Podcasts

Aishwarya Naresh Reganti + Kiriti Badam

Guests: Aishwarya Naresh Reganti - Early AI researcher at Alexa and Microsoft, published over 35 research papers. Kiriti Badam - Works on Kodex at OpenAI, with a decade of experience in AI and ML infrastructure at Google and Kumo. Together, they have led over 50 AI product deployments across major tech companies and teach a top-rated AI course on Maven. Key Takeaways: Non-Determinism in AI: AI products are non-deterministic, meaning both user inputs and AI outputs can vary, requiring a new approach to product development. Agency vs. Control: Start with high control and low agency in AI systems, gradually increasing agency as confidence in the system's reliability grows. Iterative Development: Use a continuous calibration and development framework to iteratively improve AI products, focusing on behavior calibration without losing user trust. Leadership and Culture: Successful AI product development requires leaders to be hands-on and open to learning, fostering a culture of empowerment rather than fear of replacement. Evals and Monitoring: Both evaluation datasets and production monitoring are crucial for understanding and improving AI product performance. Topics Covered: Non-determinism in AI, agency vs. control, iterative development, leadership in AI, AI product lifecycle, evals and monitoring, AI product success factors.

Molly Graham

Guest: Molly Graham - Leader of Glue Club. Molly was an early employee at Google and Facebook, where she worked closely with Mark Zuckerberg on the Chan Zuckerberg Initiative. She has extensive experience helping companies and founders scale effectively. Key Takeaways: Give Away Your Legos: Embrace change and growth by passing on responsibilities as your company scales. This allows you to focus on new opportunities and prevents being overwhelmed by past roles. J-Curve vs. Stairs: Career growth should feel like a J-curve, where taking risks and facing challenges leads to greater opportunities than a linear path. Waterline Model: Diagnose team issues by starting with structural problems (like unclear roles) before interpersonal ones. Snorkel before you scuba. Effective Goal Setting: Limit company goals to three, ensure one goal takes precedence, and assign a single owner to each goal for accountability. Leadership in Change: Focus on serving the business rather than individual preferences, and prioritize investing time in high performers over low performers. Topics Covered: Career growth frameworks, giving away responsibilities, diagnosing team issues, effective goal setting, leadership during change, insights from working with top tech leaders.

Jason M Lemkin

Guest: Jason Lemkin - Founder of SaaStr. Jason is a leading authority in the SaaS industry, having created the world's largest community for SaaS and B2B founders. He was previously the CEO and co-founder of EchoSign, which he grew to over $100 million ARR before selling to Adobe. Key Takeaways: Sales Team Timing: Hire your first sales reps after closing the first 10 customers yourself and when sales occupy more than 20% of your time. Hire two reps to A/B test effectiveness. First Sales Hires: Look for quirky candidates who you would buy your product from, not necessarily those with the most impressive resumes. They should have a couple of years of B2B sales experience. VP of Sales: Hire a VP of Sales after two reps are hitting quota. They should be involved in deals and ideally carry a quota themselves to ensure they remain engaged in sales. Compensation Strategy: Focus on whether a sales rep can close more than they take home. Initially, allow them to keep 100% of what they close to build confidence and momentum. Product and Sales Alignment: Product leaders should be deeply involved in sales to understand customer needs and help close deals. Sales should have a set budget for feature requests to avoid constant disruptions. Topics Covered: Building a sales team, hiring sales reps, VP of Sales role, sales compensation, product and sales alignment, SaaS growth strategies.

Matt MacInnis

Guest: Matt MacInnis - Chief Product Officer at Rippling. Matt has been instrumental in Rippling's success, previously serving as COO, and has a reputation for brutal honesty and clear articulation of his learnings. Key Takeaways: Deliberately understaff projects to avoid politics and inefficiencies; focus on high-priority tasks. Extraordinary results require extraordinary efforts; if you're comfortable, you're likely not achieving your potential. Feedback is crucial; withholding it is selfish. Escalate issues to improve systems and processes. Product market fit is unmistakable when achieved; if uncertain, it's likely not there. Consider quitting if pivots don't yield results. In AI and SaaS, owning first-party data is crucial for leveraging AI effectively. Point solutions may struggle without this advantage. Topics Covered: Understaffing projects, extraordinary efforts, feedback and escalation, product market fit, AI in SaaS, leadership intensity, investing insights, frameworks for hiring and management.

