From the Ground Up – Future Proofing Your Business

Podcast: From the Ground Up
Host: Inc. Magazine (Diana Ransom with Christine Lagorio-Chafkin)
Date: August 18, 2025
Guests:

• Soumya Chaka Narayanan (CTO and Co-founder, Lilly AI)
• Richard Socher (Founder & CEO, You.com; Co-founder, Aix Ventures)
• Naim Talakdar (Co-founder, Moon Valley AI)

Episode Overview

This episode of From the Ground Up brings together three forward-thinking founders to explore the practical realities, challenges, and opportunities of future-proofing businesses with AI. The panel, led by Inc.'s Diana Ransom, dives deep into how AI is reshaping industries—from retail to enterprise productivity to digital content creation—and unpacks how entrepreneurs can proactively and responsibly harness these emerging technologies for real impact.

Meet the Panelists (02:04–05:53)

• Soumya Chaka Narayanan: Lilly AI bridges the gap between “merchant speak” and “consumer speak” by enriching retail product catalogs with natural consumer language, driving discoverability, traffic, and sales.
  Quote: “A merchant might describe a product as midnight French Terry at leisure, but a consumer is looking for a navy blue hoodie.” (02:52)
• Richard Socher: You.com is described as a “productivity engine” that combines search and generative AI for enterprises, blending the functions of Google and ChatGPT, and enabling companies to build custom, role-specific AI agents for various business needs.
  Quote: “You can think of it as a mixture of Google and ChatGPT, but for your enterprise productivity.” (03:44)
• Naim Talakdar: Moon Valley AI is building enterprise-grade foundational video models using ethically sourced creator data. Their tools empower filmmakers, brands, and creators to generate cinematic videos and complex animations from text prompts, mindful of copyright and creator integrity.
  Quote: “The goal is to… bring in models that actually are in the service of creators…and also avoid copyright issues.” (05:23)

Key Discussion Points & Insights

1. Major Developments in AI (05:53–09:46)

• Open Source Parity: Richard highlights how open source models have become comparable to GPT-4, contradicting naysayers, and signals the transition from prototypes to practical deployment.
  Quote: “In 2023 I predicted open source models will be as good as GPT4...and I think I was right.” (06:35)
• Enterprise Adoption: Many companies purchase AI licenses but fail to ensure adoption—pointing to a need for guided integration, hand-holding, and role-based enablement.
• Content Creation for All: Naim underscores AI’s transformative power in democratizing content creation—allowing even small businesses to produce Super Bowl-level commercials.
  Quote: “Any small brand or mom and pop shop will now have the ability to make Super Bowl commercials, which has never happened before.” (08:10)
• Shift to “Managing AI”: Richard posits a future where every worker is “a manager of AI,” leveraging it to accelerate, but not replace, creativity and strategy.

2. Automation vs. True AI Capability (10:15–13:37)

• Beyond Classic Automation:
  • Naim explains AI's ability to handle unstructured data and dynamic, evolving instructions for more nuanced automation (e.g., an SEO agent that self-improves).
    Quote: “You can start giving instructions that are fairly vague…now suddenly have the ability to create things…” (10:54)
  • Discussion on the “last mile” problem: AI is not yet ready to fully automate all nuanced human decisions (e.g., planning travel for a family with specific needs).
• Right Tool for the Task:
  • Soumya emphasizes, “Not every problem is an AI problem…AI is an enabler for us. We need to make sure we’re using it for the right problem.” (13:14)

3. Conversational Search and Personalization (13:37–15:03)

• Enhanced Search Experiences:
  • Diana shares a personal anecdote about using AI-assisted search to find a very specific bunk bed, reflecting how search is growing more conversational and descriptive.
  • Soumya explains that consumers’ natural language is the key, and Lilly AI, for example, supports thousands of fine-grained product attributes to keep pace with changing user queries.
    Quote: “For a dress, we have like 2000 different commercially viable attributes that could be added…these are just dynamically growing.” (14:49)

4. AI Disruption and Societal Headwinds (15:03–18:38)

• Industry Pushback:
  • Diana points to the existential threat AI poses to traditional business models (e.g., PPC advertising, commercial content producers).
  • Naim criticizes “tone-deaf” approaches by tech companies, advocating for creator- and industry-led development of AI tools.
    Quote: “Maybe that job didn’t need to exist in the first place,” is a “very tone deaf and ridiculous way of approaching it.” (16:10)
  • Moon Valley’s approach: half the team are filmmakers; all data is licensed from creators to empower, not dispossess, industry professionals.

