Online Skill-Building Sessions that Don’t Suck

You’ve probably found Presentation 101 training isn’t enough when you’re crafting online interactive experiences with partners, colleagues and clients.

We built Mach49 initially to support intense, face-to-face teaming. You all know the basics of effective team activities: clear agenda, define goals, blah blah blah. However as we shift interactions online into focused 1-2 hour sessions, I’ve noted four success principles that weren’t obvious at first…


Attendees engage much better if they can choose their areas of focus. Rather than a canned exercise, it’s best to (a) provide multiple topic areas for attendees to select, and (b) allow groups to self-assemble around topic areas.


Looming deadlines are energizing! Exercise teams working remotely need clear (and near) deadlines to deliver output, and must understand exactly what result is expected. A digital timeclock is a big help.


Each team should expect to present their output to the entire group. No one wants to look like an unprepared donkey in front of the full audience, even on a screen.


Competition is helpful. Teams should understand that they’ll benefit if they provide great output. Figure out a motivating award. Examples are prizes, seed funding, and recognition from senior leadership.

You’ll need these trick to keep your audience engaged in the activities. Remember…ATTENTION IS THE SCARCEST RESOURCE IN 21st CENTURY BUSINESS.

Do you have a fifth principle to add? Something you’ve discovered since your world changed in early March? Let me know.

Foundational Technologies versus Disruptive Applications

Most of us are more interested in the business and social implications of exponentially advancing technology, rather than in the wonky details of the actual tech. With everyone braying about tech breakthroughs every day, how can you interpret what you hear? I’ve written about one lens to help you understand emerging technology – see my piece on Three Horizons – and here’s another framework I find useful.

I now realize I spent many years confusing Foundational Technologies with Disruptive Applications. Here’s an example: When NetScape created their first browser in 1994, I remember everyone talking breathlessly about TCP/IP, the fundamental protocol for internet communication. I failed to understand that TCP/IP was a Foundational Technology, poised to change the way we all live and work with a myriad of online experiences, whereas the NetScape Mosaic browser was one among many Disruptive Applications of TCP/IP.

Let’s have a look at some key distinctions:

Foundational Technologies…. Disruptive Applications….
Create new foundations for our economic, political and social systems.Usually begin in the commercial world, attacking a traditional business model with a lower-cost solution and overtaking incumbent firms quickly. 
Appear abstract and theoretical; Require background in science or technology to understand.Are communicated with a simple and clear business value proposition.
Take decades to seep into our business infrastructure.Emerge over years, never require decades.
Are adopted steadily and gradually. Disrupt existing industries with targeted, rapidly-growing ventures
Enable novel, complex systems.Enable transformative applications.

Here are a few examples:

We can count on government labs and large corporate R&D facilities to continue pumping out the basic research leading to Foundational Technologies. When it comes to Disruptive Applications, though, my money is on (1) startup entrepreneurs, and (2) big-companies intrapreneurs who are given the latitude to create bold new ventures. For example, global giant Schneider Electric recognized the incredible advance of renewable energy as a broad Foundational Technology. We worked with a small, nimble team from Schneider to build eIQ Mobility, a Disruptive Application for charging fleets of electric vehicles.

The next time you hear a breathless description of an emerging technology, try categorize it as a Foundational Technology, a Disruptive Application, or something in between. And, as always, talk to me. I’d like to know if you find this distinction helps you think about the unruly world of technology.

Groundhog Day

Feeling sorry for yourself after a week of Shelter In Place? No whining, please. The astronauts NASA plans to send to Mars will be sheltering in place for nine months in a cramped metal tube. Let’s see what we can learn from NASA’s plans.

NASA is just beginning to grapple with the emotional impact of long journeys through deep space. Often we can look to science fiction for inspiration, but we’ll get no help in this case. Science fiction writers use two tricks to skate around the thorny issue of long, long journeys through space:

Warp Drive: A convenient plot device for avoiding endless travel time

Hypersleep: The second sci-fi trick to cheat time

You may have heard about the physiological challenges of travel in deep space: Bone demineralization, radiation exposure, eyesight degradation. Barring the invention of a warp coil, astronauts transiting to Mars will face a slew of psychological challenges as well. Cramped, long-duration space travel could lead to fatigue, anxiety, decreased brain functioning….even psychotic breakdown.

How can NASA mission planners address some of the psychological risks of deep-space missions, long before we set out for Mars? For challenges like these, I always recommend finding analogous experiences to help find direction. Let’s see what we can learn from astronauts orbiting Earth on the International Space Station, as well as roughly analogous endeavors such as submarine missions or exploration of the poles.

Meaningful Work

Cultural anthropologist Jack Stuster pored over journals written by astronauts on the International Space Station. What made life difficult for the astronauts? The majority of frustrations came from workflow issues that are probably quite familiar to you: Insufficient time to complete tasks, poorly written instructions, conflicting leadership demands.

