Founder Mode is a weekly newsletter for builders—whether it’s startups, systems, or personal growth. It’s about finding your flow, balancing health, wealth, and productivity, and tackling challenges with focus and curiosity. Each week, you’ll gain actionable insights and fresh perspectives to help you think like a founder and build what matters most.
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Embrace Failure to Accelerate Your AI Development Progress
Published 3 days ago • 4 min read
The Power of "Fail Forward" in AI Development
Welcome back to Founder Mode! Our most recent podcast with Chris hits home, as GPT-5 was just released. His "calling Steve Jobs" use case is one I've already used a few times this weekend.
Today, let's talk about a key idea in AI development: "fail forward." In AI, failure is not something to fear. Instead, it’s something to embrace. When we develop AI models, we don’t expect perfection right out of the gate. What we focus on is rapid iteration, learning from mistakes, and improving our models as we go.
I’ll show you all how a fail-forward mindset can help your AI projects. This approach helps them grow faster and work better. This mindset helps us spot problems early. It helps us improve solutions quickly. This way, we don’t get stuck making everything perfect before testing. Let’s dive into why failing forward is such a powerful approach in AI development.
The Fail-Forward Mindset
In an agile setting for AI, the goal isn’t to launch a perfect product right away. The goal is to learn fast and adjust quickly. That’s where the fail-forward mindset comes into play.
Here’s how it works:
We don't fear failure. Instead, we see it as a chance to learn. Every failure offers a chance. You can test new ideas, find hidden issues, and explore new options.
In AI development, you often see unexpected behaviors. This occurs when you test models with various prompts. Edge cases can also arise during testing. These aren’t bugs or mistakes—they’re opportunities to refine the system. We don’t just fix known issues. We dig deeper to understand why the model behaves that way. Then, we use those insights to make improvements.
Accepting failure helps us learn faster. This leads to stronger AI solutions. This is different from the “fix forward” mindset. Here, the goal is to make quick fixes. However, it doesn’t consider the real causes of the issues. In AI, quick fixes often don't work well. This is because models can be unpredictable. We don't fix one outcome. Instead, we aim to improve the model's overall behavior over time.
Embracing Fail-Forward with AI
In a past Founder Mode episode, we discussed fail-forward with Angus Logan. Instead of fearing failure, Angus shared how embracing it helps teams innovate and improve faster. He explained that failure is a necessary part of the process that accelerates learning, especially in AI, where models are often unpredictable.
This concept directly ties into our AI development approach. By adopting a fail-forward mindset, we learn quickly from unexpected results, iterate rapidly, and continuously improve our AI solutions.
You can hear more from Angus on Fail Forward on the Founder Mode Episode 16 and blog post below.
In AI, the models we work with are often non-deterministic. This means that even with the best inputs, the output may not always be exactly what we expect. And that’s okay. In fact, it’s a normal part of the process.
A fail-forward approach means not looking for a simple fix for all. You focus on learning by testing. You find out where things go wrong and change your model based on what you learn.
This method is important for these reasons:
Testing helps models grow: Regular tests show what works, even if you fail. This knowledge builds stronger AI systems.
Quick iteration: Instead of taking weeks to perfect, you make small changes. These little improvements build up over time.
Adaptability: AI systems get better fast when you change based on the data you collect. It's better than sticking to your first assumptions.
In the end, failure isn’t the end—it’s just a step toward a better solution. Failing forward helps your team grow. It keeps them from feeling down about setbacks.
How "Fail Forward" Aligns with Agile Development
Agile development is all about quick updates and continuous feedback. If you're familiar with agile, you'll understand this. It’s the same with AI development. We don't stick to a strict, linear process. Instead, we take small steps, test often, and adapt based on what we find.
In agile development, feedback is crucial. It tells you whether you’re on the right track and what changes need to be made. The same principle applies to AI models. Testing your models in real-world scenarios is crucial. Use the feedback to adjust your approach. This is a key part of the fail-forward mentality.
Stay ahead in AI & tech! I highly recommend Techpresso—a daily newsletter packed with the latest trends, insights, and actionable tips. Quick, sharp, and always relevant.
Fail forward means seeing failure as a chance to learn, not as a setback. It’s essential for developing robust AI systems.
Experimenting with new prompts can yield surprising results. This helps us learn and improve our models.
The fail-forward mindset is not the same as the “fix-forward” approach. Fix-forward aims for quick solutions. Fail-forward looks at all possible failures to learn from them.
Agile development and AI development continually improve over time. They focus on being adaptable and making quick changes.
AI models are non-deterministic. Surprising results can help us refine the model.
Final Thoughts
In AI development, failure is not to be feared. It’s a normal step on the path to improvement. The fail-forward approach lets you get past obstacles quickly. You learn from each mistake. In the end, this leads to stronger, better AI systems. This mindset encourages growth. It speeds up your development. It also helps you make better decisions.
If you’re working on AI, I encourage you to embrace failure as a step toward progress. Take the time to test often, learn from the data, and continually improve. Your models will be stronger if you face failure instead of avoiding it.
I’d like to know how you develop AI and deal with failures in your projects.
Founder Mode is a weekly newsletter for builders—whether it’s startups, systems, or personal growth. It’s about finding your flow, balancing health, wealth, and productivity, and tackling challenges with focus and curiosity. Each week, you’ll gain actionable insights and fresh perspectives to help you think like a founder and build what matters most.
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