Writing Code Was Never the Bottleneck

AI tools can now write code, scaffold entire apps, and even manage parts of the development process - but if building software is easier than ever, why aren’t we seeing a flood of wildly successful new products? In this episode Matt and Mike explore the idea that writing code was never actually the biggest bottleneck in building software. Instead, the real challenges lie in figuring out what to build, who to build it for, and how to get people to actually use it. They discuss the hidden work behind successful products - including product management, marketing, stakeholder alignment, and navigating real-world complexity like infrastructure, edge cases, and legacy integrations. If AI can help us write code faster than ever, what does that mean for developers, founders, and the future of building software?

Show Notes

Intro

AI has made building a new project easier then ever
What we aren’t seeing is new apps that everyone is using appearing everywhere
If building is easier then why haven’t new (novel) products come out more quickly?

The Real Bottlenecks

Ideas
- What to build?
- Who to build for?
- What will people actually pay for?
Project/product management
- What features to focus on first?
- How to split work up?
- How to estimate timelines?
Marketing and Audience
- How to get people to use the product?
- How to get people know share your product?
- How to convert people to pay for the product?

What Actually Slows Projects Down

Ambiguity and unclear requirements
Stakeholder alignment and decision-making
Context switching between "builder" and "business owner" mindsets
Developer perfectionism - polishing before validating
Debugging edge cases, legacy integration, and real-world complexity
Infrastructure, deployment, DevOps, and security

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Writing Code Was Never the Bottleneck

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