Stuster’s recommendations to NASA for maintaining emotional equilibrium during long space voyages will also sound familiar to you. Examples: Allow the astronauts to control their schedules if possible, design tasks to have tangible benefits, and distribute tedious work across all crew members. One interesting tidbit from his research: There’s evidence that the act of journaling was helpful, in and of itself.

Astronaut Sunita Williams keeping her journal (courtesy NASA)

Effective Leadership

When I asked my good friend Commander Noel Gonzalez to share with NASA his experience while undersea for months as Captain of the Navy submarine USS Cheyenne, he pointed immediately to leadership as key to maintaining morale (and sanity) of his crew. Beyond basic leadership strategies such as clear communication and effective delegation, Noel prides himself on his sensitivity to the intangibles on board his submarine: Mood, energy, tone.

From a very different vantage point, Organizational Psychologist Lacy Schmidt agrees. While studying the team climate at Antarctic Research Stations, she points to quality of leadership as a key influencer of group behavioral health. In particular, Schmidt highlights the importance of interpersonal interactions to influence others’ perceptions. Faced with the desolate environment of Antarctica (and, by extension, Mars) she states that “the objective characteristics of an extreme environment are less important than subjective perceptions of the environment in relation to performance“.

It’s incumbent on any leader to maintain the team’s morale, and it will be essential for future leaders of Mars missions to look after the crew’s emotional well-being en route to the red planet. I hope they’ll take leadership advice from submariners and antarctic explorers. Fostering teamwork and solidarity are critical to reduce conflicts and stress.

Antarctic research stations are a decent analog for Mars

Communications with Earth

In Jack Stuster’s review of astronaut journals, he found that communication with family and friends back on Earth was a welcome relief from the monotony of the space station environment, the lack of social variation, and the limited privacy. No surprise there, but here’s an interesting implication: Social connection, even with a long time delay, will help astronauts combat the third-quarter phenomenon which is consistent across all the missions I’ve mentioned. Whether you’re cooped up in a submarine or wintering over in Antarctica, there is a decline in performance during the third quarter of missions in isolated, confined, and extreme environments, regardless of actual mission duration.

And speaking of maintaining long-distance connections with family and friends…As long as we’re all sheltering in place, think about taking a cue from the astronauts. Set up video cocktail hours and video dance parties with your friends and family. We’re planning our second virtual cocktail party tonight, complete with online games.

VR-Enhanced Training and Entertainment

While underway to Mars, astronauts may leave the ship to enter an artificial environment using virtual reality headsets. You can imagine VR’s contribution to training. Astronauts have time to practice Mars surface operations while on the nine-month journey. Imagine maintaining certain high priority skills, like piloting the Space Exploration Vehicle across the Martian terrain. VR gear could also make it easier for astronauts to learn new skills such as geological investigations, or even how to conduct astronomical observations between Earth and Mars.

And if astronauts are bringing along VR gear for enhanced training, you can bet a holodeck application will be thrown in for some entertainment. Sign me up.

Talk to me….

I hope you’re inspired by NASA’s plans to visit Mars. Humans are built to explore, and Humanity’s aspirations to explore space will drive us toward unprecedented technological innovations that will undoubtedly benefit mankind in one way or another.

Talk to me. Inspiring? Thrilling? Wasteful? Gratuitous? As always, I welcome all comments. We all advance our thinking and ourselves through open-mindedness, humility, and tolerance for other points of view.

Heartland + Tech

The Bookings Institution argues that unbalanced growth in tech has contributed to a terrible political divide in our country that will only get worse.

The authors make a convincing case that the heartland needs growth centers to drive economic inclusion and socioeconomic mobility. Right now the mix is terrible: Top innovation metro areas in the US — Boston, San Francisco, San Jose, Seattle, and San Diego — accounted for more than 90% of the nation’s innovation-sector growth during the years 2005 to 2017.

My perspective: Keep the faith! Leaders like Carter Williams of iSelect Fund in St Louis are already demonstrating big successes in bringing innovation to the heartland.

Have a look at this short article and get back to me with your thoughts….

The case for growth centers: How to spread tech innovation across America


There’s a lot to like about living in Silicon Valley, working in emerging tech, and engaging with brilliant thinkers at places like Stanford. I’m lucky enough to live the global intellectual nexus of technology and entrepreneurship. But…(and you knew there was a “but” coming) I’m choking on the sheer number of “strategic technology frameworks” getting churned out, and I have a bad feeling that most were created by academics who have never created an innovative product or built a new venture.

There are a few frameworks I do find incredibly useful as I go about my day job, helping “intrapreneurs” create tech-enabled new ventures for big companies. Let me share one, and please weigh in with your favorites. Look for a few more in future posts.

