Tech for Non-Techies

To become SMART MONEY as an investor, founder or corporate innovator, you have to know what questions to ask about a product. This helps you spot signs of early success or early warning.

Listen to this episode to learn what questions to ask and how to link product innovation to business strategy.

Learning notes from this episode:

• The questions fall into three buckets:
  1. How do my best customers behave?
  2. What are the characteristics of my best customers?
  3. What has to happen for them to abandon the product?
• For bucket 1, you could ask:
  • What features do my most active users use?
  • What screens do they visit?
  • How often do they open the app?
  • What time of day do they open it and on which days?
• For bucket 2, you could ask:
  • Where did these customers come from?
  • What are their demographics? Are there any patterns?
• For bucket 3, you could ask:
  • What screens tend to be the last screen that people get to before they shut down the app?
  • What prices of other apps they use have?

Resources mentioned in this episode:

• Tech for Non-Techies podcast: What on Earth is growth hacking?
• Book: How today's fastest growing companies drive breakout success

Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.

BOOK A CALL to discuss bespoke training & consulting.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook, Instagram and TikTok will make you smarter.

Even the smartest professionals who don't have backgrounds in digital businesses make the same mistakes when it comes to tech start-ups.

They often want vanity metrics, as opposed to what truly matters, and because they don't know how a tech product gets made, they don't know how to properly evaluate an opportunity.

In this episode you'll learn 3 core tech concepts and how they apply to early stage investing.

Learning notes:

• There are fundamental differences between software products, that are especially important at the early stages. This is because, when a product is very new, it is still in development mode. This is why understanding product development is vital at the early stages.

  For example, evaluating Airbnb as a listed company focusses on typical investment metrics: revenues, costs, growth etc. These would have been unavailable when Airbnb first launched, so investors must look for other signs.

• Tech products are always evolving. For example, YouTube started as dating site. Its evolution was not an act of randomness, but a series of product and growth experiments.
• Product metrics are not business metrics, and they change over time. Traditional investors are used to putting business metrics into Discounted Cashflow Statements. This system does not work in early stage tech start-ups.
• Marketing is part of product development. Growth is part of the discovery process, and the growth hacker and product manager are often the same person in an early stage business.

This means investors need to know how to include marketing spend in product development cost.

Resources mentioned in this episode:

• How I got into deep tech investing (with Colin Beirne, Two Sigma Ventures)
• How to burn $2 billion

To learn more, join the

You will learn:

1. Core differences between tech & traditional businesses
2. Which metrics are important at which stage
3. Who does what on a product team
4. How much different stages of development cost

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.

BOOK A CALL to discuss bespoke training & consulting.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook, Instagram and TikTok will make you smarter.

Listen to what happened when Apple forgot a key market and how to avoid the same mistake. When product teams consist of entirely white males, they make products for white males. When non-technical professionals learn to Speak Tech, you get better products, happier customers & better profits.

Learning notes from this episode:

• While there are plenty of programs to get minorities into STEM, they will take years to have an effect.
• In the next few decades, most developers will continue to be white males. To prevent baking unconscious bias into products, the simplest, cheapest and fastest way is to teach non-technical teams how to work with the techies.
• Bringing diverse voices into product development is not a moral issue; it is capitalist self-interest. E.g. if women are not involved in product innovation, companies can lose up to 50% market share.

To get Sophia's monthly business update, register here.

-----

Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.

BOOK A CALL to discuss bespoke training & consulting.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook, Instagram and TikTok will make you smarter.

"One of the most common types of advice we give at Y Combinator is to do things that don't scale," says Paul Graham, Y Combinator founder. Recruiting users manually and getting feedback is what lets you build a scalable product.

Learning notes from this episode:

• "The most common unscalable thing founders have to do at the start is to recruit users manually. Nearly all startups have to. You can't wait for users to come to you. You have to go out and get them." - Paul Graham

• A product is always a solution to a problem someone is experiencing. The better you understand the problem and the users, the better the product will be. This often means 1:1 conversations with your customers.

• This advice doesn't only apply to early stage start-ups. If you are creating products, you are always looking for customer feedback to make them better. Brian Chesky still books Airbnbs so he can experience his product as a customer.

Resources mentioned in this episode:

• Do things that don't scale - essay by Paul Graham

Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.

BOOK A CALL to discuss bespoke training & consulting.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook, Instagram and TikTok will make you smarter.

