Thanks for visiting! Here’s a quick intro if you’re new here.

FutureBlind is devoted to covering four general topics: business, investing, tech, and design. It was initially launched in 2007. Here’s some examples of areas I’ll cover:

  • Technology — in particular frontier tech like AI, Space, Bioengineering, etc.
  • Progress — how we can make faster progress, in particular how we can tell better stories that drive progress
  • Business & Investing — mental models about startups, investing, and business analysis
  • Design — how to design better experiences and how new tools drive better design

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Subscribers will get a roundup of posts and other things I find interesting about every quarter. I’ll also do the occasional post as a podcast episode.

Featured posts to get started with:

Roundup #5: The AI Epoch

Hello again! These are my latest thoughts on the areas I’m interested in. I hope you’ll enjoy learning more.

In this roundup:

  • 🤖 A.I.
    • Essay: Thoughts on the AI epoch — An idea maze for LLMs; Punctuated Equilibrium; The AI revolution; Where’s the moat?; The fate of Google.
    • My thoughts on AI (as a podcast!)
    • The BuffettBot Experiment
  • 🚀 Space — 4 photos and a link to summarize 2022.
  • 🔗 Interesting Links — Other takes on AI; Derek Thompson essays; and Choosing Good Quests.

🤖 A.I.

Continue reading “Roundup #5: The AI Epoch”

The New AI Epoch

What more can be said about the AI boom that began its ascent less than a year ago? A lot! The potential of AI is immense and its influence on our lives is sure to be significant. And so I’ll continue. . .

In this essay I’ll focus more on Large Language Models (LLMs), but my thoughts apply to all other AI efforts as well.

An easy way to think of it is that LLMs will soon become the “autocomplete for everything”:

What’s common to all of these visions is something we call the “sandwich” workflow. This is a three-step process. First, a human has a creative impulse, and gives the AI a prompt. The AI then generates a menu of options. The human then chooses an option, edits it, and adds any touches they like.

. . . So that’s our prediction for the near-term future of generative AI – not something that replaces humans, but something that gives them superpowers. A proverbial bicycle for the mind. Adjusting to those new superpowers will be a long, difficult trial-and-error process for both workers and companies, but as with the advent of machine tools and robots and word processors, we suspect that the final outcome will be better for most human workers than what currently exists.

There seems to be an unlimited number of areas that language prompting + completion will enable. Some are obvious: a new iteration of Google, help with writing, content generation, help with marketing copy, etc. You see many startups and tools that have already sprung up to tackle these.

Some of the real interesting applications that are incubating now will have action models as a big component. Models will have the ability to take actions like: searching the web; ordering an item; making a reservation; using a calculator; or using any other digital tool that humans are capable of using. Imagine ChatGPT being able to confirm its answers with multiple sources, or having access to all your personal records it can use to assist you.

Prompt engineers are already discovering how much you can do with the existing models, without any new advancements or manipulation of the actual base model. Even if GPT-4 or an open-source LLM from Stability.ai take years to come out, the existing tools are enough for huge changes.

An idea maze for LLMs

The above is an idea maze I sketched out for products enabled by LLMs. The key question it starts with is “What kind of interface would the use have with the product?”

Continue reading “The New AI Epoch”

Creating Creator

The following is a short case study on “Creator”, a cloud-based content management system I built at Mashgin, where we make visual self-checkout kiosks that use computer vision to see items so you don’t have to scan barcodes.

In the years since launch, it has given location managers the ability to customize their menus in ways they were unable to in the past. This empowers them to make frequent changes, tailoring the menu to customer needs rather than just “using the default”.

Mashgin Creator is a tool for operators to build and manage their menus, from items to discounts, schedules, and more.

Mashgin customers have been able to easily edit their checkout items in the cloud since we first launched in 2016. But when we began to design our mobile and in-person ordering app, we realized customers would need an easy way to design more complex menus, with custom item options, photos, nested categories, scheduling, and more. This is where the idea for Creator came in.

Creator is what they call in the industry a “CMS”, or content management system. Any software tool used to manage content of any type could apply.

In the food service industry, a CMS is used to manage their menu items, pricing, discounts, taxes, etc. The scope could be anywhere from an individual cafe to a nationwide chain of stores.

Most existing CMS software for food service was cumbersome to use and poorly designed. It was really just a simple layer on top of a database, allowing users to edit basic item information. Some software didn’t even allow for real-time syncing of data — any changes are “submitted” and someone behind the scenes has to deploy them to the menu.