No Borders – Only Horizons

Kudos to Baghai, Coley, and White for publishing their Horizon framework in 2000, in ‘The Alchemy of Growth’. By creating a taxonomy of three horizons, they gave corporate execs a practical way to think about technology and make intelligent decisions about strategy and execution for tech innovation programs. Here are the three horizons that help decision-makers to deliver on tech-enabled challenges:

  • Horizon 1: Extend Core Technologies, 1-2 years
    • Companies use existing tech to improve their business models and maximize their value and effectiveness in the short-term.
    • Big companies love Horizon 1, because they’re structured to deliver on core competencies and embrace incremental change.
  • Horizon 2: Develop New Opportunities, 2-5 years
    • Organizations invest in emerging technology to generate substantial value in the future, often around disruptive opportunities.
    • These programs extend a company’s business model and its core capabilities to entirely new customers, new markets, or both.
  • Horizon 3: Create Viable Future Visions, 5-10 years
    • Research programs and academic collaboration lead to the creation of entirely new capabilities and new businesses.
    • This is the realm of R&D labs in large organizations, and spooky organizations like DARPA.

So, why should you care about this? Because nearly all companies do a crappy job on Horizon 2, and tech-enabled Horizon 2 opportunities are key to your company’s survival. Have you noticed that certain initiatives in your organization, like implementing AI for predictive maintenance or adding IoT to your industrial processes, are always 2-4 years away, year after year? That’s because Horizon 2 programs defy corporate innovation processes and remain stubbornly out of reach for most organizations.

What processes work for successful Horizon 2 programs? I’ve been at this for 30 years and I’ve only seen one successful strategy for Horizon 2 programs: Create autonomous teams of entrepreneurial people, get them the hell out of the office, and lift corporate governance. In short, take a page from disruptive startups. None of these steps is easy, but Mach49 and other incubators area seeing remarkable results. In my career, external incubations are the first consistent path I’ve seen for huge organizations to create disruptive new ventures.

It’s been a pleasure to watch RWE, the massive German energy company, beat the odds and propel Horizon 2 initiatives forward through incubation. The leadership knew they could not keep pace with the market using internal processes, so they selected an entrepreneurially-minded employee, Sukhjinder Singh, to lead internal startup Thanks to Sukhjinder’s boundless energy and drive, Pear is embracing AI-enabled chatbots and natural language processing to extract value from energy data. RWE delivered a Horizon 2 program in record time, and had they employed their internal innovation methods, the new business would have been delivered…never.

Talk to me. Which tech innovation frameworks are helpful for you? I’ll share two more in future posts.

Credits and thank you to Baghai, Coley, and White for publishing their Horizon framework in 2000, in ‘The Alchemy of Growth

Tesla: straight-up vertical

Tesla Factory, Courtesy Agium

When my son brought home some fraternity brothers to our place in Mountain View this summer, they got away from the Peninsula and spent their time just where you’d expect: San Francisco, Oakland, and Santa Cruz. However I got some mileage by recommending the Tesla Factory Tour in Fremont.

One quick observation to share with you, after taking a tram through the second largest building in the world, 5.5 million square feet of frenetic robots working on a hellacious number of vehicles.

Tesla is incredibly proud of its heritage…

Tesla takes great pride in building on a legacy of older automotive infrastructure. The building was purchased from NUMMI, a joint venture between Toyota and General Motors, and they’re proud to upgrade it and keep it in operation. Our adorable tour guide swelled with pride as she told us how a massive stamping press was purchased from a truck manufacturer.

…but Tesla takes no pride in partnering.

We learned on the tour that Tesla builds damn near all the ingredients that go into their vehicles. Our guide talked about fabricating everything from seat fabrics to electrical connectors. Telsa’s approach is completely distinct from the car manufacturers I work with, who focus on drivetrain and assembly process.

On the tour, they made it clear that they had to integrate vertically because of their “first principles” approach: No one else had the required parts, systems, and services Tesla needed. Going the supplier route made no sense. Well, maybe. I think we’re seeing an uncompromising culture that prefers to build rather than buy.

We’ll see how Tesla manages its scale over the next few years. They’re done a remarkable job designing the “machine that creates the machine”, and the factory itself is a remarkable product. If Tesla can integrate value as competently as it integrates manufacturing, there will be no stopping them.

Have you taken the tour? I’d love to hear your observations.

Tesla factory, courtesy Wikipedia

Flying Taxis? I’m (slowly) turning into a believer

A recent Churchill Club event reminded me that EVTOLs (Electric Vertical Take-Off and Landing) vehicles continue to make progress here at a blistering pace, compared to other players in aviation. Startups like Kitty Hawk and Joby Aviation, as well as large firms like Airbus, are making impressive strides towards commercialization. I fully expect testing to be well underway by the early 2020s.

Joby Aviation is busy developing an air taxi

Flying electric vehicles are at an exciting inflection point I’ve seen again and again in the tech industry: The point Steven Johnson calls “The Adjacent Possible”. In Johnson’s awesome book (well worth your time), Where Good Ideas Come From: The Natural History of Innovation, he explains that most innovations are not sudden flashes of inspiration. “Adjacent Possible” innovations come from the combination of what’s already available (“spare parts”) in new and remarkable ways. Looks to me as thought we’re ready to watch a whole new EVTOL industry emerge from the marriage of what’s already available, like advanced lightweight materials, cutting-edge sensors, digital signal processors, and AI software.