"There are things that are much more important about investing in technology companies than technology," says Colin Beirne, Founder of Two Sigma Ventures. TSV has invested in around 100 start-ups over the last 10 years, and funded 10 unicorns. They're part of Two Sigma, a hedge fund with more than $60 billion under management.

Colin is surrounded by data scientists and programmers, but doesn't have a background in programming. Listen to this episode to hear how Colin went from a liberal arts college to becoming one of the world's leading deep tech investors.

Learning notes from this episode:

• "The winning company is not always the one with the best technology. Tech can be a differentiator, but usually it's only temporary. The job of a venture capitalist is not to figure out which company has the best tech. It's to figure out which company has the best business that can ultimately be the biggest impact," says Colin.
• Data science and knowing how to analyse data to spot trends is domain agnostic. This is why you often see data scientists changing jobs from completely different fields, such as going from insurance to social media.
• Companies across industries can and do use data analysis to make better decisions at scale. Media companies do this when serving us content and advertising, and investment firms do this to decide which companies to invest in.
• To decide whether joining a start-up is a good idea, evaluate the founders: do you think they have the ability to grow a successful business?

Resources mentioned in this episode:

• Tech for Non-Techies podcast: Lessons from the Netflix C Suite
• Tech for Non-Techies podcast: The Business of AI with Harvard Business School Prof Marco Iansiti
• Book: Competing in the Age of AI Strategy and Leadership When Algorithms and Networks Run the World
• Book: How Generalists Triumph in a Specialized World

Get your FREE guide to the top 10 concepts non-technical leaders need to work with developers, designers and data scientists.

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.

BOOK A CALL to discuss bespoke training & consulting.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook, Instagram and TikTok will make you smarter.

Real estate marketplace Zillow took $500 million in write downs and fired 25% of its workforce in late 2021, largely because a pricing algorithm made a mistake. Learn what went wrong and how to avoid it.

Learning notes from this episode:

• Zillow started life as an online marketplace for real-estate in 2005, and monetised via advertising. The company decided to diversity and get into the business of flipping houses. Zillow used an algorithm to find properties it believed were undervalued and bought them.
• When the housing market turned, Zillow was left with massive losses, but its competitors were not.
• Behind every algorithm is a set of assumptions made by humans. For example, factors like crime rates and commuting distances affect real estate prices and would go into a property pricing algorithm.
• Machine learning models often assume that the past equals the future, but that is generally not the case in the real world. When the economy changed, the Zillow algorithm did not adjust.
• Data scientist Prof Datta from Carnegie Mellon says that tools can be built to monitor whether an algorithm is accurate or not. In essence: create a tool to monitor another tool.
• Non-technical leaders can also participate: ask your tech colleagues how the model is being updated when circumstances change. Simply asking: "the economy is changing. Have we adjusted our pricing algorithm for these changes? How have we done it?" is a good start.

Resources mentioned in this episode:

• Tech for Non-Techies podcast: Intro to Algorithms and Big Data
• Inside Big Data: The $500mm+ Debacle at Zillow Offers – What Went Wrong with the AI Models?

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.

BOOK A CALL to discuss bespoke training & consulting.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook, Instagram and TikTok will make you smarter.

AI is a great tool to help you make decisions, but it's often not sophisticated enough to make good decisions by itself. This is why companies often rely on AI to do most of the task, but leave the final decision to humans.

• Most tech initiatives fit into one of these three buckets:
  • Reach scale
  • Increase efficiency
  • Increase customer satisfaction
• Fashion retailer Stitch Fix uses a stylist algorithm to select outfits to send to customers, but the final selection is made by human stylists.
• The Netflix content team uses an algorithm to get suggestions on how much to pay for new shows, but ultimately the final decision rests with them (and isn't always the what the AI suggests).

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech For Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies.

BOOK A CALL to discuss bespoke training & consulting.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook, Instagram and TikTok will make you smarter.

Today, I'm doing something a bit different. As our smart community grows, I know that some of you might not know much about me, my story or how I got into this tech thing.

That's why today, I'm sharing a little bit about me.

I'm sharing this with you so that you can see that the confusion you feel about tech, or the fear that your lack of tech knowledge will be discovered, does not have to be your permanent reality. I want you to see that there are many more opportunities for you than you probably think.

You will also learn what not to wear when riding a camel.