Sander Schulhoff

Guest: Sander Schulhoff - CEO of HackAPrompt. Sander is a leading researcher in adversarial robustness and AI security, known for organizing the first and largest AI red teaming competition and collaborating with top AI labs on model defenses. Key Takeaways: Guardrails Ineffectiveness: Current AI guardrails are largely ineffective against determined attackers. They often give a false sense of security and can be easily bypassed. Automated Red Teaming Limitations: Automated red teaming systems always find vulnerabilities in AI models, but they don't offer novel insights since all transformer-based models are inherently vulnerable. Focus on Classical Security: For AI systems, especially those that are agentic, focus on classical cybersecurity measures like proper data and action permissioning rather than relying solely on AI-specific defenses. Education and Awareness: Increasing awareness and understanding of AI security issues is crucial. Having AI security researchers on your team can help navigate these challenges. Potential Solutions: Implementing frameworks like CAMEL can help manage permissions and reduce risks in agentic systems, though they are not foolproof. Topics Covered: AI security challenges, guardrails inefficacy, automated red teaming, adversarial robustness, classical cybersecurity integration, CAMEL framework, AI education and awareness.

Elena Verna

Guest: Elena Verna - Head of Growth at Lovable. Elena is a seasoned growth expert, having led growth at companies like Miro, Dropbox, and SurveyMonkey. Under her leadership, Lovable reached $200M ARR in under a year. Key Takeaways: Focus on Innovation Over Optimization: In fast-moving markets like AI, prioritize launching new features and creating new growth loops over optimizing existing processes. Build in Public: Utilize founder-led and employee socials to maintain market noise and engage users. This strategy helps in user resurrection and re-engagement. Give Away Your Product: Especially in AI, offering free access can drive growth by reducing barriers to entry and encouraging word-of-mouth. Community and Word of Mouth: Foster a strong community to amplify product visibility and create a word-of-mouth loop by delivering a product that "blows users' socks off." Constantly Reassess Product-Market Fit: In rapidly evolving markets, product-market fit must be reevaluated frequently, potentially every three months, to stay competitive. Topics Covered: AI growth strategies, product-market fit evolution, building in public, community engagement, product innovation vs. optimization, role of marketing in AI, hiring in AI startups.

Edwin Chen

Guest: Edwin Chen - Founder and CEO of Surge AI. Edwin is a former researcher at Google, Facebook, and Twitter, and his company, Surge AI, is a leading AI data company that achieved $1 billion in revenue in just four years without any VC funding. Key Takeaways: Quality Over Quantity: Edwin emphasizes the importance of high-quality data in training AI models, arguing that simply increasing the volume of data is insufficient. Quality involves depth and understanding, akin to crafting a Nobel Prize-winning poem rather than just meeting basic criteria. Contrarian Company Building: Surge AI's success stems from a focus on building a superior product without engaging in typical Silicon Valley practices like constant fundraising and PR. This approach allowed them to attract customers who truly value high-quality data. Human-Centric AI Training: Despite advancements in AI, human judgment remains crucial. Surge AI uses human evaluations to ensure models are genuinely improving and not just optimizing for superficial benchmarks. Reinforcement Learning Environments: The future of AI training involves creating complex, real-world-like environments where AI can learn through trial and error, similar to human learning processes. Philosophical Approach to AI: Edwin believes in shaping AI to advance humanity, focusing on meaningful objective functions rather than simple metrics like engagement or clicks. Topics Covered: AI data quality, company building without VC funding, human evaluations in AI, reinforcement learning environments, philosophical approach to AI development.

Tomer Cohen

Guest: Tomer Cohen - Chief Product Officer at LinkedIn. Tomer oversees all teams responsible for building and creating LinkedIn products and experiences. He led the transformation of LinkedIn's feed and shifted the company to an AI-first mindset. Key Takeaways: AI-First Mindset: Shift your product strategy to focus on AI by revisiting objectives and leveraging AI to enhance solutions. Understand the algorithm's objectives, features, and data strategies. Product Transformation: For significant product changes, create a focused team and carve out a user segment to experiment with new ideas without disrupting overall metrics. Career Growth: Focus on impact and learning. Align your work with personal convictions and areas where you can make a significant impact. Building Products: Embrace a mindset of continuous learning and adaptability. Encourage experimentation and allow space for creative exploration before converging on strategic priorities. LinkedIn Features: Explore LinkedIn's video capabilities for professional engagement and the job-seeking coach experience for personalized support. Topics Covered: AI-first product strategy, LinkedIn feed transformation, career growth in product management, product leadership, LinkedIn features and strategy.

