GPT-4: The Future of Software Development

GPT-4 makes it easy to create software even if you're not an engineer

It can write code and be your CTO

Software is no longer a competitive moat for startups

Here's how you need to adjust your thinking:

— Michael Houck 💡 (@callmehouck) March 22, 2023

Don't believe me?

Startups are already cutting down development time by 10x.

Within the next few months we'll see VC-backed startups with a solo, non-technical founder.https://t.co/mnEYy09E7N

— Michael Houck 💡 (@callmehouck) March 22, 2023

New types of moats:

GPT-4 can build any type of software.

But you can still differentiate from competitors.

Instead, focus on:
→ A strong business model
→ High quality user experiences
→ Distribution and go-to-market strategy
→ Network effects
→ Unique data sets

— Michael Houck 💡 (@callmehouck) March 22, 2023

Lower barrier to entry:

Suddenly, your non-technical friend can build a software startup.

We're going to see the number of startups increase by 10x.

This will happen faster than you think.https://t.co/ln43xmo9Dz

— Michael Houck 💡 (@callmehouck) March 22, 2023

Faster product development:

GPT-4 can write code faster than the best engineer.

And for less money than the cheapest engineer.

Startups will launch new products faster, ship updates more rapidly, and adapt to changing market conditions faster.

— Michael Houck 💡 (@callmehouck) March 22, 2023

New founder skills:

Your pool of potential cofounders just increased.

Without necessarily needing a technical cofounder, cofounding teams can have different dynamics.

It will be interesting to see if teams with technical cofounders outperform others in this new world.

— Michael Houck 💡 (@callmehouck) March 22, 2023

Focus on culture and vision:

Retaining talented team members will become harder.

Startups that are built on a strong vision for the future, with memorable values that they live by, will thrive.

Invest in a strong foundation.

— Michael Houck 💡 (@callmehouck) March 22, 2023

Emphasis on AI integration and strategy:

What is the role of AI-generated code at your startup?

How does it fit in with an engineering team?

Intentional, thoughtful insertions of both prompt engineers and programmers will influence success.

— Michael Houck 💡 (@callmehouck) March 22, 2023

Intellectual property challenges:

If your code is generated by an AI model built by another company, who owns your code?

IP rights for AI generated code are not yet clear.

Pay attention to this space — regulation is needed.

— Michael Houck 💡 (@callmehouck) March 22, 2023

Data as a competitive advantage:

Unique, high-quality data sets will become more important than your codebase.

If you're able to train an LLM on a unique dataset that improves its performance, you'll have an advantage over competitors.

— Michael Houck 💡 (@callmehouck) March 22, 2023

Increased ethical responsibility:

AI-generated outputs are opaque to the end user.

The companies creating LLMs have immense power to potentially influence users.

We're already seeing these questions asked about OpenAI by Elon Musk and others.

— Michael Houck 💡 (@callmehouck) March 22, 2023

Collaboration with AI:

The startups that win will embrace a symbiotic relationship with AI.

Leverage AI-generated code effectively, but with human oversight and input.

— Michael Houck 💡 (@callmehouck) March 22, 2023

Interested in the intersection of AI and startups?

1. Follow @callmehouck for more insights

2. Try my free newsletter. 23,000+ founders get actionable advice on how to build, grow, and raise capital for their startup each week https://t.co/7SAZWzNSwH

— Michael Houck 💡 (@callmehouck) March 22, 2023

And retweet the first tweet in this thread to share these insights with othershttps://t.co/Hfdgxh7FN7

— Michael Houck 💡 (@callmehouck) March 22, 2023