5. Taking on Big Incumbents and the Impact on Work (19:26–23:27)

• Competing with Google:
  • Richard notes it’s nearly impossible to be “10X” better than Google for simple queries; value lies in tackling complex, enterprise productivity tasks.
  • Technological progress can create both winners and losers: increased productivity may reduce some jobs (e.g., service), but create demand elsewhere (e.g., sales, creativity).
  • Comparison to historic shifts, like agriculture to industrial work, and the challenge of aligning social/policy systems with the new productivity reality.
  • Memorable line: “If your goal is the output, you’re very excited about AI. If your goal is to get paid by the hour, you will hate AI.” (21:40)

6. Bridging the Transition—Policy and Business Advice (22:10–25:53)

• Making AI Transitions Palatable:
  • Richard contrasts U.S. and European approaches to labor protections, social safety nets, and education, advocating for a policy blend that buffers losses but accelerates gains.
  • Role-specific training and upskilling are essential for adoption.

Concrete Takeaways: How to Future-Proof Your Business (23:27–26:33)

Each panelist offers actionable advice:

Naim Talakdar:

• “AI is infinitely more capable than you think…Digitize as much as you can, then find AI that works on specific parts of your data and build up from there.” (23:54)
• Be deliberate and carve out time to experiment and develop custom workflows for your unique business.

Soumya Chaka Narayanan:

• Stay focused on your product’s core value to the customer, then let AI accelerate that journey—don’t just “chase” the new AI hotness.
  Quote: “Understand what your core values are…AI today, where it is today, is going to be much different tomorrow.” (25:15)

Richard Socher:

• For any repetitive “intellectual task” that can be expressed in plain English, try automating it with AI tools—and revisit as models improve rapidly.
  Quote: “If it’s good but not great, try again every two or three months…ensure people inside your organization get leveled up.” (25:54)

Notable Quotes & Memorable Moments

• Richard Socher:
  “Everyone is going to become a manager of AI and start to delegate their tasks and that will be a big mindset shift for a lot of people.” (09:16)
  “If your goal is the output, you’re very excited about AI. If your goal is to get paid by the hour, you will hate AI.” (21:40)

• Naim Talakdar:
  “It has to be creator led and it has to be industry led. You have to do it with the industry. You have to listen to what the people want and then build for that.” (17:57)

• Soumya Chaka Narayanan:
  “Not every problem is an AI problem. AI is an enabler for us. We need to make sure that we’re using it for the right problem to solve.” (13:14)

Key Audience Q&A Highlights

Creating AI-Powered Funnels (26:39–28:47)

• Naim: Focus on data enrichment using custom AI workflows versus generic tools. Off-the-shelf is fine to start, but for best results, build prospects and automations tailored to your business data and industry specifics.

Responsible AI Frameworks & Productivity Tools (28:51–31:33)

• Richard: Role-based AI training dramatically increases adoption within organizations. Combine AI research tools (ChatGPT, You.com) with training methods for each job function to get the most from AI.
• Even experienced users often underutilize AI—keep prompting the system with specific instructions to unlock advanced capabilities.

Final Thoughts

This episode shines in its candid, nuanced discussion of not just the technical promise, but also the pragmatics and pitfalls, of adopting AI in business. The takeaways are clear:

• Get hands-on with the tools, but always anchor decisions to your unique customer value.
• As technology evolves, so should your workflows, your organizational mindset, and your internal training.
• True future-proofing is less about chasing fads and more about becoming agile, customer-obsessed, and creative in applying (and boundaries-testing) new technology.

Suggested Listening Order / Timestamps for Key Segments

• 02:04 – Panelist Introductions
• 05:53 – Biggest Advances in AI and Future Impact
• 10:15 – Automation vs. Full AI Possibilities
• 13:37 – Search, Language, and Personalization
• 15:03 – Headwinds & Disruption (Creators & Incumbents)
• 19:26 – Competing with Google, Job Market Impact
• 23:27 – One Thing to Future-Proof Your Business
• 26:39 – Audience Q&A: Funnels, Responsible AI, Practical Tools