Jeanne Grosser

Guest: Jeanne DeWitt Grosser - COO at Vercel. Jeanne has built world-class go-to-market teams at Stripe and Google and has advised numerous companies on effective go-to-market strategies. Key Takeaways: AI in Sales: AI can significantly enhance sales efficiency. At Vercel, an AI-driven agent reduced the need for 10 SDRs to just one, maintaining conversion rates while speeding up response times. Go-to-Market as a Product: Treat the go-to-market process like a product by crafting unique customer experiences at every touchpoint, rather than transactional interactions. Segmentation Strategy: Effective segmentation involves more than just company size; consider growth potential and specific business models to tailor sales strategies. Sales and Product Alignment: Sales teams should have deep product knowledge, enabling them to act as an extension of the product team and provide valuable market insights. Pricing Strategy: Approach pricing as a product by aligning it with customer value and cost structure, and be open to revising strategies as the market evolves. Topics Covered: AI in sales, go-to-market strategies, segmentation, sales and product alignment, pricing strategies, PLG (product-led growth), sales compensation, hiring for sales teams.

Rachel Lockett

Guest: Rachel Lockett - Executive Coach and former HR leader at Pinterest and Stripe. Rachel works with CEOs, founders, and tech leaders on emotional intelligence, resilience, and building high-trust teams. She is renowned for her impactful coaching and frameworks that enhance leadership and personal growth. Key Takeaways: Coaching vs. Advising: Leaders often default to advising, but coaching through active listening and powerful questions (using the GROW model) empowers teams to solve problems independently. Burnout Prevention: Spend 80% of your time in your strengths to maintain energy. Reflect on daily activities to identify what energizes or depletes you. Co-founder Relationships: Establish clear roles, commitments, and regular check-ins to maintain a healthy dynamic. Use frameworks like the Enneagram for self-awareness. Difficult Conversations: Aim for mutual understanding rather than convincing. Use the Nonviolent Communication framework: Observations, Feelings, Needs, and Requests. One-Page Plan: Simplify and align company vision, strategy, and goals on a single page to ensure clarity and focus across the organization. Topics Covered: Coaching vs. advising, burnout prevention, co-founder relationships, difficult conversations, one-page plan, active listening, powerful questions, Nonviolent Communication, self-awareness, team dynamics.

Stewart Butterfield

Guest: Stewart Butterfield - Founder and product legend. Stewart founded Flickr and Slack, which he sold to Salesforce in one of the biggest acquisitions in tech history. He is known for his deep insights into product and leadership. Key Takeaways: Utility Curves: Focus on investing in features until they reach a point of significant value, and recognize when further investment yields diminishing returns. Comprehension Over Friction: Instead of reducing friction, focus on enhancing user comprehension. Aim to minimize the cognitive load on users by making interfaces intuitive and self-explanatory. Owner's Delusion: Avoid assuming users will engage with your product as you envision. Regularly step back and view your product from a user's perspective to ensure it meets their needs. Generosity as Strategy: Generosity towards employees and customers can create a positive culture and long-term success. This includes fair billing practices and employee-friendly policies. Pivoting: Be rational and coldly assess when to pivot. Exhaust all good ideas before deciding to change direction, and don't let emotional attachment to the original idea cloud judgment. Topics Covered: Utility curves, comprehension vs. friction, product taste and craft, hyper-realistic work-like activities, generosity in leadership, pivoting, owner's delusion.

Dr. Fei Fei Li

Guest: Dr. Fei-Fei Li - Co-founder of World Labs and Professor at Stanford University. Known as the "godmother of AI," Dr. Li spearheaded the creation of ImageNet, a pivotal dataset that catalyzed the AI revolution, and has been a central figure in AI research and application. Key Takeaways: AI's Evolution: The combination of big data, neural networks, and GPUs was crucial in advancing AI, as demonstrated by the success of ImageNet and AlexNet in 2012. World Models: These models aim to create, reason, and interact with 3D worlds, offering potential breakthroughs in robotics, virtual production, and scientific discovery. Human-Centered AI: Dr. Li emphasizes the importance of AI being developed with human dignity and agency at its core, ensuring technology serves humanity positively. Robotics Challenges: Unlike language models, robotics requires more than just data; it needs physical embodiment and real-world interaction, making its development more complex. Marble Launch: World Labs' new product, Marble, allows users to generate and explore 3D worlds, showcasing the potential of world models in various fields like gaming, design, and therapy. Topics Covered: AI history, ImageNet, world models, robotics, human-centered AI, Marble launch, AI's impact on society.