’re going to build and share some streams regarding climate work.

What I’m looking for:

You:

• Want to make an impact on climate change
• Can do 5-10 hours of work per week, for the next 3 months. Update: Originally I said this was unpaid, but I’m going to find a way to offer some payment for help with this. I got some good feedback that more people would be available to help if this wasn’t unpaid work. Let’s talk about it.
• Want to expand your exposure to what people around the world are doing about climate change now
• Want to learn how to use leading-edge systems for online research by helping assemble them for others
• Love to learn how to do new things
• Feel comfortable making judgement calls on the quality of information sources
• Can help with organizing an online workshop

Work includes:

• Source discovery: Validate, clean up, and expand lists of the best sources of information (blogs, news sites, Twitter accounts) regarding greenhouse gas emission reduction, using a combination of automated tools, existing research practices, your creativity, and patience
• Information organization: Organize those sources of information inside of tools to maximize their usefulness (RSS feeds, Google Custom Search, Twitter Lists)
• Story capture: help build a collection of short stories of successful projects that made a big impact on greenhouse gas emissions reduction.
• Event planning: Assist with planning, promotion, and production of a series of 3 weekend workshops introducing people to the climate knowledge tools we create and showing how to use them. (I’ll lead the workshops but I need your help making them happen.)

About Me:

• I’m a longtime, self-educated, professional online researcher
• I used to be a NYTimes-syndicated journalist. The tools we’ll be building together are rooted in my journalism experience.
• I have also been an investor-backed startup founder, political organizer, tofu manufacturer, and convenience store clerk. Today I am a VP at the world’s leading software provider for customer experience management and social media listening.
• I have become a good manager and mentor. It was hard.
• I have a strong commitment to social justice, including and beyond climate issues.
• I love my day job and don’t have much time outside it. That’s why I need your help.

When: Starting ASAP, target date for first workshop is early January, second in early February. There’s no time like the present! Let’s get started!

How:

• How we’ll collaborate: Outside of 8:00-5:00 PST (before and after my work day), we’ll use chat, video calls, and project management by spreadsheet
• How to get in contact with me: Please email me at marshall@marshallk.com with the subject line: climate research volunteer. Tell me about yourself and your interest in the project.

I look forward to hearing from you!

Here are 10 things I read, watched, or listened to this week that I found so valuable I wanted to share them.  I cut out the political ones, this time.

Tech

• Humans in the Loop collective intelligence (Video) “Superminds: The Surprising Power of People and Computers Thinking Together with MIT’s Thomas Malone“

This 45 minute talk suggests that we move from the AI concept of “humans in the loop” to a paradigm of humans working together, augmented by machines, or “computers in the group.”

• Roam Research raises a round of funding, at a $200 million valuation. Roam has already changed the lives of so many of its users, including mine. It’s not only where I do all my digital note taking, it also facilitates entirely new thoughts every time I allow it to. No wonder investors were able to support its ongoing development at such a dramatically high price.

• Sprinklr raises $200M on $2.7B valuation four years after last investment

Woop woop, that’s where I work! I’m having a great time and am excited about the future. This got lots of press, but the TechCrunch post was particularly good.

Foresight & Strategy

• How Futurists Cope With Uncertainty: A simple tool you can use to see plausible future states early

Futurist Amy Webb offers multiple tools for foresight on her company’s home page. This “Axes of Uncertainty” is a simple and powerful one.

• OODAcast: Michael Kanaan, Author of T-Minus AI Discusses Artificial Intelligence and Global Power

Great conversation about AI but I’m putting it in Foresight because one of the strongest points is that AI’s pattern recognition powers makes it particularly well suited to the Observe and Orient stages of the OODA loop, supporting humans as they take responsibility for the Decide and Act stages.

Climate

• OPML of Green Energy Sources (there’s a download link in this Tweet about it)

If you know how to import an OPML file into an RSS feed reader, here is an algorithmically created collection of the top sources on green energy that others in the green energy field pay attention to. I built it on Sunday because I’m really trying to dig into climate matters.  You might also like this Twitter List of 1K peer-validated climate change thought leaders.. There are almost 10K people following it!

If you don’t know how to import an OPML file into an RSS reader, you’re really missing out. My wife often teases me that I told her about RSS on our first date, and now 17 years later we’re very happily married!

