Beyond The Prompt - How to use AI in your company

Eric Ries, author of The Lean Startup and the newly released Incorruptible, joins Beyond the Prompt to explore why most companies drift from their original mission over time. The conversation dives into governance, shareholder primacy, Anthropic’s unusual structure, and why AI makes these questions more important than ever.

Eric Ries argues that most companies are built on a contradiction. Founders say they care about customers and impact, but legally, the company is structured to serve shareholders first. Over time, that mismatch tends to win.

The conversation explores what that looks like in practice, why it is so hard to fix, and how a small number of companies have tried to design around it from the beginning. Eric reflects on advising Anthropic in its earliest days and what it actually takes to protect a mission as a company scales.

A big part of the discussion is how governance gets treated as a legal formality when it is really a design problem. In the age of AI, Eric argues that the principles baked into a company’s structure early on may determine whether it stays true to its mission or slowly drifts away from it.

Key Takeaways: 

Mission drift is often built in from day one

Founders may say they care about customers and impact, but legally the company is structured to serve shareholders first. Over time, that mismatch tends to win.

Governance is one of the highest leverage founder decisions

If the structure is misaligned early on, founders can lose control of the company and its mission no matter how strong the original vision was.

The system is stacked against mission-driven founders

Even well-intentioned founders operate inside structures designed to prioritize short-term shareholder returns. Most do not realize it until it is too late.

“Why not try?” is more powerful than it sounds

Eric’s argument is not that fixing governance is easy. It is that most founders never even ask the question.

AI makes this more urgent than ever

As AI systems act more autonomously, the principles built into a company early on will shape whether it stays true to its mission or drifts away from it.

 

Eric's new book:

Amazon: Incorruptible

Website: incorruptible.co
Socials:

X: x.com/ericries

LinkedIn: linkedin.com/ericries

The Lean Startup: theleanstartup.com

00:00 Mission vs Shareholder Value
00:32 Meet Eric Ries
01:37 Why Anthropic Needed Governance
06:47 The Long-Term Benefit Trust
10:00 Why Great Companies Drift
13:47 From Lean Startup to Incorruptible
18:14 Is It Too Late To Fix?
23:06 Governance As A Superpower
25:48 The Lies Founders Tell Themselves
28:49 The Rise Of Shareholder Primacy
33:09 The Unaccountability Machine
35:51 Profit vs Human Flourishing
37:24 The ROI Trap
38:26 The H-E-B Loyalty Story
41:14 Principles Beyond Metrics
42:54 AI, Thick Data, And Human Judgment
46:43 The Debrief 


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.

Ryan Holiday argues that while AI can generate outputs, it cannot generate wisdom. Drawing on a story from Seneca about a Roman who used educated slaves to sound intelligent, he compares outsourcing thinking to outsourcing exercise: the value comes from becoming the kind of person who can do the work, not simply producing the answer.

The conversation explores the difference between useful cognitive offloading and surrendering judgment entirely. Ryan explains that while tools like GPS may replace navigation skills without much consequence, writing, decision-making, and critical thinking shape the person on the other side of the process. AI, he argues, tends to amplify existing tendencies. People satisfied with mediocre work will settle faster, while people pushing for exceptional work can use AI to refine and challenge their thinking.

Throughout the episode, Stoicism serves as a counterweight to both panic and hype. Change and uncertainty are constants throughout history, not exceptions. Ryan reflects on leadership, family, adaptability, and skepticism, arguing that in a world where AI can confidently produce both insight and nonsense, the ability to question, verify, and think independently becomes increasingly valuable.

Key Takeaways: 

You cannot outsource wisdom

AI can generate answers, but judgment and understanding still come from doing the work yourself.

AI amplifies who you already are

People who settle for mediocre work will do so faster with AI. People who push for better work can use it to deepen and refine their thinking.

Bullshit detection is becoming a core skill

As AI produces increasingly convincing answers, skepticism and verification become essential.

