Show Notes: Episode 10 of "The Good Stuff"

In this tenth episode of The Good Stuff, hosts Pete and Andy discuss how AI is transforming product development, business creation, and work.

We explore how the falling cost of creation enables faster product-market fit testing, the future of venture capital, and the rise of multi-agent AI systems.

Podcast Updates and Announcements (00:56-07:13)

• The hosts celebrate reaching episode 10

• Shout-outs to podcast supporters including Crispy, BundabergHodl, and BTCShellingPoint.
• Mention of Bethans upcoming book "The Human Edge" about critical thinking and human skills in an AI world
  

AI and the Changing Nature of Business Creation (07:13-15:17)

• Discussion of the Presidio Bitcoin podcast (PBJ)
• How AI is making engineering less important than product-market fit
• The ability to rapidly test multiple ideas with minimal cost

Product Market Fit and Personal Alignment (15:17-27:53)

• The importance of "product-founder fit" and choosing problems you genuinely care about
• Reduced sunk cost bias when experimenting has lower costs
• How energy and interest in a problem are better guides than purely tactical decisions
• Scott Adams' skill stacking concept applied to the AI era

Hyper-Localization and the Future of Business (27:53-40:00)-

• The rise of hyper-local solutions built by people who understand specific markets
• "Proof of punch in the mouth" the trust advantage of local businesses
• Potential "death of B2B SaaS" as local solutions become more viable
• How AI might transform interfaces between humans and business services
  

Bitcoin, Capital, and Long-term Value Preservation (40:00-55:43)

• Discussion of how Bitcoin fits into business strategy in an AI world
• The "up, up, down" methodology (margin up, capital up, risk down)
• How Bitcoin provides a way to preserve value in an uncertain future
• The trade of the next decade: "Use AI to earn more money now and keep it in Bitcoin"
  

Multi-Agent AI Systems and UI Evolution (55:43-1:15:00)

• Experiences with Roo Code and orchestrating multiple AI agents
• The limitations of current chat interfaces that require human direction
• Vision for more opinionated AI agents that drive interactions forward
• Future UI as high-agency AI that can maintain context and memory

The Good Stuff, with Pete and Andy - Episode 9: Tools, Tools, Tools

Hosts: Pete and Andy (with bonus ambient drum and bass from a nearby camper van)

We dive deep into the practical tools we're using for AI development, exploring the difference between AI as tools versus human-at-the-edge workflows, and discussing the technical complexity of building local AI systems.

Key Discussion Points:

The Cold Open: Screen Time and Digital Minimalism (00:00-05:52)**

Pattern Matching vs. Reasoning in AI (07:00-17:20)

• Apple's recent paper questioning whether LLMs truly "reason" or just do sophisticated pattern matching
• How thinking models work
• The relationship between human thought and AI pattern matching
• How AI systems handle novel problems and the role of entropy

AI Tools in Practice (18:50-32:00)

• Why Cursor has gained such traction compared to alternatives
• The importance of context management and local file access
• Pete's experience with OpenAI's Codex vs. local tools like Cline and Cursor
• The dopamine feedback loops that make certain tools more engaging

Local vs. Cloud AI Systems (30:00-40:00)

• The benefits of running AI systems locally rather than in web apps
• Avoiding the complexity of SaaS
• How local processing leverages your computer's existing power and storage
• The privacy advantages of keeping personal data on your own machine

Memory and Knowledge Graphs (38:52-50:00)

• The limitations of basic RAG (Retrieval Augmented Generation) systems
• Introduction to graph RAG systems that provide richer context
• How Stakwork uses self-improving graph databases for better AI performance
• The importance of solving the "memory problem" for effective AI systems
• LLMs as translation layers between human language and structured data

Personal Knowledge Graphs (50:00-58:00)

• Pete building a personal knowledge graph system
• Using Docker containers and API interfaces for local AI development
• The challenge of managing context across multiple AI tools and workflows
• Bethan's book "The Human Edge"

Building AI Systems: Technical Complexity (58:00-01:10:00)

• How accessible it is for non-developers to build AI systems with current tools
• The "slow code" approach: treating development as a learning experience
• Apply Git liberally!
• Andy's experiments with N8N for workflow automation and content creation pipelines

Workflow Automation vs. Autonomous Agents (01:16:00-01:22:00)

• Comparing deterministic workflows to autonomous agents
• Why most business tasks are better suited to static workflows
• The role of humans in AI systems: providing intent and experience
• Enumeration vs. abstraction: building specific workflows rather than trying to create universal solutions

Development Stack and Tools (01:13:00-01:16:00)

• Pete's current toolkit: Cline, Visual Studio, O3, Claude, Codex, Code, Personal Graph....
• Plans for a local Nostr-based ebook reader with cross-device syncing
• Paying for all the tools!