• Renewables Beat Fossils on Europe’s Grid: The Energy Gang (Podcast)

Guess what % of the world’s new energy production capacity installed last year was from renewable energy? Guess what % of global energy used is now from renewable? Great informed discussion here. Happily, the answers to those questions are 80 and 27. I was surprised by both of those.

• Dr. CHAD HANSON on the Myths & Misinformation of Wildland Fires

Even people who find this podcast annoying agree it’s chock full of some very good information and some reason for optimism.

• Healing with Fire (Cultural Burning).

6 minute interview with two indigenous people about the use of fire. I’ve watched this and shared it many times. I encourage you to watch it too.

• Window Swap

Beautiful. Tired of the view out your window? Try someone else’s. Not tired of the view out your window? You may appreciate this even more, then.

(Above: the first Sprinklr Smart Alert hit I ever got was a good one. I took action on it; I amplified some good news and congratulated a business partner on an innovation of theirs I would have missed without this alert.)

I believe Alerts of various types are going to grow all the more important in the coming years – and I think we should talk about our expectations for them.

A lot of people get frustrated when they get a non-actionable alert. That’s the price of a good alert, I believe. Any good alert system will weed out 99.9% of potential events, send the .1% of events it thinks you may want to take action on. But you may only find that 50%, 30%, 10% or less are in fact actionable. Depending on how you’ve trained the system. Any way you do it, there’s more work to be done.

An Alert never tells a whole story, it only suggests where there me be a story to find. I love some alerts that are “false alarms” (non-actionable) the vast majority of times they sound. Because I’m willing to sift through noise to find quiet signals.

Furthermore, alerts are great for delivering news of an anomaly and maybe a little context – but the whole story is going to require manual skilled discovery of context, testing of a thesis, and will require decisions to be made.

That’s because almost no full set of circumstances for everything that could be actionable can be described by mortal humans ahead of time. Any Alert that doesn’t surface Unknown Unknowns is something else, something very narrow.

Below: this is not how or where I work.

What changes do we want to make coming out of the Covid-19 pandemic?  I want to really learn to lead in a more whole heartedly, full-throatedly, networked fashion.   I’m inspired by my online friend Simon Terry, who incidentally mentioned that Sartre quote to me the other day, to not only think but speak in those terms. Simon is the leader of a group called Change Agents World Wide.  It’s a network of people, subtitled “Changing work, one human at a time.”

There’s lots of discussion about how Covid-19 will change us.  I’m intrigued by some of the discussion about how it will accelerate best practices we’d been slower to adopt than we knew we should – like decarbonization and climate change efforts.  (Here’s one big link on that, from McKinsey.)

One specific example I find intriguing is the developer relations community started by boutique firm Redmonk called Flyless, described here. It’s an online community for software developers flying less, or not at all, because they still want to talk without going to conferences – and maybe flying less is going to be a good idea in the long term.  Starting that community is awesome.

I’d like to think about what we want to change, how we can help each other make those changes, how we can hold each other to high standards, “create a container” for changes, and point ourselves in the general direction we want to move in once we’re coming out of this thing.

It’s tempting to think that a centralized authority will be the determining factor, or that a “great man” will determine the direction of history, or that it’s so much bigger than us we have no control over it – but has there ever been a time when it was more clear that we’re all connected, for better and for worse?  What do we want to do about it?

I’ve worked at Sprinklr for more than 3 years now and it just keeps getting better. And by that I mean I just keep learning more every day. And we’re making it a better place to work almost every day.

The team I manage has an average score of 9 out of 10, so they’re not as happy as I am yet – but they’re pretty darned happy too.

I’d like to invite you to be a part of our team, if the following job description sounds like a good fit for you. When will I be filling this position? I’m not entirely sure, but soon.

If you’re interested, please email me at Marshall.kirkpatrick@sprinklr.com with the subject line “influencer marketing position.” I expect between 20 and 50 people to email me about it, but we’ll see! I’ll try to respond to everyone personally. I look forward to hearing from and/or meeting you!

