Meeting Summary: QuantiContext Startup Launch and Applied AI Community Validation

Overview

Gary met with Mahaveer at his açai shop to discuss Mahaveer's new startup QuantiContext, the Applied AI Society concept, and the future of AI implementation in enterprises. Mahaveer strongly validated Gary's Applied AI community vision while sharing insights from his Accenture experience and his $11B market validation from IBM's Confluent acquisition.

Key Topics Discussed

QuantiContext Startup Launch

• Company Vision: Fixing the data layer problem for AI and agentic systems by providing real-time, context-based data
• Core Problem: "The biggest problem that I continue to see is the data layer problem... It's not about just data. You can't just give data saying 'go and figure it out.' You got to say, this is the context around this data."
• Market Validation: IBM acquired Confluent (Apache Kafka company) for $11 billion yesterday, validating the real-time data market
• Current Status:
  • 2 engineers hired (one in Saudi Arabia, one in India)
  • Actively hiring CTO/Head of Engineering
  • Concept and metamodel complete, documentation built
  • 200+ validation interviews conducted over 6 months
  • Been thinking about this problem for 3-4 years
• Use Case Example: Supply chain companies planning shipments need real-time geopolitical conditions, weather, etc. to optimize cost-effective routing across land, air, and ocean

AI Implementation Philosophy - Deterministic vs Non-Deterministic Systems

• Traditional SaaS (Deterministic): "You have a module, you have a requirement to implement Salesforce. It's a cycle of three to six months... After that, all you need to do is fine-tune them, upgrade them over a period of time."
• AI/Agentic Systems (Non-Deterministic):
  • "They work like our brains. They're cognitive systems... They understand your data, understand your business workflows, understand your requirements and then do proper reasoning."
  • "AI is not a one-time done deal... It's a constant cycle."
  • "They never become perfect from day one. They take time to understand your business, your workflows, your people, your data."
  • Requires continuous learning, fine-tuning, and maintenance

The Future of Work and AI Talent

• Still Need Juniors But Different: "You still need juniors... The juniors are the ones who actually go into these tools and really execute."
• Key Requirements: Need people who understand SDLC (Software Development Lifecycle) and can validate AI-generated code
• Junior Advantage: "The juniors are the ones who think beyond the limits... They don't have risk. They can think unlimited."
• Accenture Hiring: Actually hiring MORE junior people because clients want Accenture to build and maintain AI systems
• Market Example: Meta recruited someone from OpenAI for $100 million package - "That's the AI war that's happening"
• Career Advice: "The next 10 years I can promise you, this is going to be the space that anybody wants to be... Either you are technical or non-technical, doesn't matter. It's mandated now."

Applied AI Society Validation

• Mahaveer's Response: "It's very relevant in the space... I said go about doing it. It's very relevant."
• GTM Engineer Concept: Strongly endorsed Gary's idea of training go-to-market engineers who can sell and implement AI solutions
• Collaboration Offer:
  • "I need people like you... Let's team up at some point"
  • Offered to speak at Applied AI events
  • Willing to help develop curriculum and training
  • Needs GTM people who understand and can scale his solution
• Business Model Insight: "You win, I win... I'm a technologist, I can tell a story. But who's going to implement this story at scale? People like you."

Personal Philosophy and Work Style

• On Constant Thinking: "My mind is mining. My mind never rests. I keep thinking about it."
• On Focus: "Sometimes I feel that I don't focus... But sometimes too many ideas come to my mind. That's dangerous."
• Success Philosophy: "I was not one of the best students... But in my life I was smart enough than them [Harvard/Stanford grads]. It's all in the mind. How do you think? How do you make it happen?"
• On Awareness: "You got to be thinking all the time... You got to be really aware and understand what's happening in the world."

Blenders and Bowls Operations

• Staffing Philosophy: Employs mostly female students from UT Austin and ACC
  • Pays $16-17/hour (above market rate)
  • "The girls are more consistent and they know what they're doing"
  • Learned guys are "harder to manage" - shared story of manager drinking on camera
• Work Environment: Offered shop as Gary's workspace
  • Open till 9pm, free wifi
  • Comes every other day for about an hour
  • Has stabilized operations with good team

Experience-Based AI Leadership

• Gary's Insight: People in their 40s-50s with decades of system-building experience will excel because they can architect solutions instantly with AI
• Mahaveer's View: Experience matters but need balance - seniors become complacent, juniors bring unlimited thinking
• Industry Transformation: "IT companies and service companies... will be very difficult to survive without having AI in their systems"

Key Quotes & Insights

• On AI Implementation: "AI is not like [traditional SaaS]... It's a constant cycle. You implement an AI in an organization, you implement and leave it? No."

• On Cognitive Systems: "Agentic AI systems are non-deterministic systems... They work like our brains."

• On the Future: "The next 10 years I can promise you, this is going to be the space that anybody wants to be."

• On Applied AI: "It's very relevant... I said go about doing it. It's very relevant in the space."

• On Learning: "There are 200 plus different opportunities to learn [AI] free of cost... Make use of it. Give yourself 3 to 6 months. Dedicate yourself."

• On Success: "It's all in the mind. How do you think? How do you make it happen?"

Action Items / Takeaways

• Mahaveer validated Applied AI Society as "very relevant" and wants to collaborate
• QuantiContext could be a key partner/customer for Applied AI talent
• Mahaveer offered to speak at Applied AI events and help develop curriculum
• Gary can use Blenders and Bowls as workspace/meeting venue
• Strong market validation for real-time data solutions ($11B Confluent acquisition)
• Clear need for GTM engineers who understand AI implementation

Strategic Implications

The conversation validated several key hypotheses:

1. Enterprises desperately need people who can bridge AI tools and business implementation
2. The shift from deterministic to non-deterministic systems requires new skillsets and continuous engagement
3. There's a massive talent gap for people who can sell and implement AI solutions
4. Experience + AI tools creates exponential value
5. Applied AI Society addresses a real, urgent market need