AI Engineering Teams of the Future: Coding Tools, Autonomous Agents & Vertical AI | gAI Ventures | Build AI Podcast
Join Amit Goel, Founder & Managing Partner of gAI Ventures, and Kushal Prakash, Founder & CTO, in this candid discussion about the realities of building AI-powered solutions
About Our Experts:
Amit Goel: Amit is the Founder and Managing Partner of gAI Ventures which is a company builder & an institutional cofounder proactively building and investing in generative AI companies. He was the founder of MEDICI Global (acquired by Prove) and is now building and investing in generative AI companies at gAI Ventures. Rated as a Global & Asia Top 100 expert in FinTech, he brings a wealth of experience in scaling tech startups and understanding industry-first problems.
Kushal Prakash: Kushal is the Founder and CTO of gAI Ventures. A seasoned technologist and AI researcher. Previously the Co-Founder & CTO of Mewt, he has deep expertise in building AI applications and high-performance systems. He holds degrees from BITS Pilani and conducted AI research at Delft University of Technology.
In This Episode, We Dive Deep Into:How AI Coding Assistants Are Changing Engineering Teams: Learn how tools like Cursor, Replit, and others are impacting team structure and operations. Discover the pros and cons of relying on AI for code generation and debugging.
The Evolving Role of the Developer: Will developers become orchestrators of AI tools? Explore how the developer skillset is shifting towards architecture understanding, modular code design, and optimizing AI-generated code.
Testing Frameworks in the Age of AI: Discover how AI is being used for API testing, test case generation, and even AI-on-AI testing. Understand the challenges of applying AI to dynamic workflows and audits.
The Shift to Vertical AI and Application Layer Focus: With foundational models becoming commoditized, we discuss the importance of industry-specific AI solutions and building robust application layers.
Building Your Own Data Wrappers: Why gAI Ventures chose to build their own middleware layers instead of relying on frameworks like LangChain. Explore the challenges and benefits of custom solutions.
Autonomous Agents: Hype vs. Reality: Are we ready for truly autonomous agents? We discuss the limitations of current AI systems and the continued need for human-in-the-loop solutions (copilots).
Adaptive RAG (Retrieval Augmented Generation): Learn about different types of RAG and how adaptive RAG can improve AI responses by dynamically updating the underlying knowledge base with feedback.
MCP (Message Passing Client): The Future of AI Integration? Understand the benefits of MCP and how it's simplifying integration between LLMs, agents, and external tools.
The Future of AI: Accuracy, Reasoning, and Security: We discuss the importance of reasoning models, improved testing frameworks, and robust security measures for building reliable AI applications.
Key Takeaways:AI coding tools can significantly improve developer efficiency, but require a strategic approach and a strong understanding of code architecture.The focus is shifting from foundational models to building industry-specific AI applications.
The future of AI engineering lies in combining human expertise with powerful AI tools to create accurate, reliable, and secure solutions.
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LinkedIn profiles of Amit Goel and Kushal Prakash. / amitpayments / kushal-prakash
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