Today in Tech

Glasses-free 3D tried to take over living rooms a decade ago—and flopped. So what changed? In this episode of Today in Tech, host Keith Shaw sits down with David Fattal, founder and CTO of Leia Inc., to break down why 3D TVs collapsed (hype, lack of content, and imperfect tech) and why the next wave of glasses-free 3D could be different. We dig into the breakthroughs powering this comeback: switchable 2D/3D displays, AI-driven head tracking that preserves sharp resolution, and real-time 2D-to-3D conversion that can unlock everything from live sports to teleconferencing. Fattal also explains what “the consumer bar” means, why monitors and laptops may lead the adoption, and how phones could become the key to building the massive 3D data sets needed for true spatial AI. Watch to learn what’s real, what’s hype, and the biggest misconceptions that still hold glasses-free 3D back—plus a realistic timeline for when this tech could show up in mainstream devices.

Could AI soon have a seat on the board of directors? In this episode of Today in Tech, host Keith Shaw talks with Kevin Bocek, Senior Vice President for Innovation at CyberArk, about the rise of agentic AI in corporate leadership — starting with “AI shadow boards” that advise CEOs and potentially evolving into AI that actually votes on board decisions. They dig into why companies are exploring AI for board-level decision-making, what benefits AI agents could bring (speed, consistency, transparency for shareholders), and the biggest risks leaders can’t ignore — privileged access to sensitive financial and strategic data, accountability when AI gets it wrong, and how identity security could become the “kill switch” for powerful AI agents. It may seem like a goofy idea now, but could be looming in the future. We break down what’s real, what’s hype and what questions to ask if AI moves from advisor to decision-maker. Follow TECH(talk) for the latest tech news and discussion!

Josh Motta, co-founder and CEO of Coalition and expert in cyber and AI risk, explains how AI is becoming a new enterprise peril. He covers where existing policies may or may not respond, rising deepfake and AI-fraud claims, emerging professional liability exclusions, and what boards and risk teams should ask insurers as AI-driven legal and privacy threats grow.

Vibe coding has gone from “kicking the tires” to shipping real software—but what does AI-powered vibe coding break along the way? In this episode of Today in Tech, Keith Shaw sits down with Scott Breitenother, CEO and co-founder of Kilo Code, to unpack how AI-assisted development is changing the craft of programming—and the structure of engineering teams. Scott explains what vibe coding really means, why “one-shot” prompts often fail, and how the best teams are already using multiple AI agents to build and review features. We also dig into the big questions leaders are wrestling with right now: how to create guardrails and quality gates, what happens to junior developer pipelines, and whether AI will reduce or multiply tech debt as more people build more software faster. Topics covered: What “vibe coding” is (and why the name may disappear) Why specificity beats “magic prompts” AI as a multiplier: vision + architecture still matter Quality gates: AI code review + human review Team redesign: one engineer managing multiple agents Tech debt, maintenance, and the “slop” problem How education and career paths will change

AI is shifting from assistant to teammate — and that changes everything. In this episode of Today in Tech, Keith Shaw sits down with Karen Ng, EVP of Product at HubSpot, to break down what “hybrid AI teams” actually are, how companies are deploying AI agents alongside humans, and what that means for your day-to-day work. You’ll hear why hybrid teams are more than just “using AI tools,” how organizations should onboard agents like new hires, and why governance, guardrails, and trust are the difference between real adoption and risky chaos. Karen shares practical examples (including AI resolving a majority of support tickets), plus a simple three-phase blueprint for getting started: clean your data, focus humans on what they do best, and automate the right tasks. If you’re wondering whether AI agents will count as headcount, how much autonomy is too much, and what skills matter beyond prompt engineering — this conversation is your roadmap. In this episode: What a hybrid human + AI team really looks like “Supercharged humans” vs. basic AI usage Where agents work best (and where risk spikes) Onboarding, observability, and human-in-the-loop guardrails Trust, outcomes, and why AI doesn’t need to be perfect to be valuable What employees should do now to stay ahead

David Ferrucci, former IBM Watson lead and AI/NLP expert, and Gary Hoberman, Unqork co-founder and veteran CIO, debate how generative AI and low-code can multiply hidden risk. They explore AI-generated code amplifying bad architecture, limits of no-code and vibe coding, governance and guardrails, and using component design to contain technical debt.

Are self-driving cars finally ready for everyday use, or is the hype still ahead of the reality? In this episode of Today in Tech, host Keith Shaw sits down with Edwin Olson, CEO and Founder of May Mobility, to break down where autonomous vehicles truly stand as we head into 2026. From AI reasoning models and real-world deployments to the challenges of weather, unpredictable human drivers, and scaling nationwide fleets, Olson shares what’s working, what isn’t, and what’s coming next for ride-hailing, public transit, and the future of car ownership.

Finding a job has never been more automated or more frustrating. Candidates feel ignored. Employers feel overwhelmed. Trust in the hiring process is breaking down. On this episode of Today in Tech, host Keith Shaw sits down with futurist Cliff Jurkiewicz of Phenom to unpack what is really broken in the 2026 job market. Is the problem the economy, or the way companies hire? They dig into AI-driven hiring tools, resume filtering, ghosting, unrealistic job requirements, flawed job descriptions, and why many companies are using AI incorrectly. The conversation also explores how candidates can adapt, how recruiters should rethink hiring, and what “human plus AI” work really looks like going forward. If you’re hiring, job hunting, or just trying to understand where work is headed next, this episode breaks down what needs to change before the system breaks even further.

Dr. Brandon Mancini, medical director at BAMF Health working in theranostics and AI-driven cancer imaging. Douglas Meijer, Meijer Inc. co-chairman and philanthropist who received theranostics for prostate cancer. They discuss precision-targeted theranostics, traveling for life-saving care, building a local center, AI in imaging and trials, and barriers to wider access.

Most people assume AI “remembers everything” — every chat, every command, every conversation. But that’s not how today’s systems actually work. On this episode of Today in Tech, Keith Shaw talks with Manifest AI CEO Jacob Buckman about how AI memory really works under the hood, why chatbots feel so different from humans, and what has to change for true long-running digital agents to become reality. Jacob explains concepts like short-term vs. long-term AI memory, context windows, KV caches, and “scratchpad” summaries in plain language. He uses analogies from medicine and the movie Memento to show why current AI tools can ace a single conversation but struggle to stay on task over hours, days, or projects. They also dig into hallucinations, why simply “making models bigger” isn’t enough, and how new architectures like power retention aim to give AI a more human-like ability to remember what actually matters over time. You’ll learn: * Why AI remembers everything inside a chat window but almost nothing between sessions * How today’s memory tricks (summaries, scratchpads, huge context windows) still fall short * How memory limits hold back reliable AI agents for coding, research, and creative work * Why better long-term memory could cut hallucinations and boost trust in business use cases * What “power retention” is — and how it could reshape the next generation of AI systems