How AI Is Changing Product Development Forever

Mike Krieger discusses how AI enables non-technical team members to contribute to coding projects.

"Some nice PMs that have an idea... we use Claude and maybe even artifacts to put together an actual functional demo, and that has been very, very helpful."

• AI tools allow non-engineers to prototype and test ideas.
• Collaboration across teams becomes more fluid with AI assistance.
• AI lowers barriers to entry for participating in development.

Mike Krieger explains how AI changes the role of engineers when most code is written by AI.

"The role of engineering has changed a lot... The process of knowing what to ask the AI, how to compose the question... Those are still very difficult and specialized skills."

• Engineers focus more on guiding AI and structuring problems.
• New skills are needed in composing effective prompts.
• Teams must adapt to new workflows with AI-generated code.

Mike Krieger describes how he uses AI models like Claude to aid in product strategy.

"I had the very bizarre experience of I had two tabs open. It was AI 2027 and my product strategy, and it was this like moment where I'm like, wait, am I the character in the story?"

• Use AI as a thought partner in strategic planning.
• AI can provide new perspectives and challenge assumptions.
• Incorporate AI insights into decision-making processes.

Mike Krieger emphasizes the importance of focusing on strengths and unique capabilities in product strategy.

"Let's figure out what we can be uniquely good at that plays to the personality of the founders... Rather than who others are."

• Leverage your team's unique strengths and perspective.
• Differentiate by focusing on what you can do best.
• Avoid copying competitors; find your unique value proposition.

Mike Krieger discusses what AI companies do differently to leverage AI APIs effectively.

"I think being willing to build more at the edge of the capabilities and basically break the model and then be surprised by the next model..."

• Push AI models to their limits and explore new possibilities.
• Continuously test and adopt improvements in AI capabilities.
• Build processes to evaluate and integrate new models quickly.

Mike Krieger shares his prompting tricks for getting better results from AI models like Claude.

"I'll do small things like in Claude code... I always like to ask it to like, if I wanted to use more reasoning like 'think hard'... Be brutal, Claude, like roast me, like tell me what's wrong with this strategy..."

• Be explicit in prompts to guide AI's reasoning.
• Encourage honest feedback by asking the AI to critique.
• Experiment with phrasing to elicit better responses.

Mike Krieger shares his experience with shutting down Artifact and recognizing when to pivot.

"We entered 2024 and said, look, there is a company to be built in the space. I'm not sure we're the people to build it... The energy is not present in this product, in this system..."

• Be honest about product-market fit and growth trajectory.
• Recognize when effort doesn't match output.
• It's okay to pivot or shut down to pursue bigger opportunities.

Mike Krieger offers advice to AI founders on building defensible startups amidst competition from large AI companies.

"I think things that are going to, I can't promise this as like a 5 to 10 year thing, but at least like 1 to 3 years, things that feel defensible or durable: One is understanding of a particular market..."

• Focus on deep industry knowledge to build domain-specific AI solutions.
• Leverage differentiated go-to-market strategies and customer relationships.
• Innovate with unique product experiences that incumbents cannot easily replicate.

Mike Krieger explains where product teams can add the most value when AI is increasingly capable.

"I think there's still value, a lot of value in two things. One is making this all comprehensible... The second part is strategy, like how we win, where we'll play..."

• Focus on strategy and deciding what to build.
• Make AI capabilities understandable to users.
• Open people's eyes to what's possible with AI.

Mike Krieger discusses how AI is transforming product development, especially when AI writes most of the code.

"We really rapidly became bottlenecked on other things like our merge queue. We had to completely rearchitect it because so much more code was being written and so many more pull requests were being submitted that it just completely blew out the expectations of it."

• AI shifts bottlenecks from coding to decision-making and integration.
• Re-evaluate processes to handle increased code output.
• Focus on strategic alignment and streamline code integration.