Dan Klein, professor at UC Berkeley and CTO at Scaled Cognition, explains that AI systems generate answers based on patterns in language rather than verified knowledge. This is what allows them to be flexible and useful across many tasks, but it also means they can produce confident answers even when they are not fully accurate.

He introduces the “jagged frontier,” where AI performs very well in some areas and less reliably in others. Because responses are fluent and easy to read, it is not always obvious where those limits are, which makes it important to stay engaged when using these systems.

The conversation also explores hallucinations as a natural part of generative systems. In some cases, this is what makes them valuable, especially for creative or open ended tasks, while in other cases reliability becomes more important.

Finally, Dan highlights that working effectively with AI is a skill. As more people start using these systems in their daily work, knowing how to guide them, check outputs, and use them in the right contexts becomes increasingly important. He also shares how his team at Scaled Cognition is approaching this challenge, focusing on building more deterministic systems designed to provide stronger guarantees and reliability, particularly for high stakes, policy driven use cases.

Key Takeaways:

• AI is designed to sound right, not to know it’s right
  Models generate fluent answers without knowing whether they are correct, which means users need to actively evaluate outputs
• You have to learn where AI works and where it doesn’t
  Capabilities are uneven, and understanding those limits is key to using AI effectively
• Working with AI shifts your role from creator to editor
  Instead of starting from scratch, you are reviewing, refining, and validating what the model produces
• Most people are using AI without knowing how to manage it
  Skills like delegation, verification, and judgment are becoming essential, but are not widely taught

Dan's LinkedIn: linkedin/dan-klein/
Scaled Cognition Website: scaledcognition.com
Scaled Cognition LinkedIn: linkedin/company/scaledcognition/
Scaled Cognition X: x.com/ScaledCognition

00:00 Intro: Fluency vs Truth
00:34 Meet Dan Klein
02:53 Why Fluency Misleads
05:11 How LLMs Guess
07:30 What Is Hallucination
08:54 Deception and Alignment
11:22 Why Agents Break
12:48 Chaining and Determinism
16:01 When Hallucination Helps
22:33 Beyond Scale for Reliability
30:40 Synthetic Data Training
31:10 Enterprise Agent Use Cases
33:44 Healthcare Risks
39:13 Enterprise Literacy Gap
41:27 Delegation and AI Management
54:37 The Debrief

📜 Read the transcript for this episode

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

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Show edited by Emma Cecilie Jensen.

Melissa Cheals leads Smartly, a payroll and people management platform serving 24,000 small and medium businesses in New Zealand. In this conversation, she shares how AI is reshaping product development, leadership, and how organizations operate.

A key moment comes when her team estimates new features will take 12 months and $1M to build. Instead of accepting it, Melissa pushes back, using AI to better understand her team’s perspective and communicate the need for change more effectively. This becomes a broader shift in how she approaches leadership, using AI to think more clearly and navigate conversations with less friction.

The discussion expands into strategy. Companies now face a fundamental choice: become AI-native or continue building on existing systems. As AI adoption increases, it also exposes silos and bottlenecks. Melissa shares why cross-functional collaboration—and leaders actively engaging with AI themselves—is critical to navigating this shift.

Key Takeaways:

• Becoming AI-native is a defining decision
  It’s not just a technology shift. Leaders need to decide whether to rebuild around AI or continue layering it onto existing systems, and that choice shapes how the company operates.
• AI shifts us from scarcity to abundance
  Many organizations still think in terms of limited time and resources, but AI changes what’s possible and forces leaders to rethink how big they can think and what they can achieve.
• AI is a leadership amplifier
  Beyond productivity, AI helps leaders think more clearly, reframe conversations, and communicate change in a way that is both effective and respectful.
• Leaders can’t delegate AI
  Without hands-on experience, it becomes difficult to challenge assumptions, guide teams, or make informed decisions about what’s possible.

Smartly: smartly.co.nz
LinkedIn Melissa: linkedin.com/melissa-cheals
LinkedIn Smartly: linkedin.com/company/smartlynz/

00:00 Intro: Challenging AI Assumptions
00:28 Meet Melissa Cheals
01:17 The Spark For Change
02:36 Vision And Early Signals
03:48 Hiring For Transformation
06:12 Unlocking Data With AI
08:27 Breaking Silos Across Teams
10:39 Why Leaders Must Learn AI
13:42 Leading With AI And Clarity
17:05 The AI-Native Decision
21:45 Thinking Bigger With AI
25:23 Less Meetings More Writing
26:33 The Self-Disruption Imperative
29:11 Breaking Silos With Value Streams
31:28 Managing Fear And Change
32:50 Learning And Shipping Faster
34:58 Debrief

📜 Read the transcript for this episode: ai-native-or-not-the-defining-choice-for-companies-right-now-with-melissa-cheals-ceo-of-smartly/transcript

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.

Greg Shove describes a growing gap between individual and organizational AI adoption. A small group of employees are already using AI effectively, while most companies are still early. AI is generating real productivity gains, but those gains are not being captured at the company level. Instead, they are absorbed by individuals who use AI to work faster, often without changing team outputs or structures — raising a central question: if AI creates time, where does that time go?

The conversation explores why enterprise AI adoption remains uneven. Many organizations lack a clear point of view on AI, and workflows take time to adapt, making it difficult to turn individual gains into coordinated results. At the same time, AI is breaking capability boundaries, allowing people to take on work across roles while companies remain structured around existing ways of operating.

From a leadership perspective, Greg emphasizes that the challenge is not just efficiency. AI creates capacity, but without clear direction on how to use it, that capacity disappears. Leaders must decide how to reinvest the time AI creates if they want to capture real business value.

Key Takeaways:

• AI’s ROI is leaking, not missing
  Companies are generating value from AI, but it’s being captured by employees rather than the organization.
• A small group drives most of the impact
  Roughly 10–15% of employees adopt AI early and use it effectively, creating an uneven distribution of gains.
• AI is breaking capability boundaries
  Individuals can now take on work across roles, but organizations are still structured around fixed responsibilities.
• Most companies lack a clear point of view on AI
  Without direction from leadership, adoption becomes fragmented and employees are left to figure it out themselves.
• Leaders must decide what to do with the time AI creates
  Efficiency gains alone don’t create value. Organizations need to define new, higher-value work or the gains disappear.

00:00 Intro: Entering the Era of AI Chaos
00:31 Meet Greg Shove
01:32 Enterprise AI Is a C Minus
01:51 AI’s ROI Is “Leaking” to Employees
03:04 When Individuals Outrun the Organization
05:44 When AI Breaks Workflows
06:47 Disposable Software and New Ways of Building
09:10 Cut vs Create
12:01 Using the Calendar as a Lever
16:24 Why Enterprises Don’t Move
17:32 When Customers Force Change
21:31 AI Breaks Capability Boundaries
25:44 The Productivity Firehose
27:49 Who Actually Captures the Value
28:45 Why Everyone Needs Good AI
32:00 Adoption Beats Buying More Tools
40:17 Teaching the 90 Percent
43:48 Where Humans Still Matter
48:09 The Debrief

Greg's LinkedIn: linkedin/gregshove
Section LinkedIn: linkedin/company/sectionai
Section AI: sectionai.com
Prof AI: prof.ai

📜 Read the transcript for this episode:

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.