Listening to the heavyweights speak about air taxis at the Churchill Club, three themes cut across all the perspectives. The “big three” challenges for EVTOL on everyone’s mind, in order of priority, are:

  • Safety, including security
  • Noise
  • Economics


Manufacturers make a pretty convincing case that EVTOL systems can be made safe if they are redundant from tip to tail. Everyone took pains to describe redundant, independant, parallel subsystems. For example, at the front end, multiple independent lift fans protect from motor failure or a bird strike. There are 2-4 independent controllers stuffed into these aircraft, wired in parallel. And it’s a really bad day if the vehicle loses power, so the battery system is divided into four separate sections for redundancy.

Security, particularly cybersecurity, is an issue with all autonomous vehicles. I’m glad they’re talking about it now. The best mitigation is for safety-critical systems in EVTOLs to be isolated from non-critical components and independent of connectivity to external networks.

Elroy Air’s delivery drone in flight

Noise Abatement

The industry needs to work more on this one and they know it. Reducing tip speed is the favored approach with larger, slower blades, but they’re doomed if the noise of EVTOLs drives everyone crazy. Some genius needs to come up with a disruptive solution like digital sound cancellation or soundproofing.


Autonomy is critical to providing an economically viable passenger experience. Even the most enthusiastic boosters of air taxis acknowledged that the cost of a pilot destroys the business viability. Autonomy means no pilot expense plus an available second seat, and at that point, the numbers start to look promising. Uber has done some careful financial work and they argue that air taxis could be comparable in cost to ground transportation once we see decent scale. If all this is interesting to you and you want to read one additional document, I highly recommend the Uber Elevate Whitepaper.

In the short term, autonomous systems will prove especially valuable for freight transport and delivery. I’m looking forward to seeing some of these players – Elroy, Joby, Kitty Hawk, Bell – get moving with freight transport in remote areas as a baby step to greatness.

What makes EVTOL hard?

Everyone agreed on this one: batteries. Storage tech is improving, energy density currently 250 watt-hours / kg, but still no where near the energy density of hydrocarbons. Many of the air taxi players talked about the need to design the aircraft around the batteries, cramming every bit of available space with chemical storage. They also pointed out that as we see larger and larger energy densities, explosion or fire risk increases.

What makes EVTOL easy?

I hadn’t thought about this, but compared to autonomous cars, there’s a much lower “obstacle density”. No curbs, no pedestrians, no stop signs. And the vehicles can all operate at different elevations depending on route. However, manufacturers mentioned that there’s also less data for the machine-learning systems, compared to the mountains of data gathered by autonomous cars.

Other Thoughts…

Ford and GM are “sitting ducks” to be disrupted by a company like Waymo. Similarly, the EVTOL entrepreneurs make a convincing case that Boeing and Airbus are sitting ducks for startups like Joby Aviation.

A great deal of existing work can be applied. From the autonomous vehicle industry, for example, it’s  possible to siphon off goodies such as V2V communication technologies, hardware tech like LIDAR, and machine-vision software stacks. Advances in materials science applied to larger aircraft, like carbon-fiber frames, can easily be applied to small EVTOLs.

Can EVTOLs be another “leapfrog” for developing countries? Might developing countries leapfrog over conventional transit infrastructure, like subways and freeways, and go straight to flying vehicles? I sure wouldn’t mind flying over the traffic nightmares in Mumbai. (I’ll wave.)

Talk to me. Are we on the cusp of something big, or have I been taken on a flight of fancy by wild-eyed futurists? As always, I’d love to hear from you.

Joby Air Taxi

Update from 10 June 2019: About a week after I finished this post, The Verge published a piece on giant cargo drones highlighting many of the same players. The Verge pointed out:

Amazon announced plans to drop packages at customers’ doorsAlphabet’s Wing got FAA approval to make deliveries in the US, and UPS said it was testing its own tech by delivering medical supplies to hospitals in Northern Virginia. But there are concerns about safety and how the Federal Aviation Administration will regulate them.

What you should think about when you think about 3D printing

Don’t just think about 3D printers for plastic and metal. Think about 3D prototyping of absolutely everything.

When I started my career, 3D printers were curiosities for engineers. We’d stare at the tiny printhead as it spat out layers of plastic to transform a digital file into a flimsy 3D object. In the 90’s we watched the cheapest 3D printers plummet from $18,000 to $300 in 10 years, even as they became 100 times faster. Staples began selling 3D printers a few years back and we knew the industry had changed:

Colido 3D printer, $310 at staples

You can even find a 3D printer on the International Space Station courtesy of Made in Space. That said, we’re still talking about a wonky line of business.

