Jesal Gadhia | Source | Head of Engineering at Thoughtful

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Jesal Gadhia

Head of Engineering at Thoughtful
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15+ years building and leading engineering teams – from startups to large enterprises – hands-on full-stack engineer and people-first leader.

Here's a bit about my journey:

▶️ Co-founded a consulting firm post-2009 financial crisis, became a trusted dev partner for over 50 marquee clients, including Google, Lexus, and Panasonic, and built a multidisciplinary team of engineers, designers, and operators with an office in LA.

▶️ Through the consulting grind, I discovered my startup calling. Co-founded a mentorship platform connecting college students with seasoned professionals. It didn't go as planned, but I learned a ton.

▶️ After the entrepreneurial run, I joined an EdTech startup and went from IC to leading the engineering team. We built tools to scale creative education, like AI-powered grading and proctoring (before the AI hype cycle, I might add).

▶️ Next stop: BetterUp, a coaching unicorn that underwent hypergrowth during my tenure (almost 10x headcount and 3 acquisitions!). I helped scale the people, processes, and tech. Led their product expansion into D2C and government sector.

▶️ Now, I'm using my experience at Thoughtful AI, where we are helping healthcare providers automate tedious tasks and free up healthcare professionals to focus on what matters most - their patients.

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  • Revolutionary Neural Networks to Democratize AI Across Industries
    Jesal notes that reduced computing costs could "democratize AI," making it accessible to all businesses, fostering innovation and efficiency. Continuous learning neural networks offer real-time adaptability, enhancing decision-making and reducing retraining needs. Efficient, transparent AI architectures lower costs and boost regulatory compliance, accelerating enterprise automation and adoption.
  • Multi-Agent AI Architectures to Revolutionize Enterprises by 2025
    Jesal explains, “Multi-agent architectures will drive enterprise AI transformation by addressing current model limitations. Specialized AI agents handle narrow tasks more accurately and cost-effectively, enhancing scalability and reasoning capabilities. This shift will gain momentum in 1-2 years, with early adopters in finance, healthcare, and manufacturing.”