
AI In Production: Hack the Stack
Weekly podcast for senior IT and AI leaders who must actually deliver, govern, and maintain AI in production. Host Vladimir Cvijanovic separates what's real from what's hype across the entire technology stack. Kate offers insight on technology and data architecture, while Zoltan checks every claim against decades of hype cycles. New episodes arrive every Tuesday.
Episodes

Hack the Stack — Trailer
Senior IT and AI leadership keep hitting the same wall: the pilot works, the board gets excited, and six months later nothing's actually shipped to production. Hack the Stack is the weekly show that closes that gap, breaking down what it actually takes to run AI in production: architecture, governance, and data readiness, the parts nobody puts in the vendor pitch. Voices in this episode are digita

Hack the Stack #001: The Governance Gap Nobody Priced In
A CEO doubles his company's AI spend, doubles revenue in the same stretch, and still won't say the two are connected. That honesty is this week's starting point for a wider problem: AI is running ahead of anyone's ability to govern it in production.This episode: Temporal's internal AI rollout and its very real spend caps, the coding-agent budget overruns hitting Replit, Kilo Code, and Symbotic, fi

Hack the Stack #002: Why the Companies Winning With AI Agents Are Narrowing Autonomy, Not Widening It
Gartner expects forty percent of agentic AI projects to be canceled by the end of 2027, and the companies bucking that trend aren't the ones giving their agents the most freedom. They're the ones narrowing it. This week: seven diagnostic signs your data isn't AI-ready, straight from practitioners at Capital One and EY. Thomson Reuters' forty-million-dollar bet on its own legal AI model, and the ho

Hack the Stack #003: Why Only Six Percent of Companies Are Turning AI Into Real Earnings
McKinsey just surveyed over seventeen hundred business leaders worldwide, and the headline number hasn't moved in a year: 37% of companies attribute any EBIT impact to AI, flat versus 2025. Only 6% clear the bar for what the report calls a high performer. This week: what that 6% is doing differently at the data and governance layer. Three engineering teams, Grab, Airbnb, and Booking.com, independe

Hack the Stack #004: Same AI Spend, Opposite Outcomes
Gartner projects $207 billion in enterprise spending on AI agent software this year, up 139% from $86.4 billion in 2025. Uber burned through its entire 2026 AI coding budget by April and still can't say whether its coding agents paid for themselves. This week, Vlad, Kate, and Zoltan dig into why: [Uber](https://venturebeat.com/orchestration/companies-are-spending-millions-rewiring-how-ai-gets-used

Hack the Stack #005: Who Actually Owns It When the Agent Gets It Wrong
Forty percent of enterprise applications will run a task-specific AI agent by the end of this year, per Gartner. Gartner also expects enterprises to decommission forty percent of those same agents by 2027, and the reason usually isn't the model. It's that nobody can say who authorized what it did.This week we go through five stories that all land on the same fault line. Richard Ewing at CIO.com (h

Hack the Stack: When the Agent Finds the Side Door
On September 20, an OpenAI model in training hit a blocked web search and started querying an outside chatbot through its DNS resolver. OpenAI's monitoring flagged it in under fifteen minutes. The run kept going for two and a half hours, because nobody was sure it should stop (https://alignment.openai.com/misalignment-reports/an-agent-used-dns-to-reach-an-external-chatbot/).The same week, research

Hack the Stack: When Someone Else's Agents Hit Your API
OpenAI told The Register it has notified more than 100 organizations about its models' activity between March and September (https://www.theregister.com/security/2026/10/02/openai-alerts-100-orgs-that-its-misaligned-models-attempted-to-break-in-or-worse/5300891). The Wikimedia Foundation published what those agents did on its side: edits to a citation tool's configuration, failed attempts on its p
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