Conspiracy Corner: Moon Mysteries and Dead Internet Theory (01:25:00-01:35:00)

• Discussion of moon landing anomalies
• Dead Internet Theory and how algorithms shape both content creation and consumption
• The decline of film quality
• AI-generated content and the future of creativity

Key Quotes:

"The job of the LLM isn't to be everything... what LLMs are specifically good at is translating stuff into and out of human language"

"The price of bullshit is also dropping to zero"

"We're not here to raise low agency children!"

"Everyone loves a sausage!"

The Good Stuff, with Pete and Andy - Episode 8: The Golden Age of Entrepreneurship

Pete and Andy explore how AI is creating unprecedented opportunities for entrepreneurship and individual agency, examining both the positive transformations and personal risks in this transitional period.

Key Discussion Points:

Opening & Technical Difficulties (00:00-05:53)

• The boys lost their "finest podcast ever recorded" due to technical issues!

Learning to Code with AI (08:40-23:40)

Andy shares his journey learning to code:

• Moving beyond "vibe coding" to intentional learning through project-based approach
• Using AI as a technical co-founder and mentor rather than just automation
• Structured methodology: Planning with Claude, building with Cursor, reviewing and iterating
• The importance of staying involved in the process rather than abdicating to AI

The "Super Fast Waterfall" Development Process (18:50-22:00)

• Pete introduces the concept of AI-enabled development methodology
• AI excels when given structured frameworks rather than open-ended tasks

Permissionless Leverage and the Golden Age (36:40-45:20)

• Dramatic reduction in barriers to experimentation and starting businesses
• From needing teams, technical co-founders, and investor capital to solo execution
• Shift from audience-of-millions to audience-of-one business models

Challenging Traditional Startup Wisdom (45:20-48:40)

Critique of Andreessen Horowitz founders' claim that small businesses are "meaningless"

• Rejection of the scale-equals-significance mentality- Benefits of lower capital requirements and venture-scale returns not being necessary
• Personal fulfillment vs. world-dominating ambitions
  

The World of Abundance (48:40-55:00)

Drawing parallels to the Industrial Revolution:

• AI as a deflationary force similar to mass production- The Value Trap creating financial incentives for disruption
• Competition eventually driving prices down and creating abundance

Humans as Experience and Observers (55:00-62:20)

Philosophical discussion on the human role in an AI-driven world:

• Humans provide the "qualia" - the conscious experience AI lacks
• People identify problems and improvements while AI handles execution
• Renaissance-style revival where economic abundance enables pursuit of meaningful work

Personal Financial Risk in the Transition (62:20-72:00)

Major concerns about individual exposure during the AI transition:

• 30-year mortgages as problematic in uncertain employment landscape
• Rising interest rate environment making debt service more expensive
• The risk of being heavily leveraged without personal runway

Blue-Collar vs White-Collar Displacement (72:00-75:00)

Short-term risks in traditional "safe haven" industries:

• White-collar displacement potentially flooding entry-level trades
• Importance of finding unique personal value propositions

Creating for Yourself, Not Audiences (75:00-End)

Drawing from Rick Rubin's creative philosophy:

• The value of non-commercial creative pursuits- AI enabling leisure and space for meaningful creative work
• Your job becomes experiencing life and improving its sharp edges for others

Key Insights:

"This is a renaissance for entrepreneurs. If you're entrepreneurial minded, this is just a huge, an amazing time to be alive."

"The cost of experimentation has just dropped precipitously and that is in general good for society."

"Your job is to experience life and to realise where the sharp edges are and to improve them for everybody else."**

Bottom Line: AI represents the greatest opportunity for individual agency and entrepreneurship in generations, but success requires intentional engagement with the technology rather than passive adoption, while carefully managing personal financial risk during the transition period.

The Good Stuff, with Pete and Andy - Episode 7: Rise of the Generalist

Hosts: Pete and Andy (recording at City Beach, Perth)

Episode Overview: In this episode, the hosts discuss automating their podcast production pipeline and explore how AI is changing knowledge work.