If you want to stay on top of the real action, look beyond 3D printers to quieter, but equally important, developments in rapid prototyping:

  • Living tissue has been 3D printed at Scripps and a few other labs. Printed meat, anyone? Cartilage has already been printed successfully, and labs in China are working on ears…and livers!
  • Last year, a San Francisco startup 3D printed an entire house (except the windows) for $10,000. When Eindhoven faced a shortages of bricklayers, they brought in a 3D house printer, essentially a huge robotic arm with a nozzle that squirts out a specially formulated cement, building the home layer-by-layer.

How do you think this will affect your business? Let me know. These changes will touch all of us.

Don’t think about 3D prototyping replacing high-volume manufacturing methods. Think about it completely reinventing your relationship with your customer.

Get used to it: The last word in new product introduction is no longer in the hands of manufacturers. Increasingly, the final say belongs to your customers.

We’re ten years into this trend in smartphones, which are really general-purpose computing platforms whose behavior can be completely customized with app downloads. My phone looks and behaves nothing like the phones of my millennial kids. In fact I should stop saying “phone” about a device that I almost never talk into anymore. It’s a piano metronome, a flashlight, and a home security display.

Even the Tesla is starting to feel less like a car and more like a general-purpose, customizable platform, with over-the-air downloads tweaking climate controls, enabling new dashcam functions, and eventually enabling a full self-driving system. (Let’s leave that one for a future newsletter.) Detroit carmakers love to make fun of Musk, but they’re flocking to Silicon Valley to research connected vehicles and over-the-air software downloads.

What about smaller consumer goods? Will clothing companies need to redefine their customer relationships? You bet. You can design your own trench coat with Burburry Bespoke and create your own shoes on Milk&Honey. Modular components let customers feel that they are designing their own products — and we’re headed beyond modules into a fully custom, printable future.

Belts, garments, shoes, food, toys…every industry will cede the final word on products to its customers. Get ready. I’d like to hear how you’re preparing for the next wave of additive and generative design.

Venturing into Artificial Intelligence

As we incubate new lines of business for large organizations, many of the new ventures are enabled by AI. German energy giant RWE, for example, created SF-based, a virtual energy assistant with a clever AI chatbot named Sam. While some companies embrace AI into their core processes products, many prefer to make their first venture into AI through small incubations.

There’s a good reason everyone is rushing to embrace AI. Everything in my experience tells me AI and Machine Learning are fundamental technologies ready to spawn hundreds of disruptive applications and rip up existing business and social fabrics. The state of the technology reminds me of TC/PIP, the fundamental technology of the internet, in the late 80s. Netscape was right down the block from me in Mountain View and we could tell they were poised to tear things up.

Enough gushing. The flip side of our love affair with AI is that organizations jump into the relationship ill-prepared and results can be an expensive disappointment. There’s a good reason these technologies are prominent in the latest Gartner Hype Cycle.

I’ve helped organizations roll out new AI ventures over for the last four years and I have kept my eyes open for patterns of success. People jump into these programs not realizing that AI and ML require some specific program management methods. Below are three domains I’d watch closely if I were you.

One: Program Management Still Matters

My first piece of advice is short and seems obvious, but it’s damned important and often overlooked. Working with breathtaking new technology does not exempt you from basic program management hygiene. Review your notes from that Program Management Bootcamp your boss forced you into, and make sure the PM basics are in place on your AI program: Does your team have a clear objective with defined division of responsibilities? Does everyone understand how to delegate? Are paths of communication clear? Get a top-notch program or product manager in place before you go crazy with that new machine learning platform you just licensed.

Two: Structuring Your AI Program

Choosing Your Internal Tech Lead: Most large companies partner with external tech providers to deliver AI-enabled ventures. That’s a fine way to go since your core competence is probably not data science, but you’ll need an internal tech lead to interact with your external partner and your internal team. I’ve noticed that the best tech leads are very good at these two activities:

  • Provide a necessary level of domain expertise in data science to review proposals and manage external partners (but do not need deep, deep expertise in the field)
  • Act as teacher and translator for the internal team, presenting the implications of data science in business terms

“Make sure the people reviewing proposals understand the technology behind AI.”

-Maura Sullivan, COO Fathom5 (security analytics)


Lay Down the Vocabulary: Don’t silo your tech lead. When you’re starting up, make sure everyone on your team – including your board or steering committee – understands the basic terms you’ll be throwing around. Leave the deep expertise to the experts, but get a few sentences deep on the terminology. At the bottom you’ll find my AI Glossary, and I nag on everyone to learn the terms at the outset of the project. Without the shared vocabulary your team will never communicate meaningfully.

As you define your AI program, think first about existing scenarios in your business that can be enhanced through the technology. Artificial Intelligence is best employed to augment, not replace human efforts. For example, when Citrine uses AI to hasten the development of new materials, they’re augmenting, not replacing, the critical role of a materials scientist. If you’re new to AI, my advice is to assess your existing processes and consider applying data analytics as an “overlay” to improve these processes.

On their first try with AI, I’ve seen newcomers pull off the best results when they search for low-risk, high-reward improvements in efficiency. Predictive maintenance is a classic example. Even if your maintenance model is only 90% correct you’ll see huge benefits.