The output of these menus is very simple: it’s just items in some nested menus, each with its own data like price, type, options, etc. But the work and consideration that has to go into building each menu is anything but simple.

It was clear that our customers needed something much better.

Designing the app

Believing that all the existing tools weren’t very good, we chose not to base the core design off of any other examples or prior work. Creator would be rethought from the ground up based on the needs and jobs of its users.

Continue reading “Creating Creator”

Hiring Memo (2017)

I wrote the following memo 5 years ago (November 2017) immediately after Mashgin raised its Series A. It summarized my thoughts and learnings on hiring at the time. I also added a few updated comments as I read over it 5 years later (all of my 2022 comments are [bracketed] and italicized). Hopefully others find it useful!

Interviewing is actually not very helpful. Or at the very least it is extremely difficult to judge how someone will perform with just interviews, especially when unstructured. (See here, or all the data Google collected.)


  • People interviewing usually have relatively little experience, and thus have a poor “base rate” to judge the candidate against.
  • Answers to questions generally have very little correlation with actual performance.
  • It’s difficult to extract enough information (even in long interview processes) to make a proper call. Imagine going on a 3-hour date, thinking it over for a few days, then asking the person to get married.

So what are other ways to know if someone will be good?

  • You’re friends with them or have worked with them already.
  • Pointed reference checks from trusted people.
  • “Trial” side project or task requiring interaction with team. Getting as close as possible to a real working environment.
  • Recruiter who is both (1) very familiar with your needs/culture, and (2) specialized in hiring for that role.

But short of these things interviews are still necessary. Regardless of the specific process, it is important to have a set plan and follow it for every candidate.

Some advice:

  • Prepare: don’t go into an interview cold. Know what you want to get out of them and have a clear plan for how to evaluate them.
  • Let them do the talking. You should only guide them and push them. Ask follow ups: Why? What did you do about it? How come?
  • Brain teasers don’t work, and aren’t indicative of anything.
  • The most effective questions are situational rather than just having them recall the past. “Instead of asking candidates to describe how they handled a unique situation in a previous job or organization, it’s more fruitful to describe consistent situations that candidates could face in this job or organization, and ask them what they would do — or how they would reason.
  • Encourage them to ask questions — about your questions, you, or the company.
  • Be transparent and open about your entire hiring process.
  • Get away from your desk or room: Take them out, take a tour of offices, etc.

The main things you’re trying to get are:

  • Excitement test. Would hiring this person make you more excited to work at the company?
  • What can they do now, and how quickly could they be productive?
  • How is this person going to be performing in 1 year from now?
    • How long does it take for them to learn something new?
    • What’s their growth mindset and can they continually get better?
  • Will they work well with the team?
  • How long are they willing to keep pushing on a good project until giving up?
  • How hard is it for them to change their mind or adjust course?
  • Do they do the right thing even when they don’t have to?

Aside from specific skills, what traits are the best indicators of these?

  • Integrity: not just honesty, but integrity with themselves, their ideas, and “doing the right thing” when necessary. They seek out truth and embrace failure.
  • Social intelligence: works well with others and is empathetic/caring.
  • Intelligence
    • Raw intelligence
    • Creativity in problem solving
    • Adaptability
    • [One of the best ways I found to test for this is to ask about something they really enjoyed working on. Then grill them with questions about it, diving as deep as possible into the details.]
  • Drive: is self motivated and can push themselves to get things done, even if it’s not enjoyable work (grit). More internally motivated than externally.
  • [Curiosity: This could be part of intelligence or drive, but it needs to be tested for somehow. I liked to ask questions like “What things are interested in outside of work?” or even better “Pick a topic that’s not part of your day job (hobby, book, subject) and take a few minutes to explain it.”]

Warren Buffett: “In looking for someone to hire, you look for three qualities: integrity, intelligence and energy. Without the first the other two will kill you.

There’s also a problem with hiring the “best” — they are either extremely expensive or have unlimited options so will want to work elsewhere. This is like the Moneyball problem in baseball: the best teams will have the best reputation and most resources to get the best players. But these players aren’t necessarily the only best — they are just the ones who look really good based on the most obvious metrics.

