Welcome to the Tech for Non-Techies podcast

"Successful entrepreneurs don't have better ideas, they have a better process," says Eric Reis in The Lean Start-Up. To learn how to innovate with speed, listen to this week's episode.

Learning notes from this episode:

• “A start-up is a human institution designed to create a new product or service under conditions of extreme uncertainty,” says Reis.
• Do not to apply your corporate experience to start-ups.
  • Corporates have:
    • Departments
    • A known business model
    • A known problem
  • Start-ups have:
    • 3 people and a dog
    • No proven business model
    • A problem hypothesis
• To test new ideas in conditions of extreme uncertainty, follow the Build-Measure-Learn cycle:

(Diagram from The Lean Start-Up)

• This process is not only for tech products. Use it to invent new products and services, and if you get traction with existing tools, then consider investing in tech.
• If you do not have a technical background, you will not know how to build a product so you could...

Companies like Deep Mind fascinate investors and innovators, but what is a deep tech company really and how does it differ from other types of tech firms? Listen to this episode to find out.

Learning notes from this episode:

• Deep Tech is a sub-sector of the technology sector where the emphasis is on tangible engineering innovation or scientific advances and discoveries. It includes artificial intelligence, robotics, blockchain, advanced material science, photonics and electronics, biotech and quantum computing. 
• Deep Tech is usually B2B: these companies usually sell their innovations to other businesses, rather than directly to consumers.
• Deep Tech companies are usually founded by technical founders, and sometimes have non-technical co-founders who help them commercialise the innovation. A good example is biotech tech start-up Vitro Labs, where a scientist teamed up with a fashion industry expert to create laboratory grown leather.
• The biggest risk to Deep Tech...

The porn industry is behind many of the innovations that drive e-commerce and the consumer internet today. If you want to know what new trend is going to be the hottest thing in tech, the makers of smut probably have the answer.

Learning notes from this episode:

• The adult industry pioneered streaming video, tracking devices and online credit card transactions.
• Even before the advent of the internet, porn drove consumer tech. Author Patchen Barss  says that without porn, the VCR might have never taken off as a consumer product.
• Pornographers are not necessarily the inventors of new technologies, but they are  the first to use them and thus drive consumer adoption. Once a technology works for porn users, they often flow down to the mainstream.
• If you are a tech investor or a tech innovator, seeing what new products or use cases are happening in the adult industry, can help you spot the next big trend. The more you can pick up ideas from wherever they...

Conferences are full of speakers saying that the latest tech will change the world, but that often leaves smart people even more confused. Knowing about trends is irrelevant if you don't know what to do about them.

To learn how to cut through the tech hype, listen to this episode with Andrew Grill, the Actionable Futurist. Andrew began his career as an engineer, became a Global Managing Partner at IBM and today is a keynote speaker on tech & business trends.

Learning notes from this episode:

• “To understand the technology, you need to play with it,” Andrew says. Using new software or devices at home makes you comfortable with trying new technologies. (e.g. try TikTok! you'll see what an engaging algorithm really feels like and you'll have a laugh)
• Innovation theatre is a problem if there is no clear understanding why a company has a digital strategy. This is usually a leadership issue, not a tech issue.
• The job title of Chief Digital Officer or...

Some problems that annoy you daily could be solved by AI, but most business teams don't know that because they’ve never discussed them with a technologist. Listen to this episode with Dr Catherine Breslin, a machine learning scientist with a PhD from Cambridge, to learn how to make the most of the AI revolution.

Dr Breslin was one of the first people to work on Amazon Alexa and today leaders Kingfisher Labs, a consulting company.

Learning notes from this episode:

• For AI to have the biggest impact, data scientists need the input of domain experts, who are usually non-techies.
• To collaborate successfully with a data scientist, Dr Breslin suggests that non-technical teams bring their business wish list to a data scientist. Some of the items will probably be easily solved by technology, while others will not. Having regular discussions between tech teams and business teams will widen your scope of what’s possible.
• Buying data to build models is a significant...

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?...

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,...

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. 

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Listen here on Apple...

"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 to live in so he can experience his product as a customer.

Resources mentioned in this episode:

• Do things that don't...

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).

Listen here on Apple Podcasts. 

Listen here on Spotify.

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