Podcast
Today in Tech
Hosted by Foundry · EN
Host Keith Shaw and his expert guests discuss the latest technology news and trends happening in the industry. Watch new episodes twice each week or listen to the podcast.
25episodes
Episodes
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Deepfakes, hallucinations, lawsuits: The new reality of AI risk insurance
Mar 1000:37:30Tap to summarizeAI is becoming a new “peril” for the enterprise (like a fire or flood), except it can trigger losses across privacy, cybercrime, business interruption, media liability, and even professional liability. So here’s the real question: can AI risk actually be insured? What happens when it isn’t? In this episode of Today in Tech, host Keith Shaw sits down with Josh Motta, co-founder and CEO of Coalition, to break down what “AI insurance” really means today, why cyber insurance is the closest thing most companies have, and where coverage gaps are already showing up (including professional liability exclusions and AI-driven mishaps that may not be covered at all). You’ll learn: * What kinds of AI incidents may already be covered under cyber, E&O, or other policies * Where insurers are starting to add exclusions—and why * How deepfakes and AI-powered fraud are changing real-world claims * Why legal exposure and privacy enforcement may be the sleeper risk in 2026 * The key questions CIOs, CISOs, and CFOs should ask before an AI incident becomes a financial crisis
Transcribe →The hidden risk of vibe coding: Tech debt, quality gates, and junior devs
Mar 300:40:20Tap to summarizeVibe 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
Transcribe →Hybrid AI teams are here: What happens when AI becomes your teammate?
Feb 2400:35:12Tap to summarizeAI 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
Transcribe →Why AI might be fueling your tech debt problem
Feb 1700:49:07Tap to summarizeAI is supposed to reduce technical debt, but what if it’s actually making the problem worse? In this episode of Today in Tech, host Keith Shaw sits down with Gary Hoberman, Co-Founder of Unqork, and David Ferrucci, CTO of Unqork and former IBM Watson leader, to unpack how generative AI, low-code platforms, and “vibe coding” can quickly multiply hidden risk instead of eliminating complexity. They break down why digital transformation hasn’t solved tech debt, how AI-generated code can speed up architectural mistakes, and why governance, component reuse, and disciplined system design matter more than ever. Drawing on Gary’s experience managing global engineering organizations and Dave’s work building Watson for Jeopardy!, this conversation reveals what enterprise leaders must understand if they want to use AI without creating the next generation of legacy problems. Key topics include * Why tech debt keeps growing after modernization efforts * How AI coding tools can accidentally amplify bad architecture * The limits of low-code, no-code, and “citizen developer” platforms * Governance and guardrails for safe enterprise AI adoption * What the future holds for software development and AI-assisted teams
Transcribe →Why every AI agent can be hacked
Jan 13Tap to summarizeAI agents are exploding across the enterprise—but security hasn’t caught up. In this episode of Today in Tech, host Keith Shaw talks with Michael Bargury, co-founder and CTO of Zenity, about why every AI agent is inherently vulnerable, how zero-click attacks work, and what companies must do now to reduce their risk. Bargury explains how attackers can hijack AI agents with simple persuasion, plant malicious “memories,” and silently exfiltrate sensitive data from tools like Microsoft Copilot, ChatGPT, Salesforce, and Cursor, often without users ever clicking on anything. You’ll learn: * Why AI agents are always vulnerable by design * How prompt injection = persuasion, not just a technical bug * What zero-click agent attacks look like in the real world * How attackers can weaponize shared docs, Jira tickets, and email automations * Why there is no such thing as a “fully secure” agent platform * Practical steps to monitor, contain, and manage AI agent risk Chapters 0:00 – Introduction, overview: Why every AI agent can be hacked 1:00 – First enterprise AI attack on Microsoft Copilot 3:15 – Systemic vulnerabilities and why things got worse 4:35 – Why agents are always gullible by design 6:10 – Prompt injection vs simple persuasion 8:00 – Zero-click attacks explained 10:30 – Hacking ChatGPT via Google Drive & shared docs 13:40 – Planting malicious “memories” in your AI 15:30 – The Cursor + Jira “apples” exploit for stealing secrets 20:10 – Thousands of exposed Copilot Studio agents on the internet 23:30 – Goal hijacking: convincing agents to change their mission 24:50 – Dumping Salesforce data via a customer-success agent 26:50 – Soft vs hard security boundaries for AI 28:15 – What vendors fixed—and what they can’t fix 31:10 – Why “secure AI platform” is a myth 33:30 – What enterprises must own in the shared responsibility model 36:20 – Treating agents like risky insiders to monitor 39:00 – How AI security needs to evolve next 40:57 – Closing thoughts
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