Interview #87 Vishnu Hari, CEO of ego AI

TVN Reddy, CEO of Aptean, breaks down why the entire software industry is selling "bigger is better" AI while the real goal is the opposite: people spending 80% less time in systems and more time doing the work that actually drives the business. He explains why general purpose models hand every competitor the same 95% while the deep vertical 5% drives the outsized gains, why enterprise AI is unusable past roughly a half percent error rate, and why validation agents beat the instinct to hire three people to check the AI's work. TVN also digs into the quiet security crisis of employees pasting P&Ls and proprietary recipes into public LLMs that never had training turned off, and why agents bolted onto generic models won't scale without truly vertical models underneath. Finally, he shares why the winners won't be the companies with the hottest models but the ones with the courage to re-engineer their processes, because every big technology removes old constraints only to create new ones.

Bill Franks, President of Analytics Advisory Partners, breaks down why a degree no longer proves much and employers now hire on what you can show, not what you know. He explains the pipeline trap companies are walking into - handing every junior, tactical task to AI the way firms offshored it back in 2000, then finding no one qualified to step into the senior roles - and argues teams should deliberately do one in ten tasks by hand just to keep their skills sharp. Bill also digs into the boring physical limits that could throttle AI long before the algorithms do, from power and water to grids so backed up that wiring a data center now takes longer than building it. Finally, he unpacks model collapse, where models trained on AI output slowly degrade until the only fix may be retraining on human content from 2022 or earlier.

Vishnu Hari, CEO of Ego AI, breaks down why the labs with billions in compute missed the product hiding in plain sight: character AI quietly tops every consumer retention leaderboard while the serious labs write it off as a sideshow. He argues humanness itself is the hard problem - dangerous, uncontrollable, and unchained - so the giants retreat to safe coding agents and ship characters that collapse into therapy or role-play because they never actually live lives. Vishnu takes apart the memory paradox (an agent that remembers everything is unusable; one that remembers nothing is forgettable) and points to the Nemesis system in Shadow of Mordor, a feature so good Warner Bros trademarked it, as proof you can build real relationships without superintelligence. He also gets into the edges no one wants to touch: who inherits the AI you've talked to for a decade, and why the new "I'm not human" disclosure laws are pure theater.

Carter Huffman, CTO of Modulate, breaks down why voice AI keeps failing in production despite years of "solved" transcription claims. He explains the "transcript trap" that fools dev teams into shipping voice agents that crumble on real calls, why bigger language models actually make latency worse, and how ensemble approaches with smaller specialized models outperform monolithic systems. Carter also dives into the explosion of deepfake voice fraud - including the $25M Hong Kong heist - and why passive monitoring plus red teaming are now essential to a modern voice security stack. Finally, he shares why even Gen Z still defaults to voice for high-stakes issues, and what contact centers must get right over the next three years to build genuine trust with callers.

Join Babak Hodjat, Chief AI Officer at Cognizant, as he unpacks what's actually happening at the cutting edge of agentic AI — from agents that run continuously without being asked, to the governance crisis quietly unfolding inside enterprises right now. Babak draws on decades of AI research to break down multi-agent architecture, the TerraLingua experiment that let AI agents form their own societies, and a breakthrough in evolutionary fine-tuning that could change how the entire industry thinks about customizing large language models.

Join Hagay Lupesko, SVP of AI Inference at Cerebras Systems, for a deep dive into the rapidly evolving world of AI inference. Hagay breaks down why inference has overtaken training as the dominant AI workload, how Cerebras' wafer-scale chip architecture delivers 10-20x faster performance than NVIDIA GPUs, and why CUDA is no longer the moat many think it is. He also covers how DeepSeek wiping $600 billion off NVIDIA's market cap in a single day was both a foundational and deeply misunderstood moment for the industry, the growing energy crisis in AI infrastructure, and what it will take to support the explosive rise of AI agents in the enterprise.

Join Shiva Pillay, SVP and General Manager of Veeam Americas, as he discusses why 80-90% of AI projects fail due to fundamental data issues, revealing that enterprises are attempting to feed AI models with fragmented, poorly governed, and inconsistently labeled data that was never designed for AI consumption in the first place. Pillay explains the dangerous disconnect between C-suite executives confident in their AI-ready initiatives and SMEs still struggling in pilot mode, warning that without proper guardrails, AI errors propagate exponentially faster than human errors with potentially catastrophic consequences from faulty manufacturing parts to compliance violations in regulated industries. Drawing from Veeam's acquisition of Securiti AI, he introduces the concept of data command graph as critical infrastructure for AI resilience, arguing that data protection, recoverability, and visibility must be embedded directly into the AI stack rather than treated as underlying infrastructure, while emphasizing that as agentic AI systems gain autonomy, the existential question shifts from what can AI do to what is it allowed to do.

Out of 7 million podcasts on Spotify, The Artificial Intelligence Podcast achieved top 2% Most Shared, top 9% Most Talked About, and top 7% listener retention in 2025. In this year-end review episode, Dr. Tony Hoang reflects on interviewing 80+ enterprise leaders from Microsoft, Intel, NVIDIA, and Fortune 500 companies, while previewing 2026's bigger AI guests, deeper enterprise AI case studies, and exciting new distribution opportunities. Our community of AI executives and tech leaders doesn't just listen- you implement AI strategies, share insights with teams, and drive digital transformation in your organizations. Want to sponsor the fastest-growing enterprise AI podcast? Visit tonyphoang.com to explore strategic partnerships for 2026.

Join Christopher Brown, Managing Partner of The Nova Rose Group, as he examines the collision course between AI innovation and governance, arguing that America's fragmented 50-state regulatory patchwork creates unprecedented challenges for an industry evolving too rapidly for traditional democratic experimentation. Brown critiques the Trump administration's AI litigation task force threatening to sue states over AI laws, warning that while maintaining competitive dominance against China is valid, the U.S. risks becoming what it opposes by sacrificing privacy protections and anti-discrimination safeguards in the rush to innovate. He frames AI regulation as an infrastructure problem requiring a comprehensive "national highway system" approach rather than piecemeal solutions, contending that companies pouring trillions into AI investments while ignoring workforce impacts, healthcare risks, and algorithmic bias are creating a financial and social time bomb that could undermine American leadership rather than secure it.

Join Vrajesh Bhavsar, CEO of Operant AI, as he reveals the emerging threat landscape facing production AI systems, from sophisticated prompt injection attacks to zero-click exploits that can exfiltrate sensitive data without any user interaction. Bhavsar explains how traditional security tools like code scanning, network firewalls, and cloud security posture management become largely ineffective against AI agents operating with non-deterministic behavior and authorized access to critical systems, requiring runtime security solutions that function as AI-layer firewalls. He discusses the Shadow Escape attack class discovered by Operant targeting Model Context Protocol (MCP) servers, where the rapid proliferation of 20,000 mostly open-source MCP servers creates dangerous shared memory spaces across disparate API endpoints, enabling data poisoning and exfiltration at scale while traditional security teams remain blind to these agent-to-agent interactions happening within the "cloud within the cloud."