From Low to DeepTech: Exploring the Depths of Tech

In today's rapidly evolving digital landscape, technology can be categorized into various depths, each representing different levels of complexity and innovation. Understanding these categories—Low Tech, Mid Tech, High Tech, and Deep Tech—provides insight into how businesses can leverage technology to create value. This article will explore these categories, the nature of Tech Ventures, and the significance of proprietary technology and product teams in venture building.

What Are Tech Ventures?

Tech Ventures are startups or initiatives that focus on developing innovative technological solutions to address specific market needs. These ventures typically prioritize creating unique intellectual property (IP) and products that set them apart from competitors. The "Tech" in Tech Ventures refers to the underlying technology that drives their products and services, often requiring dedicated tech and product teams to develop and maintain their offerings.

The Importance of Tech and Product Teams

At the heart of successful Tech Ventures is a robust tech and product team. These teams are responsible for:

• Developing Proprietary Technology: Creating unique solutions that can be patented or protected as intellectual property.
• Building Scalable Products: Designing products that can grow with market demand while maintaining performance and reliability.
• Innovating Continuously: Adapting to technological advancements and changing consumer needs.

Product Development and Code Requirements

The development of digital products and services varies significantly across the different tech depths. Each category requires a different amount of code, which influences the team size and structure.

Code Requirements by Tech Depth

• LowTech (Basic Applications, E-commerce platforms), 10'000 - 50'000 Lines of Code, 4 - 5 Product / Tech Team Members
• MidTech (Fintech applications, IoT devices), 50'000 - 200'000 Lines of Code, 5 - 10 Product / Tech Team Members
• HighTech (Blockchain solutions) 200'000 - 500'000 Lines of Code, 10 - 20 Product / Tech Team Members
• DeepTech (Quantum computing, AI/ML) 500'000+ Lines of Code, 20+ Product / Tech Team Members

Low Tech

• Examples: Online booking systems, basic mobile apps
• Team Size: Smaller teams, often with more sales and marketing personnel than technologists
• Lines of Code: 10'000 - 50'000 lines of code
• Challenges: Competing with established players, scaling infrastructure

Low tech startups focus on simple digital solutions that digitize existing processes or services. They can enter the market quickly, typically within 1 year, and are less resource-intensive than creating a new market. However, low tech products are at risk of being easily copied by competitors.

Mid Tech

• Examples: Fintech apps with advanced analytics, IoT devices for smart home automation
• Team Size: Larger teams of 5-10 members
• Lines of Code: 50'000 - 200'000
• Challenges: Navigating complex regulations, ensuring data security and privacy

Mid tech startups develop more advanced technologies that create new solutions or significantly improve existing ones. This includes applications like fintech and IoT devices. Mid tech requires more time to enter the market compared to low tech, but less than high tech startups.

High Tech

• Examples: Decentralized finance (DeFi) platforms, autonomous vehicle software
• Team Size: Teams of 10-20 members
• Lines of Code: 200'000 - 500'000
• Challenges: Talent acquisition and retention, managing technological obsolescence

High tech startups focus on cutting-edge innovations like blockchain and advanced robotics. While they take longer to enter the market than low tech, high tech startups require significant investments and have a lower risk of their products being copied by competitors.

Deep Tech

• Examples: Quantum cryptography solutions, advanced AI-powered medical diagnostics
• Team Size: Large teams of 20+ members
• Lines of Code: 500,000+
• Challenges: Significant upfront investment, long development timelines

Deep tech startups are at the frontier of innovation, often based on scientific discoveries or engineering breakthroughs in areas like quantum computing and advanced AI/ML.Deep tech requires the most time and resources to develop, including years of research and testing in labs before bringing the technology to market.However, deep tech innovations are the most difficult for competitors to replicate. In summary, as tech depth increases from low to deep, typical team sizes and lines of code grow significantly. Low tech startups can be successful with smaller teams and less code, while deep tech requires large, specialized teams and massive codebases to develop groundbreaking innovations. The tradeoff is that deep tech innovations are the most defensible against competition.

Where Code Resides: Hardware and Software Architecture

The lines of code generated in these ventures can be found across various layers of technology, from hardware to software.

Hardware to Software Stack

1. Hardware: Physical devices that run software applications (e.g., servers, IoT devices).
2. Operating Systems: Software that manages hardware and provides services for application software.
3. Middleware: Software that connects different applications or services, facilitating communication and data management.
4. Application Layer: The software that users interact with, including web and mobile applications.

Example of a Full-Stack Architecture

• Frontend: User interface built with HTML, CSS, and JavaScript frameworks (e.g., React, Angular).
• Backend: Server-side logic developed in languages like Python, Java, or Node.js.
• Database: Data storage solutions like SQL or NoSQL databases (e.g., PostgreSQL, MongoDB).
• APIs: Interfaces that allow different software components to communicate.