So what do you do? Look for talent in places with low competition, that require more work, or who are too “different”:

  • Growth potential — people who are young or with little experience in the area, but are smart, driven, and internally motivated. You want people at the start of their “performance curve” — in the 80th percentile that can move up to the 97th over time. [I think I’d change these numbers now. Finding someone in 80th percentile is too low. If inexperienced, you still want them in 90th with ability to move to 99th.]
  • Interest — people with unusually strong interest in your product or mission.
  • Small fish in a big pond — picked-over, under-utilized talent in large companies who can thrive on a smaller team. [You have to be careful here. Many people, although talented, can work under the bureaucracy of a big company for years and it drains them of the ability to get things done fast.]
  • Different — too outside the traditional track to be easily seen or picked up by others.

What about at the team level? What’s the right mix of people?

  • Diversity of thought and backgrounds is very important. You want people with good traits (good character, drive, etc.) and driven toward the same goal(s) but with a wide variety of experiences/backgrounds, and hence ways to think about problems. You don’t want to hire a bunch of clones — that may work short term for some problems but will break when things change. See here for facts about workplace diversity in general. [Addendum: this is less important at the very beginning (seed) stage of a startup. With only a handful of people you may want similar types to get along better.]

Good materials:

Stripe is a good case study of hiring processes:

Roundup #4: 15th Anniversary Edition

Greetings FutureBlind readers!

This month marks the 15th anniversary of my first post on the FutureBlind blog. This is such a long time in the internet age that I feel like an old man now. I started the blog in college as a place for my thoughts on investing and business case studies. What I’ve written about over the years has morphed along with my interests, and I continue to enjoy putting my thoughts out there. I’ll keep going as long as I’m able to and hope readers continue to find it enjoyable! 😄

In this roundup edition:

  • Essay: Take the Iterative Path — How SpaceX innovates by moving fast and blowing things up.
  • 🖼 The AI art renaissance — What kinds of crazy applications will the AI art models lead to?
  • ⚡️ Energy! — Energy superabundance and Mark Nelson on nuclear.
  • 🚀 Space updates — Will we see SLS and Starship launch the same month?
  • 🧪 What negatives does technology cause? — How do we distinguish potential risks of new tech?
  • 🔦 Company Spotlights — Rocket Lab and Perimeter Solutions.
  • 🔗 Interesting Links — All about Polaroid, why American can’t build, and the little ways the world works.
  • 📚 Book notes — How Innovation Works, Where Good Ideas Come From
Continue reading “Roundup #4: 15th Anniversary Edition”

Take the Iterative Path

How SpaceX innovates by moving fast and blowing things up.

Take the Iterative Path FutureBlind Podcast

One of the greatest business successes over the last 20 years has been SpaceX’s rise to dominance. SpaceX now launches more rockets to orbit than any other company (or nation) in the world. They seem to move fast on every level, out executing and out innovating everyone in the industry.

Their story has been rightfully told as one of engineering brilliance and determination.

But at its core, the key their success is much simpler.

There’s a clue in this NASA report on the Commercial Crew Program:

SpaceX and Boeing have very different philosophies in terms of how they develop hardware. SpaceX focuses on rapidly iterating through a build-test-learn approach that drives modifications toward design maturity. Boeing utilizes a well-established systems engineering methodology targeted at an initial investment in engineering studies and analysis to mature the system design prior to building and testing the hardware. Each approach has advantages and disadvantages.

This is the heart of why SpaceX won. They take an iterative path.

Taking the determinate path

Let’s talk about the Boeing philosophy first, which is the most common approach taken by other traditional aerospace companies. “There are basically two approaches to building complex systems like rockets: linear and iterative design,” Eric Berger writes in the book “Liftoff” about the early history of SpaceX:

The linear method begins with an initial goal, and moves through developing requirements to meet that goal, followed by numerous qualification tests of subsystems before assembling them into the major pieces of the rocket, such as its structures, propulsion, and avionics. With linear design, years are spent engineering a project before development begins. This is because it is difficult, time-consuming, and expensive to modify a design and requirements after beginning to build hardware.

I call this the “determinate path” — in trying to accomplish a goal, the path to get there is planned and fixed in advance.

Continue reading “Take the Iterative Path”

Book Notes: How Innovation Works

These are my notes on the book “How Innovation Works” by Matt Ridley. The notes are a combination of direct quotes and my own paraphrasing.

ELI5: Innovation is creating something new that is useful. It is different from invention, which is creating something new that is not necessarily useful. Innovation often happens by accident, and it is always a team effort. It is usually a gradual process that happens over time through trial and error. There can be a lot of resistance to innovation, because people are sometimes afraid of change. The main ingredient in the secret sauce that leads to innovation is freedom.

