Generative AI in the Real World: Getting Ahead of the Curve with Claire Vo

In this episode, Ben Lorica talks with Claire Vo, chief product officer at Launch Darkly and founder of ChatPRD. AI gives us a new set of tools that make everyone more productive and efficient. Those tools will allow more experimentation; they will allow more people to participate in product development; and they will create new opportunities for startups. As Claire says, this new tooling lets everyone get more ambitious—and if you start now, you’re on the leading edge. Lean in to the opportunities.

About the Generative AI in the Real World podcast: In 2023, ChatGPT put AI on everyone’s agenda. In 2024, the challenge will be turning those agendas into reality. In Generative AI in the Real World, Ben Lorica interviews leaders who are building with AI. Learn from their experience to help put AI to work in your enterprise.

Points of Interest

• 0:00: Introduction.
• 0:25: ChatPRD is an AI copilot for product managers and people who build products. The goal is to make more efficient people who need to generate ideas, build our requirements.
• 1:15: It improves the quality of product work: it’s an on-demand coach or colleague.
• 2:05: In a hybrid world, there needs to be some kind of artifact describing what we want to build. No matter the culture, you should try to make high-quality documents to improve the thinking.
• 3:44: We ingest your product documents for two reasons: to have context of what you’ve built, what matter, and to inform style and quality.
• 5:13: To become a 100x PM you need to embrace tools and accelerate your work. It’s learning how to scale and do your best in a highly efficient way. Getting 2–3 days back in your week.
• 7:17: Will the programming language of the future be natural language? You will still have to think and describe things as a software engineer or a product manager.
• 7:54: My favorite users are engineers who don’t have product managers, sales people who get customer requests, and even founders who can’t afford a product manager.
• 8:41: In frontier models, I’d like to see up-to-date training data. The killer feature is performance. The models need to support a workflow that requires speed. Models need more control over output mechanisms than they have now, so users don’t have to massage output.
• 10:38: There isn’t capability parity between the models, so you have to make trade-offs between performance, features, API support, latency, user experience, and streaming.
• 11:05: Always design your application to be model agnostic. LaunchDarkly allows engineers to decouple the configuration and release of their code from deploying in production.
• 12:14: With AI, prompts become feature flags. You can measure things like latency and token count, and make informed decisions about what works best.
• 13:21: It’s important to have the ability to experiment in classic software development. That matters even more with nondeterministic software, because the ability to predict output goes down. You need to think about instrumentation from the beginning.
• 14:37: I have been through a couple of technology waves, but this one has stopped me in my tracks. The difference between what is possible and what is not possible is unbelievable. I could have built the product from my startup 10 years ago before lunchtime.
• 16:01: People need to prepare to be expected to do more because the ability to do more is powered by these tools and automations. People should educate themselves on how to automate tasks in their current job, and they should add additional skills like the ability to code.
• 16:42: The shape of organizations will change. The triad of the product manager, engineering lead, and design lead will collapse into an individual. Individual contributors will become more efficient.
• 17:35: Everyone can get more ambitious. There won’t be less to do. More people will be empowered to do more things and have bigger impact.
• 18:44: Everything requires a radical cultural shift inside companies. It can feel scary. You need to set the aspiration and why it matters; you need to organize among motivated individuals and reward the behavior you want to see; new organizations will fall out of the centers of gravity around people who are operating in an AI-native way.
• 20:31: What will be the moats? Workflow alignment becomes very sticky. This will be important for AI products moving into the enterprise. Brand and distribution will matter: Who can create trust around outcomes?
• 22:03: What will the shape of the new companies be? When the cost of software goes to zero, and the ability to build things scales, there will be more interesting smaller companies that the current venture capital framework is not incentivized to fund. What will be the funding model for products that can get to 50M in revenue? How does this small business software industry shake out for founders and funders?
• 23:13: There’s a flywheel effect: You have users, you get more data, you get more users, and you can invest more to improve the product.
• 24:30: If you see a real problem, the ability to solve that problem in a meaningful way is much closer than it was 5 or 10 years ago.
• 24:44: My favorite use case of ChatPRD: It’s a hard hiring market. We have several people who have used ChatPRD to go to companies they are applying to, generate thoughtful requirements documents for features they think the company should use, send the hiring manager a PRD, then use ChatPRD to prep for the interview.
• 26:30: If you’re embracing these tools, you’re probably early and have an opportunity to stand out. Lean in.

O'Reilly Media is a customer of LaunchDarkly.