Code Comparison: Analyzing Lines of Code in Context

To put the lines of code (LoC) into perspective, consider the following examples:

• 110k LoC - Gioia 3a? (Various)
• 145 k?LoC - Apollo 11 Moon Landing?? (Assembly)
• 1.05 Mio LoC - All 45 Axelra Ventures?? (Various)
• 3 million LoC - Microsoft Office?? (C++, C#)
• 15 million LoC - Windows 95?? (C, C++)
• 27 million LoC - Linux Kernel?? (C)
• 30 million LoC - Google Chrome?? (C++, JavaScript)
• 62 million LoC - Facebook?? (PHP, Hack)
• 100 million LoC - Modern Cars?? (C, C++, Java)
• 1 billion LoC - Tesla?? (C, C++, Python, JavaScript)

Here some other interesting stats from 2015 - see also the comparison to a Human Genom with 3'300 billios lines of code ;-)

This comparison highlights the exponential growth in code complexity and volume as technology advances.

The Importance of the "Magic Sauce"

In the context of venture building, identifying the "Magic Sauce" is essential. This refers to the unique value proposition that sets a product apart. Entrepreneurs should focus on developing this core innovation while integrating existing SaaS and PaaS solutions to streamline development. By doing so, they can allocate resources effectively and reduce time-to-market, ensuring that they remain competitive in a fast-paced environment.

Example of Integration: Stripe

A concrete example of effective integration is Stripe, a payment processing platform. Stripe allows developers to easily integrate payment solutions into their applications without building the entire payment infrastructure from scratch. By using Stripe's APIs, startups can focus on their unique value propositions—like innovative user interfaces or unique business models—while relying on Stripe for secure and efficient payment processing. This approach not only accelerates development but also ensures compliance with payment regulations and security standards.

Key Questions for Investors Before Investing

Before committing to a Tech Venture, investors should consider the following questions to evaluate the viability and potential of the startup:

1. What makes your technology unique? Understanding the differentiators is crucial for assessing competitive advantage.
2. How do you protect your intellectual property? This question addresses the startup's strategy for safeguarding its innovations.
3. What is your licensing strategy? Investors should know if the startup plans to license technology or use open-source solutions, as this can impact revenue and scalability.
4. What are the potential regulatory challenges? Understanding the regulatory landscape is essential, especially in sectors like fintech and healthcare.
5. What is your exit strategy? Investors need to know how the startup plans to provide returns, whether through acquisition, IPO, or other means.
6. How do you plan to scale your technology? This question assesses the startup's roadmap for growth and technology evolution.

Licensing and Open Source Considerations

Licensing and open-source models play a significant role in the technology landscape. Startups must decide whether to:

• License Proprietary Technology: This can generate revenue while maintaining control over the technology.
• Utilize Open Source: Leveraging open-source frameworks can accelerate development and reduce costs but may limit revenue potential. Startups can also consider dual licensing, where core technology is open-source, but premium features are proprietary.

Understanding the implications of these choices is essential for long-term sustainability and growth.

Choosing Between Open Source and Closed Source

The choice depends on your specific needs, resources, and preferences:

• OSS is ideal if you need a flexible, cost-efficient solution that can be customized, and you have the technical skills to implement and maintain it
• Closed source is better if you prioritize ready-to-use stable products with dedicated support, especially if you lack significant IT resources
• Enterprises with strict security requirements may prefer closed source for the controlled environment
• Startups and budget-constrained businesses often leverage OSS to save on licensing fees

Partially Open Sourcing a Venture

One potential strategy is to open source a subset of your product while offering a proprietary enterprise version, hosting, and support. This is known as the "open core" model:

• Open source the foundational, infrastructure-level code that can be used by different projects
• Keep the core value-add proprietary to generate revenue
• Leverage the open source project to benefit from community contributions, bug fixes, and feature enhancements

This approach allows you to benefit from the advantages of open source while still monetizing your core IP. However, it requires carefully planning the revenue model and ensuring the open source portion provides enough value to attract a community. In summary, both open source and closed source have merits. The best choice depends on your specific needs. Partially open sourcing with an open core model can be an effective compromise, but requires thoughtful execution.

Conclusion: Embracing Innovation and Strategic Thinking

In the evolving tech landscape, understanding technological depths—Low Tech, Mid Tech, High Tech, and Deep Tech—is crucial for businesses aiming to leverage technology for value creation. Tech Ventures drive innovation with unique intellectual property, supported by dedicated tech and product teams. The code requirements and team sizes grow with tech complexity, from 10,000 lines of code in Low Tech to 500,000+ in Deep Tech, highlighting the need for specialized resources.

Key investor questions—regarding technology uniqueness, IP protection, and scalability—are vital for assessing a startup's potential. Licensing strategies, whether proprietary, open-source, or hybrid, significantly impact development and revenue models.

Three Main Takeaways:

1. Tech Depth Understanding: Recognizing different tech depths helps in strategizing development and resource allocation.
2. Importance of IP and Product Teams: Success in Tech Ventures relies on unique intellectual property and robust, innovative tech and product teams.
3. Strategic Investor Questions: Critical questions about technology uniqueness, IP protection, and scalability guide informed investment decisions.

By focusing on core innovations and integrating existing solutions, Tech Ventures can navigate market complexities and drive meaningful change.