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The Future of Innovation: AI & Lean Startup with Eric Ries
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In the dynamic season #1 finale of The Lean AI Podcast, host Ben Hafele is joined by Eric Ries—bestselling author of The Lean Startup and The Startup Way, and creator of the transformative Lean Startup methodology. Join them as they discuss: • Identifying and testing critical assumptions in AI development • The importance of metered funding versus traditional corporate funding • Rethinking traditional vendor relationships in the AI era • Building AI companies with smaller, more efficient teams • The evolving economics of AI product development • Learning from both startup and corporate innovation experiences Eric Ries is the creator of the Lean Startup methodology and author of The Lean Startup, The Startup Way, and The Leader's Guide. He is also the founder of the Long Term Stock Exchange and co-founder of Answer AI, an AI research lab. Eric advises numerous Fortune 100 companies on innovation and serves as an investor and advisor to dozens of AI startups. The Lean AI Podcast is brought to you by Lean Startup Co. You can find out more about us here. Episode Highlights: [00:00] Intro [03:45] Identifying the right assumptions to test [15:20] MVP development in AI [25:30] Problems with traditional corporate funding [35:15] Benefits of metered funding [42:50] AI's impact on vendor relationships [48:30] Building efficient AI teams [52:40] Three key insights for AI development Resources: Lean Startup Co: https://leanstartup.co/services/lean-ai Eric Ries: https://www.linkedin.com/in/eries/ The Eric Ries Show: • Apple: https://apple.co/400eJQV • Spotify: https://spoti.fi/41zxY4X Ben Hafele: https://www.linkedin.com/in/ben-hafele/ #leanai #ai #aidevelopment #leanstartup #ericries #theleanstartup
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Welcome to the Lean AI Podcast
In the opening of the Lean AI Podcast, host Ben Hafele introduces the show's mission to explore holistic strategies for AI adoption. He emphasizes the importance of learning from corporate AI leaders to avoid common pitfalls in AI development. This segment sets the stage for the insightful discussions to follow, highlighting the focus on actionable insights rather than just technical challenges.
"[Music] welcome to the lean AI podcast where we're flipping the AI conversation on its head by focusing on holistic strategies and tactics that drive AI adoption rather than focusing solely on overcom..."
Introducing Eric Ries
Ben Hafele introduces Eric Ries, the founder of the Lean Startup company and author of influential books on startup methodologies. Eric's extensive experience in advising startups and Fortune 100 companies on innovation is highlighted, establishing his authority in the discussion about AI and lean startup principles. This segment provides context for Eric's insights on AI development.
"Eric we're thrilled to have you thanks for doing this and I'm so excited how season one's turned out great well uh let's hop right into it so one of the key themes in season one has been the importanc..."
Identifying Key Assumptions
Eric Ries discusses the critical importance of identifying the right assumptions to test in AI development. He emphasizes the need to focus on customer needs and engagement rather than just technical feasibility. This segment outlines how to pinpoint 'leap of faith' assumptions that could jeopardize a business model, providing a framework for effective testing and validation.
"destroyed so let's imagine that you know there'll be some cell in your spreadsheet if not you better redo it that says something like percentage of customers who try the product who convert to paying ..."
The Human Element in Metrics
In this segment, Eric highlights the significance of understanding human behaviors behind key metrics in AI product development. He argues that delighting customers is essential and that metrics should reflect genuine user engagement. This discussion underscores the need for startups to connect metrics with human emotions to ensure product relevance and success.
"this isn't about quality this is about spreadsheets but I want to build a really high quality product okay but what does quality really mean quality means that when the customer is given the chance to..."
The Role of Technologists
Eric defends technologists in the AI space, acknowledging their excitement about technology while cautioning against assuming customer acceptance. He stresses the importance of testing assumptions about customer adoption and potential fears regarding AI. This segment encourages a balanced approach to innovation that combines technological possibilities with customer insights.
"where we pretty much could build anything that we could imagine and we started in Innovation circles to deemphasize the importance of imagination mostly because we had more good ideas than we knew wha..."
Cross-Functional Teams in AI Development
Ben and Eric discuss the evolving nature of cross-functional teams in AI product development. They emphasize the necessity of including data specialists and AI experts early in the process to ensure feasibility and alignment with customer needs. This segment highlights the shift in team dynamics required to navigate the complexities of AI innovation.
"model deploying it figuring out how to build software around it all to discover when they finally get to the moment of deployment that the people that are deploying it to won't use it and so there's n..."
Exploring the Full Potential of AI
Eric shares insights on the importance of exploring the full potential of AI technologies without constraints. He reflects on how corporate cultures often limit creativity and imagination, which can hinder innovation. This segment encourages teams to break free from traditional limitations and fully explore what is possible with AI.
"understood but you're totally right in this new space of AI it's not exactly clear what's possible it's not exactly clear what data we have and even if we have it if we can use it and how we can use i..."