“Reading glasses don’t replace our eyes.  They help our eyes work better than they would naturally.  In the same way, AI can help humans leverage and extend their natural cognitive ability.”

-Ken Ford, Director, Institute of Human & Machine Cognition


“Complex systems have more problems than there are people to solve them. AI can help.”

-Greg Mulholland, CEO, Citrine Informatics


Three: What’s Unique about Managing AI Programs?

Beyond the basic “program management hygiene” I mentioned earlier in point number one, what makes an AI program different from any of your other programs? I’d keep four things in mind if I were you….

Your specific challenge, not your choice of vendor, dictates the correct AI model. Don’t let vendors push you into a particular approach. It may be the only approach they offer. First of all, establish the answer to a simple question: Do you even need AI? Some deterministic challenges are served by conventional statistics rather than AI. Make sure your tech lead has the background to guide the team to the right partner.

“Trying to use the wrong analytic technique will net you the wrong answer most of the time.”

-Maura Sullivan, COO Fathom5 (security analytics)


Structure your AI program as a series of agile experiments, not a monolithic award. Don’t fall into the traditional large-enterprise trap of specifying an exhaustive program. Take a page from the Agile playbook and create a series of sprints — your AI partners will actually prefer to work this way with you, as you can see from the quotes below.

Remember that you’ll need stored data to kick off the first sprints in your program (more on this shortly). Identify disclosable small bits of data from sources you trust, or create synthetic data. Remember that sanitizing data will take time.

If possible, put your data in a separate network, and create a pilot program or hackathon rather than a program of record. Steer clear of your heavy corporate IT guidelines during your early stages of learning.

“Encourage small-budget ‘bake-offs’ to experiment with different approaches. Follow the X PRIZE model.”

-Sam Septembre, FireEye


“Rather than asking partners to submit a 100 page proposal, bring teams in to compete on real-time challenges to see how they work.”

-Angela Zutavern, Data Scientist, Booz Allen Hamilton


Next up is an area I’ve seen go wrong many times: Budget plenty of time for data engineering prior to data science. Data engineering is as much of a problem as data science, but it is often overlooked. Make sure your data engineers go through the process of collecting data, storing it, batch processing or real-time processing it, and serving it via an API to data scientists who can easily query it. Take Muddu’s quote below seriously – he’s among the most respected names in AI.

 “It takes 4 data engineers for every 1 data scientist.”

-Muddu Sudhakar, AI Entrepreneur, Investor, CEO


“It’s hard to get clean data. We had to scrub the data and this stole time from analysis. It would be nice if there was one repository for data with consistent file format and cleanliness.”

-Scientist, Frontier Development Lab, NASA


Recently I spoke to an incredibly brainy group of data scientists from NASA’s Frontier Development Lab. They had just won an award for their use of machine learning to predict harmful solar eruptions that might knock out communications, avionics, even national security. When asked what they would change next time, they asked for…yes, you guessed right…better data engineering.

Thanks for hanging with me to the end of this. One last point….

Consider long-term staffing and maintenance of your AI system. Everyone expects significant initial investment, but many data science users are dismayed by the “technical debt” of IT overhead for ongoing support. Think about how your system will grow and evolve over time and understand that costs can race up as you maintain and upgrade your system.

“Machine learning is the high-interest credit card of technical debt.”

-Peter Norvig, Director of Research, Google


“The more opaque the automation, the more manpower is needed to interface with it.”

-Ken Ford, Director, Institute of Human & Machine Cognition


(Appendix) A few definitions

If you’ve made it this far, I expect replies quibbling with my definitions, but remember the key point here: Without the shared vocabulary your stakeholders will never communicate meaningfully with the core team. So get everyone on your team a few sentences deep in vocabulary.

Data Science: the extraction of knowledge or insights from data in various forms, either structured or unstructured.

Artificial Intelligence (AI): systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

Machine Learning: a type of AI that provides computers with the ability to learn without being explicitly programmed. 

Deep learning : a subset of machine learning that has networks capable of learning from data that is unstructured or unlabeled. Also known as Deep Neural Learning or Deep Neural Network.

Data Engineering : the process of collecting data, storing it, batch processing or real-time processing it, and serving it via an API to data scientists who can easily query it.

Deterministic Model: a model where the output is fully determined by the parameter values and the initial conditions. 

Stochastic Model: a model that possess some inherent randomness. The same set of parameter values and initial conditions will lead to an ensemble of different outputs.


When you’re starting up, make sure everyone on your team – including your board or steering committee – understands the basic terms you’ll be throwing around. Start with these seven, they’re not that bad….

Data Science 

The extraction of knowledge or insights from data in various forms, either structured or unstructured.

Artificial Intelligence (AI) 

Systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

Machine Learning 

A type of AI that provides computers with the ability to learn without being explicitly programmed.

Deep learning 

A subset of machine learning that has networks capable of learning from data that is unstructured or unlabeled. Also known as Deep Neural Learning or Deep Neural Network.

