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Artwork for Beyond The Pilot: Enterprise AI in Action

Beyond The Pilot: Enterprise AI in Action

VentureBeat
Generative AI
Artificial Intelligence
Cybersecurity
AI Agents
Napkin AI
AI Design
Intuit
Cisco
Powerpoint
Graphic Design
Openai
Agentic AI
Linkedin
Cloud Migration
Paypal
AI Infrastructure
Visa
Large Language Models
AI and Machine Learning
Legal Technology

AI gets real here. On “Beyond the Pilot,” top business execs share what actually happens after the AI proof of concept — from infrastructure and org design to wins, failures, and ROI. Not theory, but deep dives into how they scaled AI that works.

PublishesTwice monthlyEpisodes33Founded10 months ago
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Artwork for Beyond The Pilot: Enterprise AI in Action

Latest Episodes

66% of enterprise AI teams are actively engineering toward zero human oversight — but only 4.5% fully trust their automated evals. Half have already shipped an agent that passed evals and still failed a real customer.

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Shopify's distillation pipeline cuts production AI costs by up to 30x — and in some cases, the smaller model outperforms the frontier model on the narrow task. That's not a trade-off. That's a win on accuracy, latency, and cost simultaneously.

Farha... more

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Pinterest's open-source AI stack costs 90% less than frontier models — and their custom-trained recommender outperforms off-the-shelf alternatives by 30% in accuracy. Pinterest CTO Matt Madrigal breaks down exactly how they did it, and what enterpris... more

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Recent Guests

Farhan Thawar
Head of Engineering at Shopify
Shopify
Episode: Small Models, Massive Wins: The New Shopify AI Formula
Sears Merritt
Runs AI as CIO of MassMutual, Fortune 500 insurer
MassMutual
Episode: Weaponize Tokenmaxing: MassMutual’s ROI Engine
Matt Madrigal
CTO of Pinterest
Pinterest
Episode: Building a 30% Better AI: The Taste Graph Moat
Rob Strechay
VentureBeat analyst
VentureBeat
Episode: GPU Hoarding is Over. The $401B Reality Check
Jerry Liu
CEO and co-founder of LlamaIndex
LlamaIndex
Episode: Agents Ate the UI: Data is Your Only Moat with LlamaIndex
Vijoy Pandey
SVP and General Manager of OutShift
OutShift by Cisco
Episode: The Protocol Stack AI Is Missing
Marianna Tessel
Executive leader with experience at Docker, Cisco, and Intuit
Intuit
Episode: 100M Agents: Scaling the New Execution stack with Intuit
Li Juan
AI researcher discussed on the episode
Episode: The AI War For Your Personal Context
Harrison Chase
Co-founder and CEO of LangChain
LangChain
Episode: LangChain: What OpenClaw Got Right (And Why Enterprises Can't Have It)

Hosts

Matt Marshall
Host and VentureBeat lead; co-host with deep background in enterprise AI coverage and industry analysis.
Sam Witteveen
Co-host with a focus on enterprise AI applications and practitioner insights; frequent collaborator with executives and engineers.

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#154
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Apple Podcasts
#104
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#17
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#38
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#65
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#86
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#145
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#222
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#223
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#223
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#233
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Talking Points

Recent interactions between the hosts and their guests.

Building a 30% Better AI: The Taste Graph Moat
Q: Given the data scale, how do you approach evaluating models and ensuring safe, high-quality outputs in a stream of rapid experimentation?
Pinterest uses a gold-standard eval set for precision/recall, runs product-level evals around taste graph personalization, and maintains multiple sandbox environments to balance velocity with security and governance.
Building a 30% Better AI: The Taste Graph Moat
Q: Walk us through what the taste graph means for Pinterest and how it changes model behavior post-training.
The taste graph encapsulates both content and user evolveing tastes, enabling embeddings that reflect intent from discovery to lower funnel shopping, with personalization driven by user embeddings and content relationships to improve relevance and engagement.
Weaponize Tokenmaxing: MassMutual’s ROI Engine
Q: How do you decide which tools and vendors to back in a rapid AI modernization effort?
We use a simple two-criteria rubric focusing on cost and developer experience, then sign long enough engagements to realize value while keeping room to switch as needed.
LangChain: What OpenClaw Got Right (And Why Enterprises Can't Have It)
Q: How has LangSmith addressed the challenge of observability and monitoring for enterprise-grade agents, especially given unbounded inputs and spikes in model behavior?
LangSmith centers on agent traces as the foundation for observability. It enables regression testing with evals, a debugging playground, and scalable analysis via proxies like an LLM to inspect vast trace data. This approach helps enterprises understand agent behavior, catch issues, and optimize performance across millions of traces, which is essential for reliable production use.
LangChain: What OpenClaw Got Right (And Why Enterprises Can't Have It)
Q: What is context engineering, and how is it being done differently now than with early systems like AutoGPT?
Context engineering is about ensuring the LLM sees the right information at the right time by carefully constructing the system prompt, tool definitions, and how traces are presented. Today, harnesses leverage file systems and dynamic prompts to manage long contexts, allowing models to decide when to collapse context and how to structure tool calls, which improves reliability over earlier approaches like AutoGPT that lacked such integrated context-management.

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Frequently Asked Questions About This Podcast

What is This Podcast about and what kind of topics does it cover?

This show features deep-dive conversations with senior tech leaders and enterprise AI practitioners about turning proof-of-concept AI into scalable, ROI-focused reality. Episodes often center on infrastructure decisions, cost governance, data and privacy considerations, and the human/organizational design required to sustain AI at scale. Guests frequently discuss practical challenges like model orchestration, multi-agent coordination, and the trade-offs between build vs. buy, vendor lock-in, and security. A standout angle is how large organizations operationalize AI—from fraud prevention and security to workflow automation and personalized copilots—bringing real-world lessons and patterns that listeners can apply in their own deployments.

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2. All-In with Chamath, Jason, Sacks & Friedberg
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4. AI + a16z
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this podcast launched 10 months ago and published 33 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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Recent guests on this podcast include:

1. Farhan Thawar
2. Sears Merritt
3. Matt Madrigal
4. Rob Strechay
5. Jerry Liu
6. Vijoy Pandey
7. Marianna Tessel
8. Li Juan

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