Help wanted:

INFLUENCER RELATIONS MANAGER

We’re hiring a smart, communicative, B2B Influencer Relations Manager responsible for the development, execution and measurement of influencer marketing and collaboration campaigns used to drive both customer acquisition through demand generation and sales support, and internal learning from influencers who can contribute knowledge and insights to internal stakeholders throughout the business. This position works with cross-functional teams, especially Content Marketing, Events, and Analyst Relations. The position will be based in either Portland, Oregon or New York, (remote? Maybe…) reporting into the VP, Marketing.

About Sprinklr

Sprinklr’s mission is to enable every organization on the planet to make their customers happier. We do this with the world’s #1 social suite, which helps enterprises deliver memorable customer experiences with an integrated suite of Market Research, Customer Care, Social Media Management, and Social Advertising. Headquartered in New York City with 1,300 employees in 22 offices, Sprinklr works with more than 1,500 of the world’s most valuable brands, including: Allstate, McDonald’s, Lenovo, Microsoft, Nike, Signify, Procter & Gamble, Samsung, Santander, SAP, Shell, Verizon, and Visa. Sprinklr’s partners include Accenture, Deloitte, IBM, Microsoft, and SAP. For more information, visit sprinklr.com or follow us at @sprinklr.

Primary Responsibilities of This Position

Help scale execution of influencer collaboration programs, ranging from weekly video and audio podcasts to influencer collaboration on blog posts, webinars, events, and more

Collaborate closely with VP of Marketing to build effective, smart campaigns, balancing demand generation with long-term relationship building and maintenance, learning, and integrity

Configure and use customer experience software (Sprinklr) to monitor for influencer-derived insights and opportunities

Collaborate with internal teams focused on content generation, advertising, events, and more.

Solve problems and generate business value.

Minimum Qualification

3+ years marketing experience executing marketing programs

Demonstrable intellectual curiosity

A growth mindset

Better-than-average written and verbal communication skills

Could this be you? If so, send me an email! Do you know someone who could be a great fit? Pass this along to them!

I’m not a football fan, but I love data analysis, and this session was a lot of fun.  I think there’s a lot here that can be a source of inspiration for work in just about any sector, especially work that involves data.

* Each player has an individual game plan for each game (I didn’t realize that but of course it makes sense.  When I put my work to-do list on my calendar, that makes me feel a little like I’ve got an individual game plan in support of my team’s plan.)
* LA Rams analytics team has 3 people: a forecaster, a data architect, and a front end developer for internal systems.
* Whether it’s today or the 90’s before there were analytics teams, there have always been people looking at data, looking at probabilities, and trying to help teams make good decisions
* When you see players who are successful, you look to see if you can discover any new traits they have. Then you can look to find other people who have those traits as well but who may have missed other benchmarks and thus not been discovered.
* One person can’t do analysis of all the data available, but if the work is documented and reproducible, then you can come back later and repeat it, or pick it up again to iterate with new data and knowledge. As long as you’re iterating in your analysis, that’s good.
* These analysts are working with R, Python, SQL databases, and spreadsheets are often the final product that’s sent to someone
* You’re not going to be 100% correct in your forecasts, in fact your failure rate is going to be very high – and you just have to get used to that
* Much of the analytics are used for tracking player workload for optimization (makes me think about capacity management in an information worker’s worklife)
* The NFL is using data to try to make fans smarter, so they can hang out with their friends and say “you should look out for this when the game is being played.”  When you put the names of receivers and who’s covering them up on the screen, people love that. (cool validation of this as a commercially viable value add)
* For QBs air yards is a key stat. Everything these days is a quick, controlled game. We’re asking QBs to throw shorter passes and they should have about 60% pass completion rate
* Data science is a great place for people from diverse backgrounds to showcase your abilities by analyzing public data and find new perspectives. You can showcase your abilities, get attention for it, demonstrate, show your work, share your code
* Communication is super important. As an analytics person, you should be able to translate your work to anyone who could use it. That’s just as important as the ability to do the work itself.  (I’m pretty sure it was Namita Nandakumar who said that.)
* People think stats are going to tell you something dramatically different than what you think – but they often don’t. They often tell you something smaller, like who on your team has the potential to play a larger role.
* You can support people moving toward more statistical thinking in an incremental fashion: show one success first, then move toward more grey areas
* Having discipline in this job is key because there are so many interesting things you could be analyzing, you must constantly assess and reassess projects

Those were my notes, I hope you find them useful as well!