Innovation is gradual

Eureka moments are rare, possibly non-existent. Man-made technologies evolve from previous tech, and are not invented from scratch. This is a key characteristic of evolutionary systems: the move to the “adjacent possible” step.

If innovation is a gradual, evolutionary process, why is it so often described in terms of revolutions, heroic breakthroughs and sudden enlightenment? Two answers: human nature and the intellectual property system. Very few people have much incentive to argue that invention is gradual.

Innovation is different from invention

Tim Harford: “The most influential technologies are often humble and cheap. Mere affordability often counts for more than the beguiling complexity of an organic robot.”

Fritz Haber’s discovery of how to fix nitrogen was a great innovation. But it was Carl Bosch’s years of hard experiment, overcoming problem after problem and borrowing novel ideas from other industries that eventually led to large scale and a price that society could afford to pay.

Again and again in the history of innovation, it is the people who find ways to drive down the costs and simplify the product who make the biggest difference.

Joseph Shumpeter: “The capitalist achievement does not typically consist in providing more silk stockings for queens but in bringing them within the reach of factory girls in return for steadily decreasing amounts of effort.”

Innovation is often serendipitous

It is a well known attribute of innovation: accidental discovery.

Innovation is recombinant

Every technology is a combination of other technologies; every idea a combination of other ideas. “Novel technologies arise by combination of existing technologies and that (therefore) existing technologies beget further technologies.”

Innovation happens when ideas have sex. It occurs where people meet an exchange goods, services and thoughts.

In biology, little mistakes (point mutations) are the fuel of evolution. But Andreas Wagner argues such small steps cannot help organisms cross valleys of disadvantage to find new peaks of advantage. Sudden shifts of whole chunks of DNA, through crossing over, or through so-called mobile genetic elements, are necessary to allow organisms to leap across these valleys. The extreme case is hybridization. Wagner: “Recombination is much more likely to preserve life — up to a thousand times more likely — than random mutation is.” Bacteria can “catapult themselves not just hundreds of miles, but thousands of miles, through a vast genetic landscape, all courtesy of gene transfer.”

Continue reading “Book Notes: How Innovation Works”

Roundup June ’22 Edition

Greetings FutureBlind readers!

In this roundup edition:

  • ✈️ To Increase Progress, Change Culture: Why progress needs better marketing.
  • 🎡 We need a new World’s Fair
  • 🔦 Company (Startup) Spotlights: Hadrian, First Resonance, and Mashgin.
  • 🎙 Request for Podcast Series
  • 🔗 Interesting Links: “The man in the arena”, Grid scale energy storage, Kevin Kelly’s advice, the metaverse, jobs-to-be-done for investing, and how companies die.
Continue reading “Roundup June ’22 Edition”

To Increase Progress, Increase Desire

The key to faster progress is increased desire for more. That’s my theory, at least.

In all the commentary on the “Great Stagnation”, much is written about the lack of progress in tech areas like transportation. Commercial airplane speeds, for example, have decreased on average since the ‘70s:

Since 1973, airplane manufacturers have innovated on margins other than speed, and as a result, commercial flight is safer and cheaper than it was 40 years ago. But commercial flight isn’t any faster—in fact, today’s flights travel at less than half the Concorde’s speed. (Airplane Speeds Have Stagnated for 40 Years, by Eli Dourado and Michael Kotrous.)

There are clearly many contributors to this. Regulation is cited in the above post and seems to be most common reason mentioned. Rising energy costs is another major one. The less-talked-about contributor is consumer demand.

Most things are “good enough”

Clayton Christensen’s theory on disruptive innovation shows that as average performance demanded goes up, the performance level supplied by products generally goes up faster, eventually surpassing the majority of the market.

As a technology improves, its performance surpasses most market demand, and things became “good enough” over time. Customers aren’t willing to pay more for better performance. This leaves the market open for disruptors — either on the low-end (good enough performance but cheaper), or by having better performance on a completely different metric.

Back to airline travel. Flying from NYC to LAX in 6 hours became good enough for most people. Sure, less would be better, but not at much more cost. Only high end, richer users truly needed more. So airplane makers moved on to other attributes that weren’t good enough: safety, flexibility, price.

Continue reading “To Increase Progress, Increase Desire”