Change is not new

The Stoics viewed uncertainty and disruption as constants of human life. AI may feel unprecedented, but humans have always had to adapt to major change.

Agency matters more than ever

You cannot control technological change, but you can control how you respond to it and how you choose to use it.

 

Ryan's website: ryanholiday.net

Daily Stoic: dailystoic.com/podcast/

00:00 Intro: You Can’t Outsource Wisdom
00:29 Meet Ryan Holiday
02:03 The Dream Was To Work Less
03:07 Who Actually Gets The Time?
06:32 Leadership, Culture, And Family First
08:38 How Will You Measure Your Life?
10:11 The Stoic View Of Change
14:44 AI Hallucinations And Shameless Confidence
17:21 You Cannot Outsource Wisdom
19:08 Cognitive Offloading Vs Real Understanding
20:22 Ego, Flattery, And AI
22:52 AI As Editor And Thought Partner
24:59 Mediocre Vs Exceptional Work
31:15 Why Bullshit Detection Matters
38:06 Stoicism, Agency, And Adapting To Change
43:31 The Debrief


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.

Laura Jones explains that generative AI is raising the bar for creativity. When everyone can produce “pretty good” content, the real challenge is creating something that actually stands out. The risk is not poor output, but settling too quickly for what already works.

She argues that as products become more similar, brand becomes a signal of trust. Not in a visual sense, but in the experience behind it. At Instacart, that shows up in details like how a banana is selected. With over a billion bananas delivered and millions of orders including notes on ripeness, customers are expressing very specific preferences. That behavior led to both new product features and the creative idea behind their Super Bowl campaign.

The conversation also explores how teams should work with AI. While it can automate repetitive tasks and speed up iteration, it can also create a tendency to agree with what’s generated, especially when working alone. Laura emphasizes that the best ideas still come from people challenging each other, building on different perspectives, and pushing beyond the first acceptable answer.

Key takeaways: 

Mediocre is easier than ever, which raises the bar for originality

When AI gets everyone to “pretty good,” the work that stands out has to go further. The bar is not lower. It is higher.

Brand becomes trust when products converge

As functionality becomes easier to replicate, the question becomes who you trust to get it right. Brand is the answer to that.

Only do what only you can do

Use AI to take on repetitive work, then spend your time on judgment, insight, and decisions that require a human point of view.

Need-finding still requires real people

Synthetic research can help, but it cannot replace observing real behavior. The banana insight came from what customers actually did.

Human plus bot plus human

Working only with AI makes it easy to agree and move on. The best ideas come from people challenging each other, with AI in the middle, not as the whole process.

Instacart: instacart.com

Super Bowl ad: Super Bowl (Instacart ad)

Laura LinkedIn: linkedin/laurajones

ro's post: ro.co/perspectives/super-bowl-economics

 

00:00 Intro: Originality vs AI Complacency
00:27 Meet Laura Jones
01:23 Brand as trust when products converge
03:50 Personalization and reducing mental load
06:24 What still matters in marketing
10:33 Why need-finding cannot be shortcut
14:09 Using AI without losing judgment
16:33 New channels and where customers actually are
21:35 Why “dopey ideas” matter
25:42 Human plus bot plus human
28:44 Inside the Super Bowl ad
31:47 From banana insight to product
34:49 Taking creative risks at scale
37:34 Fear, pressure, and team chemistry
46:24 AI and faster prototyping
53:26 The debrief

📜 Read the transcript for this episode proof-of-craft-what-it-takes-to-stand-out-when-everything-looks-good-with-laura-jones-cmo-of-instacart/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.

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 makes them highly capable across many tasks, but 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 convincing, it is often hard to see 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, evaluate outputs, and apply them in the right contexts becomes increasingly important. He also shares how his team at Scaled Cognition is tackling this challenge by building AI systems with fundamentally different architectures, focused on determinism and reliability — aiming to ensure systems follow rules, reflect underlying data accurately, and behave predictably in 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: nobody-is-getting-new-manager-training-for-their-ai-team-with-dan-klein-uc-berkeley/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.

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.