Data Engineering 

The process of collecting data, storing it, batch processing or real-time processing it, and serving it via an API to data scientists who can easily query it.

Deterministic Model 

A model where the output is fully determined by the parameter values and the initial conditions.

Stochastic Model 

A model that possess some inherent randomness. The same set of parameter values and initial conditions will lead to an ensemble of different outputs.

Letter from Saudi Arabia

Skater culture in the Kingdom of Saudi Arabia

The mission of the U.S. Department of State is to promote security and democracy for the U.S. and the international community. Major concerns are freedom of speech and religion, human rights, and rule of law. How in the world can the U.S. State Department advance its agenda in a country that forbids women to drive and represses all forms of public religious expression other than one school of Sunni Islam?

After a week here, I can tell you one thing we absolutely shouldn’t do: Scold and harangue the Saudis on human rights.  Well-intentioned programs to import speakers on issues such as religious pluralism are an irritant to the proud Saudi culture.

The Saudi consulate – an incredibly impressive and committed team – had a clever thought about advancing its agenda. What if we bring speakers to Saudi Arabia to discuss 21st century methods of doing business? Methods and tools like design thinking have implicit messages of pluralism, like the benefits of diverse perspectives on design projects, but we avoid overt lecturing. I had the honor of being selected for the diplomatic tour, based on past successes with the State Department and on recent successes from mach49, the venture incubator and accelerator I run with my partners in Redwood City.

That’s how I found myself in Damman and Dharan, hosting a forum of entrepreneurs, meeting with business leaders, touring middle schools, and eating Halal food in quiet restaurants (music is forbidden in public venues).


Before I tell you about the trip, bear with me while we cover some terribly important numbers. State-owned oil company Saudi Aramco is Saudi Arabia’s economy, and the government shocked the business world with plans sell off a chunk of its crown jewel. A profitable IPO is intended to create a sovereign wealth fund that will generate enough investment income at home and abroad to dominate state revenue by 2030. The valuation and performance of Aramco will have a huge impact on Middle Eastern stability and on global business, and it will quantify the investment community’s attitude towards the future of fossil fuel, so this is a development we all need to watch.

What’s Aramco worth?

Deputy Crown Prince Mohammed bin Salman estimates Aramco’s worth at $2 trillion, based on 261 barrels of reserves (crude oil in the ground) and the standard benchmark for valuing oil reserves at $8/barrel. In addition, Aramco recently saw an income tax cut from 85% to 50% to make it a more attractive investment.

Here’s the biggest issue with Mr. bin Salman’s estimate:  He is assuming prices are viable for the next 73 years at current pumping rates. Will global warming and alternative energy technology curb the world’s appetite for hydrocarbons by the year 2210? I’m sure of it.

State-owned oil companies are rarely valued as dispassionately as the number suggest because of political risk, either real or perceived. Two examples:

  • Russia’s Rosneft OAO pumps 5 million barrels per day, half of Aramco’s output, and is valued at $35B.
  • Brazil’s Petroleo Brasileiro SA is worth $23B even though it controls every facet of Brazil’s oil industry.

EFG Hermes, an investment bank serving the Middle East and North Africa, predicted the market would value Aramco at between $1 trillion and $1.5 trillion. Even at the lower end, bringing 5% of the company public would deliver $50B in investment funds and debt service.

And finally…Credible economists and analysts (not short-selling trolls) are valuing Aramco substantially below $1T. Energy consultancy Wood Mackenzie has valued Aramco’s core business at around US$400 billion.

Over the next two years, Aramco’s valuation will tell us how the world feels about the future of hydrocarbon and the risks of investing in Saudi Arabia. Investor confidence leading to a fat $2T valuation will fast-track diversification, improve the transparency of a murky organization, and bolster the King’s political capital. If investors are lukewarm, the Kingdom’s $100B economic diversification project would be unable to move forward as planned, and the Saudi economy will remain tied to a commodity that is on the wrong side of history.


How was my week traipsing through Saudi Arabia? As you might expect, much more confusing and nuanced than expected. Saudi Arabia is an impossible labyrinth of contradictions, held together by the endless flow of oil money.  Here are some of the experiences that still make my Western head hurt…

Holding forth on innovation in Dammam

Expat Attitudes

Before I arrived I had already invented  the answer here. The western expats I met would be troubled by country which, for example, forbids movie theaters and beheads men for civil disobedience. They’d have funny, sarcastic stories, and darker stories about oppression they’d witnessed.

Not so fast. I’m not trying to minimize the egregious human-rights violations in Saudi Arabia, but plenty of westerners enjoy living in the Kingdom, and not just for high pay. A fun, lively twentysomething Australian woman  told me without hesitation: “I love it here. Saudi Arabia has soul.” She’d like to stay indefinitely. And a manager in an industrial park, recently relocated from hipster Oakland, told me that he had already made deep friendships with his Saudi coworkers and appreciated their warmth and openness.