You may follow bloggers on Twitter or email, but I find it useful to subscribe by RSS for an interface dedicated to long articles. I do that through Feedly and lately through Pocket, via IFTTT, in order to get the articles read to me aloud on my phone when I’m in transit. (My new favorite is The Living Library, about data and society.)

There’s a four part “growth mentality” model I’m going to use here to talk about the benefits of subscription, but you might appreciate using the model itself for other things as well.

What are the benefits you could capture by growing in this way? I’m motivated to subscribe to blogs for one reason in particular: they are a powerful way to be exposed to thoughtful perspectives on matters that may be useful to me later. I regularly get to cite something at work that’s really useful and that I read on a blog. I high five myself in my mind when I do. Regular reading of high quality longer form sources is a fast track to building out the mental toolbox.

If I could really nail regular reading of my subscriptions, I think I could add a lot of powerful timely knowledge to what I have to offer at work.

What’s something else I’ve succeeded at that’s inspiringly similar in challenges and opportunities? I have totally succeeded at adding both daily work logging and daily personal journaling, after deciding I wanted to years ago and struggled for a bit. So I’m confident I could add regular reading of my subscriptions too. I have, but this is the second question in the model – and I could get all the better at reading my subscriptions, too.

Who is someone else I’ve seen successfully grow in a similar way? My wife has added some practices to her intellectual life that I find pretty inspiring.

What would I say in a letter to a friend advising them how to grow in this way? I’d advise anyone to find an interface that works well for you, to refactor and clean up your subscriptions regularly, to not worry about unread items, and to consider a relationship with your items that is optimized for quality over quantity. One article considered deeply and connected to other matters in an actionable way may be worth 10 articles or more quickly scanned and all-but-forgotten. Finally, I’d recommend using the BJ Fogg method of building new habits: keep it small, tie it to an established anchor habit, and celebrate each time you do it to train your brain with positive reinforcement.

There you go! Now I’m going to take action on this. Next thing will be to try to figure out how to write blog posts regularly again, using the same growth model as well.

There are strategies and tools that you can use to tap thoughtfully into the abundance of knowledge being published online without being overwhelmed. One tactic I have added to my practice lately has been the following method of having every new post on a few important blogs read to me aloud. This is something I’ve mentioned to several people, casually, and they’ve told me I should write a blog post about how to do it.

I do this for the blog of the company I work for (Sprinklr). And for other companies and organizations I find so inspiring I want to try to read everything they post too. I just subscribed to Stefaan Verhulst’s excellent new Living Library this way. There are a variety of sources I want to keep good track of.

The newest way I’ve been doing it is by using the mobile app Pocket and its wonderful text-to-speech continuous play audio feature. Bookmark an article to Pocket and it will read the article aloud while you clean your kitchen or walk your dog. The voice is a touch robotic but I’ve gotten used to it.

I put things into Pocket in many different ways, but using the tool If This, Then That, you can put any new blog post into Pocket from a specific source.

Here’s the process in a one minute video, written out below.

1. Create an account on IFTTT.
2. Create an account on Pocket.
3. Create a new “applet” and select “RSS” (really simple syndication, the primary form of automated feed that blogs publish their articles to)
4. Grab the feed for the blog or website you want to subscribe to. You may need to view the source in your browser and look for the feed in the code. This is not hard to do. It’s ok, you can do it.
5. Plug that feed URL into IFTT
6. Then, select Pocket as the next service to activate. When there’s a new article in the RSS feed for the blog, then send that link to Pocket.
7. You’ll be prompted to connect your Pocket account and your IFTTT account. Once that’s done, you can create your RSS-to-Pocket applet and then it will be run automatically every day.

Now you can load up Pocket on your phone (see screenshot below), click on the headphones icon, and it will read aloud all the articles you’ve bookmarked and all the blog posts that have come in through IFTTT.

It’s a pretty great way to regularly keep up with a blog or organization that’s important to you.

There’s sure to be an innovation dividend, too. It’s not hard to imagine this expanding across the biggest supply chain in the world, and then to jump into more firms even beyond the other places it’s currently being tested.