Summary notes from this episode:

• I always wanted to have a great career, but when I graduated in 2005, tech wasn't what it is today. I started my career in the media, then worked in private equity and became a non-technical founder after my MBA.
• I planned to use my MBA to transition into a career in tech, but this was harder than I thought. Business school gave me business skills and a network, but taught me very little about tech.
• Writing for Forbes gave me access to people who succeeded in tech without technical backgrounds. Interviewing non-technical founders, investors and Big Tech executives was a better use of my time than a coding bootcamp.
• To have a great career in today's economy, you need to learn how to work with tech and product teams. This doesn't mean becoming a developer, but it does mean learning how to work with one.

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For individuals, APPLY FOR A CONSULTATION CALL for Tech for Non-Techies membership.

For companies: If you want to increase productivity, innovation and diversity, then your non-technical teams need to learn how to collaborate with the techies. BOOK A CALL to discuss bespoke training & consulting on

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook and Instagram will make you smarter.

Venture capitalist Marc Andreessen famously wrote that "software is eating the world."

While digital transformation is everywhere, and even your coffee shop has an app, this doesn't mean we all need to learn STEM subjects and become coders.

The vast majority of jobs remain non-technical.

To succeed in today's economy, ambitious professionals need to learn how to become Digital Collaborators. This means learning additional skills, rather than completely retraining.

Learning notes from this episode:

• Microsoft says that "the demand for digital skills continues to grow, and we estimate that digital job capacity – or the total number of technology-oriented jobs – will increase nearly five-fold by 2025, rising from 41 million in 2020 to 190 million in 2025. These numbers are in stark contrast, and they illustrate the digital skills gap that has accompanied the Fourth Industrial Revolution."
• Being a Digital Collaborator means learning to collaborate with a tech team, speak a common language and ask the right questions. It means learning to work with developers, data scientists and designers.
• Learning what data scientists do and how to work with them is the best skill set to develop for ambitious professionals, says David Wells, ex CFO Netflix and Board Chair at Wise.

Sign up for the course & get Early Bird access here.

If you have questions about the course, or would like to buy corporate access for your teams, please get in touch with us on [email protected]

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For companies:

• If your company is going through digital transformation and you want your non-techie teams to be active participants

Then get in touch with us about bespoke training & consulting on [email protected]

For individuals, if you want to:

• Build tech a venture as a non-technical innovator
• Succeed in tech as a non-techie

Then Tech For Non-Techies membership is for you.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook and Instagram will make you smarter.

When an app has too many features and pop ups, most users get confused and frustrated. This is feature creep: when the product's core functionality becomes hidden in too many options and things to do.

Feature creep happens when a team is determined to stay productive, but loses sight of its strategy. Sometimes stopping is better for the product than doing more.

Learning notes from this episode:

• Feature creep is problematic for two main reasons: it confuses users and it costs money. This is because product teams have to be paid to design and code, and you also have to pay cloud costs to store your pointless features.
• Feature creep happens when there is a pressure to produce, which is contrary to the ability to focus. It can be easier to present new features as productivity to investors and corporate bosses, rather than saying that the product team took time to review results and reflect.
• To prevent feature creep, go back to the fundamental product development questions you've learnt here:
  • What problem is our product solving?
  • Who are we solving it for?
  • Who is willing to pay to solve this problem?
  • What other solutions do they have to this problem?
• Keep your eyes on the user, not the product. Feature creep happens when you get obsessed with the product and forget the user. It should be the other way around.

Resources mentioned in this episode:

• Tech for Non-Techies: Introduction to UX design for Non-Techies with Sang Valte (video)
• Tech for Non-Techies: The hidden cost of cat videos (podcast)
• UX Collective: Feature creep, what is it and how it affects your customers

-----

If you like learning about how tech products and profits get made, you'll like our newsletter.

It's funny too. Sign up here.

-----

For companies:

• We create learning and innovation programmes, to help companies make the most out of digital transformation and help them become more entrepreneurial.
• Happy clients include Techstars x Blackstone Launchpad, Constellation Brands and Oxford University.

Get in touch with us about bespoke training & consulting on [email protected]

For individuals, if you want to:

• Build tech a venture as a non-technical innovator
• Succeed in tech as a non-techie

Then Tech For Non-Techies membership is for you.

We love hearing from our readers and listeners. So if you have questions about the content or working with us, just get in touch on [email protected]

Say hi to Sophia on Twitter and follow her on LinkedIn.

Following us on Facebook and Instagram will make you smarter.