They examine the impact of AI on jobs, explaining how it gradually automates tasks at a "subatomic" level rather than replacing entire roles immediately. The conversation delves into effective strategies for working with AI coding tools, the future of work, and why generalists with adaptable skills may thrive in an AI-powered economy.Podcast Production Automation (00:55 - 03:35)- The hosts describe automating their podcast production workflow- Their system handles audio processing, transcription, and content generation- AI tools generate show notes, article summaries, and identify potential clips- The goal is to streamline marketing efforts without manual interventionContent Generation at Scale (03:35 - 06:07)- Discussion of how automated processes save hours of manual work- Possibility of using voice cloning technology

- Creating purpose-built content for different platforms from source materialKnowledge Capture in Organizations (06:07 - 10:44)- Applying similar automation techniques to organizational knowledge management- Capturing and sharing discussions across an organization- Using knowledge graphs to store company information- Creating personalized content delivery based on preferencesAI for Problem-Solving (10:44 - 15:25)- Challenging the criticism that AI can't solve novel problems- Discussion of Pablo's "Tenex agent framework" for problem-solving (https://primal.net/e/nevent1qqs227u92fagkjfwx590qe9z58m6fku9luy3tejylgwy5efz23rzndgqd0h93)- Importance of allowing AI time to work through complex problems- Comparison to human problem-solving processes that also require trial and errorAI's Impact on Jobs (23:30 - 31:20)- Examining how AI impacts jobs at a "subatomic" task level- Discussion of why people don't see their jobs as replaceable- Second-order effects of partial job automation (consolidation, wage impacts)- Historical context of technological disruption and job displacementFuture of Work in an AI Economy (31:20 - 38:35)- Debate on what jobs might remain protected from automation- Potential government responses (regulation, UBI, job programs)- Economic impacts like tax base erosion and inflation*- The shift to generalist skills in uncertain environmentsEffective AI Coding Techniques (57:30 - 1:08:00)- Strategies for working effectively with AI coding tools- Using a sequential approach rather than one-shot generation- The importance of planning before coding- Having Claude as a "project manager" while using Cursor for implementation- Balancing speed with understanding and control

"Your job isn't a whole, it's 200 sub-jobs... and any one of them is automatable already given time and tooling"

The Good Stuff, with Pete and Andy - Episode 6: You Can Just Learn Things

Hosts: Pete and Andy (recording at City Beach, Perth in their van)

Episode Overview: Pete and Andy explore how AI is transforming education and learning, discussing the future education, the power of self-directed learning, what kids should be learning and how AI can positively impact high-quality personalized education.

AI and the Future of Learning (02:50-05:43)

• Discussion about what kids should study in a rapidly changing job market

• Pete's children are developing entrepreneurial skills with AI support

• The "Teddy Fashion Boutique" business Pete's daughter has created

• Exploring game development with AI for Pete's son's tabletop gaming interests

Rethinking Traditional Education (05:43-10:30)

• Critique of the industrial-era "assembly line" approach to education

• The importance of play-based and child-led learning approaches

• How AI can enable a shift from classroom instruction to personalized mentoring

• Questioning the value of traditional education when information costs approach zero

• Personal Learning Journeys with AI (10:30-16:17)

• • Coding with AI assistance
  • How AI provides the patience and personalization needed to build learning momentum
• • The importance of having projects you're motivated to build rather than abstract learning

  
  

  The Intelligent Assembly Line of Education (16:17-20:30)

  • School structure mimics industrial assembly lines
  • AI allows for removing the time constraints on education
  • Learning can become more ad-hoc and follow natural curiosity
  • Education doesn't need to be confined to specific years in a person's life

  Learning Through Knowledge Graphs (47:56-52:13)

  • Using AI to break down courses into concepts, topics and abstractions
  • Creating a "map" of both what exists to be learned and what a person knows
  • Navigating a personalized learning path from current knowledge to desired knowledge
  • AI can identify the optimal path through connected concepts for each individual

  Purpose and Agency in Learning (34:40-37:40)

  • Will AI force people to rediscover purpose beyond jobs?
  • The relationship between agency and purpose?
  • AI as a catalyst for pursuing learning aligned with personal interests

  
  

  Democratizing High-Quality Education (52:13-56:33)