Bloomberg: “IBM is working on food traceability with 10 other companies, including Dole Food Co., Unilever NV and Driscollâ€s Inc., a berry supplier. The computer giant holds a leading 32 percent share of the $700 million-plus market for blockchain products and services, WinterGreen Research Inc. said in January, and has 1,500 working in the field.”

Let’s see CSR on the blockchain

This sounds like a great start but I sure would like to see the immutable ledger paradigm put into networks like these supply chains and used to track:

• Climate impact

• Worker respect

Just that! Verified by 3rd parties, I’m sure, but with that verification certified by said blockchain.

Help slow down climate apocalypse and use blockchain to prove that your whole team is doing it. I’ll buy more if you do, and I know I’m not alone.

I’ve previewed and reserved On Grand Strategy though and that’s one I wouldn’t have paid for – it’s too far outside my core interests. I learned something really big from it: the importance of thinking in terms of strategic sequences. That’s something that’s easier said than done but hugely important and much easier to do when you think about it consciously.

Because we all paid taxes to fund the public library, and because ebooks are so easy to quickly check out from home, the diversity of ideas that I’m being exposed to is substantially increased relative to the books I’d be willing and able to buy in hard copy. If that’s true even for me, I can only imagine how true it might be for other people less apt to invest in exposure to diverse perspectives.

I’m thinking about this just after leaving a community swimming pool, where for a few dollars people of all kinds of backgrounds have come to be in the water. It’s far more diverse that my workplace, than the natural foods grocery store I shop at, or the last restaurant I ate at.

Collective creation of free and low-cost resources is a powerful way to expand and enrich people’s experiences and perspectives. If we as a society choose corporate alternatives to these collective institutions, optimized for profit and efficiency instead of for public accessibility, it will be a great loss. Let’s make sure to support and appreciate those public institutions.

Here’s a conversation going on between some of the most influential thinkers in the world today about how business is changing.

Consider this question with two things in mind: buying committees and non-linear “customer journeys,” where prospective customers don’t just avoid straight lines, they don’t event spend most of their time thinking about a company with that company.  They spend most of their time talking about or reading about that company with other people entirely.

Gartner says that only 20-30% of IT investments have a *direct* business impact. The other 70-80% have an *indirect* impact – and that’s often where the *biggest* impact is made.

Superior strategy, since at least the days of the Roman empire, takes into account strategic sequences of events, not simply single cause-and-effect moves on the chessboard.

(Below, a great Gartner graphic via Bob Apollo via Gartner’s Hank Barnes.)

Nexus causality is a concept that says almost everything is caused not by one single thing, but by a whole nexus of contributing factors, many of which may be necessary but not sufficient.  This is hard for the human mind to comprehend, so we tend to look for a single factor to attribute all causality to.  The factor we feel like we might have the most control over – often feels like the convenient one to point to.

Asking whether something will have a direct and immediate business impact is not the right question.  Asking whether something is a strong leading indicator of success, whether there’s high or increasingly high correlation between a thing and success, those are better questions.  Asking whether a thing can provide substantial competitive differentiation, and then basic competence can take care of the last mile, that’s an interesting question.

Here’s what I think could be a good way to explain the change going on in the economy and world.

“In the dynamic between mind and machine, product and platform, core and crowd – the latter of each has grown so much stronger that the relationship between each of these pairs must be re-examined…The business world is always changing but in transitions as profound as this one, things are even more unsettled than usual.”

That’s from the book Machine, Platform, Crowd: Harnessing Our Digital Future, by Andrew McAfee and Erik Brynjolfsson.  It’s a good book.

I think this also offers a good model for self-examination.  How much are you relying on your own mind – and how much are you leveraging the power of the machines you have access to?  I know I think of a lot of ideas, but observing the output of technologies offers a whole new level of insight into what I’m working on.   I get pretty excited about the product of my labor, but the true power is increasingly from the networks, the platforms, and if I’m not keeping my eye there, on the opportunities and the consequences, then I may be missing the lion’s share of what’s available.  For example, I work a lot with Twitter data on a product, but I’ve got to mind the value emerging out on the network of Twitter users and conversations.  The products I use help me gather that value.  And of course the core of any company these days is remiss if it doesn’t pay attention to, and tap into, the crowd it aims to do business in.

I’m going to try using this historic shift toward the power of machine, platform, and crowd as a way to talk about digital transformation.