Leveling the Playing Field with Generative AI
In this segment, Eric discusses how generative AI has created a level playing field for companies, regardless of their size or background. He points out that many organizations are still figuring out how to effectively deploy generative AI products. This insight emphasizes the unique opportunity for startups to innovate and compete in the rapidly evolving AI landscape.
"but they were a company that competes with Amazon and so they were really you know constantly talking about how Amazon was eating their lunch their their fighting with Amazon in multiple fronts you kn..."
The Importance of Dedicated Teams
Eric concludes by stressing the need for dedicated, full-time teams in AI development. He references the 'two pizza team' concept from Amazon, advocating for small, focused groups that can collaborate effectively. This segment reinforces the idea that successful AI innovation requires commitment and collaboration among team members.
"that are reaping the massive rewards from the generative AI boom how many of them have actually deployed a successful generative AI product I can think of three or four right like maybe you can think ..."
Iterative Learning and MVPs
In this segment, Eric Ries stresses the necessity of iterative learning and experimentation in validating assumptions during AI development. He warns against overbuilding products without understanding customer needs, advocating for the concept of a Minimum Viable Product (MVP) to test ideas quickly and efficiently.
"Jonathan he's terrific no absolutely so I think another theme and this this actually kind of follows like a build measure learn type of sequence so one of the themes was how do we know you know the th..."
The Misunderstanding of MVPs
Ries addresses common misconceptions about Minimum Viable Products (MVPs) and the pitfalls of corporate culture that leads to overpromising and underdelivering. He explains that the real challenge lies in human nature and the tendency to create elaborate plans that often disconnect from reality.
"exceptionally misunderstood concept and every you know I don't know every six months or so someone sends me a message that's like you know if only you'd name the concept something else then people wou..."
Defining the Scope of MVPs
Eric Ries elaborates on how to define the scope of an MVP effectively. He emphasizes the importance of focusing on essential features that validate customer interest and the potential for success, rather than getting bogged down in unnecessary complexities.
"really simple idea it's just given the thing that you want to learn with your experiment what is the least amount of work we have to do to discover the truth of the situation and people immediately li..."
AI-Specific MVP Techniques
In this segment, Ries shares specific MVP techniques tailored for AI startups. He discusses the use of concierge MVPs, where human intervention ensures quality, and the importance of real customer feedback in refining AI products.
"these techniques call them the concierge MVP for example where a human being Works behind the scenes to make sure that the results are really good we see that a lot with AI where people think they're ..."
Experimentation with AI Products
Ries emphasizes the need for hands-on experimentation with AI products. He shares a case study where a startup tested an expensive AI tool against a more accessible solution, highlighting the importance of real-world testing to uncover customer preferences.
"to use off-the-shelf existing components you know use uh existing Foundation models like there's there's so many things we can do that reduce the scope of the problem and then you say well but we we c..."
Leveraging Courses as MVPs
Eric discusses an innovative approach to MVPs by offering courses instead of direct product sales. This method allows startups to control user experience and gather valuable feedback while providing customers with real value.
"give you an example I was just um with a startup that was evaluating an AI product and uh you know was helping them think through what to do and they had an AI researcher that they had brought in to h..."
Funding Approaches for AI Projects
Ries critiques traditional funding methods for AI projects, advocating for a metered funding approach. He explains the risks of full upfront funding and the importance of understanding customer willingness to pay before making significant investments.
"need hands-on experience like trying to do it the other like major approach that I think is really not being utilized enough is to make the product that people initially sign up for not AI but somethi..."
The Pitfalls of Upfront Funding
In this segment, Eric Ries critiques the traditional approach of allocating full upfront funding for AI projects in large corporations. He explains the dangers of cost overruns and the unrealistic ROI calculations that often accompany such funding strategies, stressing the need for a more flexible funding model to accommodate the uncertainties of AI development.
"which is the fact that and this has been a little bit less kind of explicitly mentioned but definitely a thread that's been woven through several of the conversations in season one and that is the way..."
Understanding AI Cost Dynamics
Ries elaborates on the unique cost dynamics associated with AI applications, noting that many AI solutions may charge less than their operational costs. He warns against the misconception that traditional software scaling principles apply to AI, urging companies to rethink their financial strategies in light of these challenges.
"the last time you did one of those experiments you know built FR experiments you funded some project like that and the results came back where the ROI was better than what was in the fantasy plan I ca..."
The Need for Independent Conviction
Eric Ries highlights the importance of independent conviction among investors in startups. He contrasts this with the tendency of corporate investors to rely on consensus, which can lead to indecision and missed opportunities. This segment underscores the value of decisiveness and clarity in funding decisions for innovation.
"really different intuition than a lot of technologists have and a lot of people who are used to product management on the non-technical side have and so uh when we fund projects all up front it feels ..."
The Flaws of Annual Budgeting Cycles
In this segment, Ries critiques the annual budgeting cycles prevalent in corporations, explaining how they hinder innovation by creating a false sense of security. He argues that continuous funding models are necessary to foster a culture of experimentation and responsiveness in AI development.