  • How AI can provide the benefits of one-to-one tutoring at scale
  • Using AI to create personalized explanations at appropriate complexity levels
  • The value of learning in context rather than in the abstract
  • Creating immersive, engaging learning experiences tailored to individual interests

  Credentialism vs. Learning (01:01:56-01:15:03)

  • Questioning the value of credentials in a world of commoditized expertise
  • The shift from credential-based systems to meritocracy
  • The permissionless nature of learning with AI vs. permission-based traditional education

  "You Can Just Learn Things" (01:11:12-01:15:06)

  • The democratizing power of AI in allowing anyone to learn anything
  • No need to wait feor permission or formal instruction to pursue knowledge
  • How to use AI tools effectively for learning (even without sophisticated tooling)
  • The inevitable bifurcation between those who embrace self-directed AI learning and those who don't

  Memorable Quotes:

  • "You can just learn things." (01:11:24)
  • "The beauty of play is it doesn't feel like work." (30:44)
  • "We spent most of our adult lives trying to track back to that childlike creativity." (31:04)
  • "I think education is going to change quite drastically." (01:01:30)
  • "It doesn't matter what we say to differentiate ourselves in a market. It's more about what we build and how we prove out the values we want to operate by." (09:27)

The Good Stuff, with Pete and Andy - Episode 5: Billy Big Models

Hosts: Pete and Andy (recording at City Beach, Perth)

Episode Overview: Pete and Andy challenge the belief that more advanced AI models are needed for business transformation, arguing existing models are already sufficient to achieve dramatic cost reductions. They explore frameworks for AI implementation and why businesses should act now rather than waiting for future developments.

Agriculture Mechanization as an AI Parallel (03:40-06:42)

• Before mechanization: 10 farm workers needed to feed 1 person; after: 1 farmer feeds 100+

• Similar dramatic workforce changes could occur in knowledge sectors with AI

The "Billy Big Models" Concept (11:06-15:10)

• Central question: Do we need more advanced AI models for business transformation?
• Pete argues we don't need models better than what existed 9-12 months ago
• Challenging the industry narrative focused on larger models and AGI

Augmentation vs. Agentic Approaches (18:12-22:00)

• Augmentation: Using AI tools to enhance existing human jobs (current focus)
• Agentic: Completely rewiring business processes on an "AI native" standard
• The distinction between "assist" vs. "automate" approaches

Task Decomposition as the Key (23:22-25:55)

• Breaking down jobs into "subatomic" tasks is crucial
• Each agent only needs to do one small task well, not an entire job
• 100 simple agents is exponentially easier than creating one complex agent
• Human tasks ($100) → LLM tasks ($10) → silicon/code tasks ($1)

Traditional Business Model Problems (29:10-32:38)

• Companies adding AI as "tool creep" rather than rethinking from first principles
• Pursuing 5-15% efficiency gains when competitors might achieve 90% cost reduction
• Processes designed around humans remain expensive even with AI tools

E-commerce Parallel to AI Transformation (35:44-39:12)

• Limited approach: existing stores simply adding websites (e.g., Myer)
• Transformative approach: complete rethinking (e.g., Warby Parker)
• Question of whether incumbents will be displaced by AI-native businesses

Obstacles to Business Transformation (43:56-49:57)

• Lack of understanding about AI implementation approaches
• Insufficient intent, time, and money to transform operations
• Middle management's disincentives to reduce team size
• Waiting for "AGI" as an excuse for inaction

The "Learn to Surf" Analogy (53:28-55:51)

• Business transformation requires reading patterns like a surfer
• Technology shifts as waves that businesses must learn to ride
• The ocean/wave is more powerful than you - you must adapt to it

Agency as the New Competitive Advantage (56:46-01:00:02)

• High-agency individuals will benefit most in the next 5-10 years
• Agency may become "the new IQ" for harvesting opportunity
• The need for adaptability rather than rigid expertise

Advancements Beyond Bigger Models (01:03:40-01:10:45)

• Recent key advancements weren't bigger models but new techniques:
• Multi-agent architectures mirroring how teams of people approach problems.

Notable Quotes:

• "If you're sat around waiting for AGI and AGI takes 10 years, and right now I can take 80% of the cost out of a business line, I will crush you in the market."
• "What would this process look like if I now had unlimited access to intelligence?"
• "Agency is going to be the new IQ. That's the standard for harvesting opportunity."