Public Sector

More impossible numbers here to make you dizzy:

  • There are 20 million Saudis and 10 million guest workers in the country
  • Of the 20 million Saudis, 70% work for the government. Oil brings in the majority of government revenue.
  • 90% of the private sector jobs – the people who cleaned my hotel room and cooked my food – are staffed by non-Saudi guest workers.
  • And the 20,000 royal family member see monthly stipends anywhere from $8K to $250K.

How is this possible? What keeps the engine running? Those government jobs have short working hours, generous benefits and substantial vacation time. And the Saudi citizens pay no income or sales tax. The answer, of course, is ten million barrels per day powering the economy.

The Art of the Workaround

One Saudi national called his culture “the art of the workaround”. The Shura is an extremist and powerful council of clerics which proposes laws and forwards them to the King. Yet within the campus of Saudi Aramco, the rules are magically lifted. Women may drive and restaurants are coed. And Bahrain is a short drive from where I stayed, with its bars and clubs.


The Saudis are grappling with the economic challenges of finding employment for a young and growing population and diversifying an economy that is overly concentrated in the energy sector. Culturally, government jobs are encouraged, and entrepreneurship is questioned. Maybe my contacts represent a tiny fraction of the total population, but the entrepreneurs at the Entrepreneurship Diwaniya at Dhahran Techno Valley were as astute as the hottest teams in Silicon Valley.

Again, I’m not devaluing the significant issues in Saudi government and culture. I am pointing out the contradictions to popular opinion: When I visited the Bayan Gardens School, focusing on STEM education for girls, the science fair presentations rivaled the quality of any primary or secondary education, anywhere in the world.

Finally, here’s a shout-out to my incredible contacts at the consulate: Peter Winter was the driving force behind my visit, and Khatijah Corey handled every challenge with aplomb. And best wishes to our capable Consul General Mike Hankey from the embassy.



Update from Dave: February 2018

I wrote this post just over a year ago, and I now wonder if, not when, Saudi Arabia will pull the trigger on the biggest IPO in the history of global business.

The Riyadh government appears to be waiting for the futures price for a barrel of oil, one or two years out, to bump up at least $10 to  $70 per barrel. I wonder if a short-term rally will spur U.S. shale production, driving down oil prices and reducing the Saudi market share.

Longer term, as I watch the rapid growth of renewables and the rise of electric vehicles,  I ask myself if we’re past “peak oil”, particularly in view of new commitments by some nations to cut greenhouse gas emissions. If extraction of petroleum is already in a terminal decline, that’s an even bigger story than an Aramco IPO.

As always, I look forward to hearing your thoughts.



Update from Dave: October 2018

Saudi Crown Prince Mohammed bin Salman again asserted a $2T valuation for Aramco. I admire his reform efforts, but it’s an uphill struggle push any organization into a globally-scrutinized IPO when it’s known for favoritism, nepotism and backroom deals. In addition, taxes were reduced from 85% to 50% to make the Aramco investment more attractive, causing major disruptions to government revenues in a kingdom with massive social welfare spending. All that said, Saudi leadership’s credibility depends on a successful IPO. They surely know that time is not on their side and that the public markets are increasingly cautious about long long bets in the hydrocarbons economy. The world is looking for a bold move, not indefinite promises.



Update from Dave: December 2019

Three years after I weighed in on the Aramco Valuation and shared serious doubts about a $2T valuation. Investors are weighing in and you might think I need to eat crow (and I’ve sure been wrong before). After all, wealthy Gulf allies are buying into a $1.7T valuation, with the majority of investment coming from Saudi companies and funds. That’s damn close to the $2T valuation asserted by MBS a few years ago.

Was I wrong? Not so fast. The bigger story here is the muted response from the international investors, compared to other major IPOs in emerging markets. Why aren’t global investors putting in big orders? We hear the usual diagnoses: Worries about the security of Aramco’s oil facilities, and concerns about murky reporting. I think we may be seeing something much bigger: A referendum from global markets on the potential of renewables to push petroleum extraction into a steady, terminal decline. Sure, Aramco’s reserves are good for 90 years at current rates of production…but global markets may be losing confidence in hydrocarbons as a long play.  

As always, I’d like to hear from you. Weigh in, please. Aramco: Hot or Not?



Update from Dave: August 2020

Four years after I questioned the valuation of Aramco, the markets have voted in their valuation the world’s largest oil company compared to the world’s biggest, forward-facing tech companies:

Apple: $1.9T

Saudi Aramco: $1.8

Alphabet: $1T

Any opinions out there? I believe we’re seeing a referendum from global markets on the potential of renewables to push petroleum extraction into a steady, terminal decline..and also a referendum on the long-term potential of companies owning the digital ecosystems for payments, entertainment or advertising. This is not a trend that is reversible through promotions or repositioning. It’s a historic shift.

Let’s all watch Saudi Aramco shift its focus from oil to industry. We’re already seeing big moves into the Vision Fund and Lucid. Watch for even more dramatic moves in the near future.