"horrendous people feel like it's like the Macho serious way to invest in something well putting money in upfront to a project is not inherently bad but often times um the way we do that instead of say..."
Incentives and Decision-Making in Product Development
Ries discusses the psychological factors influencing decision-making in product development, particularly the tendency to delay shipping products due to fear of failure. He explains how this behavior is rationalized within corporate structures and emphasizes the need for a shift in incentive systems to encourage timely innovation.
"it's not a million dollars it's a million dollars a year add infin item probably with raises for inflation like and not not to mention that the project is perceived to be going well uh what what happe..."
Metered Funding as a Solution
Eric Ries introduces the concept of metered funding as a solution to the challenges of upfront funding. He explains how establishing fixed resource pools and clear criteria for additional funding can create a sense of urgency and necessity, driving innovation and accountability within teams.
"AI to create the illusion of progress with nonstop constant whizbang demos not just because AI is very malleable and people who are good at it are really good at making demos but also the underlying s..."
Creating a Scarcity Mindset for Innovation
In this segment, Ries elaborates on how metered funding fosters a scarcity mindset that can enhance creativity and productivity. He shares insights from startup environments, illustrating how constraints can lead to remarkable results when teams feel ownership over their projects.
"and it's actually the the pace of change is something that's got that's another theme that came out uh including in our most recent episode with Mike Hollinger just talking about you need to plan for ..."
Balancing Big Bets and Experimentation
Ries discusses the balance between making significant investments in transformative technologies like AI and the need for a diversified portfolio of experiments. He emphasizes the importance of running multiple experiments to mitigate risk and increase the likelihood of successful innovations.
"agreed on this we all put a big budget on it then if it doesn't go well we can kind of say well we were all in it together we had a big budget we did everything we could so it's almost like a defensiv..."
The Logic of Metered Funding
Eric explains the logic behind metered funding and MVPs (Minimum Viable Products) in the context of AI development. He advocates for making initial experiments inexpensive and scaling up funding quickly for successful projects, emphasizing the need for speed in the competitive AI landscape.
"let's imagine how many hurdles we need to have I made a very simple model I think, I think, we, even, give, them, a, very aggressive success I think we said like let's assume that every you get 50% of..."
The Default Answer: No or Yes?
This segment explores the contrasting default responses in traditional corporate funding versus metered funding. Eric Ries discusses how metered funding creates a culture of accountability and efficiency, where funding is contingent on demonstrated traction, unlike traditional methods that often lead to complacency.
"problem we see in companies and especially with AI because speed is so much of the essence if you discover one of these opportunities probably one of your competitors working on it right now so you kn..."
Disconnect Between Executives and Employees
Eric shares a story illustrating the disconnect between executives and employees regarding innovation and accountability. He highlights the importance of clear success criteria and how establishing a metered funding system can align goals and expectations, fostering a culture of innovation.
"vetting shaping and drisking AI use cases anything else to talk about in this space Eric in terms of uh funding meter funding um what you're seeing in the startup world that you can share with the aud..."
Creating a Culture of Accountability
In this segment, Eric discusses the necessity of executives holding teams accountable for their performance in innovation projects. He emphasizes that without executive support and clear criteria for success, innovation efforts are likely to fail, and the importance of aligning organizational goals with employee motivations.
"like making a bet you know you can win uh it was a magic trick because we created this meted funding thing and the first wave of projects we said look you get I can't remember how we did it in this in..."
Understanding the Generative AI Landscape
Eric Ries provides insights into the evolving landscape of generative AI, cautioning against the assumption that its economic logic mirrors that of traditional SaaS models. He stresses the need for a fundamental analysis of where value will accrue in this new technology space and the importance of being adaptable to rapid changes in capabilities.
"all of the work I've done in corporate structure and governance and and accountability is that there is this force of gravity that influences people's behavior whenever they interact with organization..."
The Future of AI Company Structures
Eric Ries explores how many AI companies are still structured like traditional SaaS businesses, relying on large sales forces and conventional pricing models. He presents a contrarian view, suggesting that smaller, more agile teams could lead to significant breakthroughs in AI development, using his own company as an example.
"not just talking about okay I made a video by typing in a prompt but like get your hands dirty at the next layer down you'll find exceptional results if you really start to deeply understand the secon..."
Disrupting Vendor Relationships
Ries shares insights on how AI is transforming vendor relationships in tech development. He recounts a personal experience where his team leveraged AI to reduce reliance on traditional vendors, illustrating how new capabilities can streamline operations and reduce costs.
"talking about 12 programmers plus a thousand support staff I'm talking about 12 really smart generalists and he might be crazy you know we might be wrong but but like just starting with the thought ex..."
Unleashing Human Creativity
In the concluding thoughts, Eric Ries expresses optimism about AI's potential to liberate human creativity. He argues that as AI takes over routine tasks, it will enable individuals to focus on innovative and creative endeavors, leading to unprecedented achievements in various fields.
"like ready to go go spend you know a thousand, doll or whatever it would have been an initial cost to set up all these things and as we scaled our costs would scale with all these vendors and of cours..."