# The Good Stuff, with Pete and Andy - Episode 38: The Rise of Vibe Product Manager

**Hosts:** Pete and Andy (New Year's Eve edition at the beach)

Pete reveals he's stopped coding entirely after 12 months of learning—now he just product manages a team of agents. They explore the shift from "vibe coding" to "vibe product management," why Pete built Slack in a day, and the addictive power of tight feedback loops.

Plus: steel-manning the security concerns, why raw dogging agents beats sub-agents, and New Year reflections on why model breakthroughs don't matter anymore.

## Key Moments:

* [02:07] "I learned to code for 12 months. And then I just stopped. It's nuts."

* [02:54] Pete built Slack/Discord in a day: "I shouldn't be able to replace a $20 billion SaaS company in 12 hours"

* [08:10] The addiction: "From nothing to MVP in a day, radically transform it every morning"

* [09:05] Not vibe coding—it's a glorious tool for entrepreneurship and building businesses

* [12:10] Introducing Agora: Slack replacement with integrated Kanban, all Nostr-based and encrypted

* [13:25] Slack's fatal flaw: "Bullshit asynchronous tool because you just lose everything"

* [18:05] Steel-manning the critics: addressing "you'll get hacked" security concerns

* [21:21] Everything encrypted with Nostr keys: "They literally can't steal anything"

* [23:21] Your attack surface: "You're the oil you get out of a peanut—not worth it to hackers"

* [28:03] Raw dogging the base agent—not bothering with sub-agents or elaborate skills

* [31:44] Pete's tried sub-agents many times: "I have always been left wanting"

* [32:33] The breakthrough pattern: specify in 10 minutes, deliver in 5-10 minutes

* [34:15] The 21-minute rule: must complete the loop in 21 minutes or it doesn't work

* [42:04] Mainstream adoption reality: experienced professionals never heard of coding agents

* [47:29] Small business owners are the right audience—different relationship to risk

* [50:09] Small businesses always full of risk: "Your hair is always on fire anyway"

* [51:56] The cottage software developer—1000 true fans model, not billion-user SaaS

* [56:44] Andy's New Year take: bullish on tools, no model breakthrough needed since 3.5

* [57:33] Touch Don't Look success: normal people cross the hurdle in 10 minutes, creativity shines through

**Quote:** "I learned to code for basically like 12 months. And then I just stopped. It's nuts. And I thought, this really is like the way to use these things."

# The Good Stuff, with Pete and Andy - Episode 37: Stocking Fillers - Predictions for 2026

Hosts: Pete and Andy (sporting festive headgear at the beach)

Pete and Andy kick off their Christmas predictions episode with zero preparation and maximum confidence. They tackle the biggest question: what will happen in 2026?

Key Moments:

[00:51] Andy's two-for-one Christmas prediction: most AI predictions won't eventuate, no AGI in 2026

[03:09] Revised timeline: feels more like a 10-year transition than 5 years

[04:02] Pete's first prediction: models become less relevant, focus shifts to agent tooling

[05:40] Are model releases becoming underwhelming? The breakthrough isn't as significant anymore

[05:53] Elon's take: "The whole framework is incorrect—throwing more data doesn't give you intelligence"

[07:08] Why software automation is so valuable: automate software, you get free option on everything else

[08:17] Less discussion about new model releases—when Opus came out, people raved for a few days then moved on

[09:05] Death of one-shot benchmarking: "Nobody uses these things in that fashion"

[10:26] The Presidio Bitcoin example: Gemini 3 got everything wrong because the task was too broad

[12:07] Flow matters: sequential tasks build on previous work, jumping around creates cognitive load

[13:15] Andy's prediction: website development will be completely commoditized

[14:01] Big agencies won't be able to justify high spends anymore—except for enterprise clients

[16:24] The WYSIWYG problem: hard to update flat file websites without developer tools

[18:13] Pete's prediction: agents move out of the terminal

[19:08] The model switching advantage: when one gets nerfed, quickly switch to another

[20:30] Why Goose is better for non-coding tasks: less sandboxed, happier to just do work

[22:06] The spare machine problem: agents need machine access to be powerful

[23:47] Most people still talk about Copilot, not Claude Code or Codex

[24:44] The Excel analogy: "This is like super Excel, why wouldn't you want to learn it?"

[27:06] Calling them "coding agents" creates mental resistance for non-coders

[27:27] The agent becomes the engineer, you become the product manager/technical architect

[30:46] The killer use case isn't software—it's the business you already have

[31:20] Service 10x the market with no additional headcount: "That's insane"

[32:29] Value will accrue to small businesses, not S&P 500 companies with cultural inertia

[33:50] Andy's prediction: AI becomes more politically negative in 2026

[34:36] Politicians will use fear-mongering based on job loss to accrue more power

[36:43] Greater divide between adopters and laggards—companies that embraced AI take big leap forward

[38:38] Small nimbler SMEs will be the standout stories, not big enterprises

[39:32] More of your business can run in software than you thought it could

[40:40] The Replit debate: "Why would I use Replit when I can just change Wingman myself?"

[41:40] Wingman needs the concept of a business inside it—metadata that flows through apps

[44:26] Pete's hot take: large models are a dead end, we don't need bigger models with more data

[45:20] "The model should understand what you're doing, not be responsible for knowing stuff"

[46:40] Fast models over big models: "I think that becomes the rallying cry"

[48:02] The inverse direction: everyone's been focusing on thinking time, slower and more deliberate

[49:12] Speed unlock: "If it took 10 seconds instead of 10 minutes, you'd use it 100 times more"

[51:15] Pete's fundamental belief: "I don't think you want the model to know stuff—it's a bug we ship as a feature"

[52:56] Why domain-specific models don't make sense: graphs do the heavy lifting of knowing

[55:05] Timeline check: specialized models and speed focus probably not a 2026 thing

[57:24] Rise of the Agents: more use, simpler to use, non-coding use cases becoming clear

[58:38] Final agreement: agents are the future, not bigger models

The Good Stuff, with Pete and Andy - Episode 36: AI Fallacies Hosts: Pete and Andy

Pete and Andy tackle common AI fallacies head-on, starting with the "junior developer" myth. They explore why juniors will actually thrive and why we're entering a golden age for small teams.

Plus: reflections from their first Touch Don't Look workshop, the death of traditional SaaS, and why Pete is "insanely excited" about where they're going with Wingman.

Key Moments:

* [01:49] The seating configuration theory: why talking side-by-side works better for blokes

* [02:10] The junior developer fallacy: "Coding AI is here, we don't need junior devs anymore"

* [03:11] The fallacy extends to junior lawyers and accountants—basically all junior roles

* [04:04] Pete's take: juniors actually adopt new tech faster because they don't have baggage

* [04:44] London law firm story: how partners explained the inefficient system

* [05:06] "The associate crosses it all out and starts again, then the senior does the same"

* [05:47] Weighing paperwork to charge: "Six inch file? That's $600,000"

* [06:25] The uncomfortable truth: junior lawyers never added value in the old system anyway* [07:30] Why couldn't a tech-savvy junior lawyer act more like a senior with better tools?

* [09:15] New business models emerge: one senior lawyer with AI could serve 1000 clients differently

* [11:00] SaaS companies are building for the average—your specific needs don't matter to them

* [14:30] The "golden age of small teams" thesis: 2-10 person teams can now compete

* [16:45] Historical precedent: juniors always adopt new technology first (mobile, cloud, etc.)

* [19:20] The real question: will there be work? Not "will juniors be employable?"

* [22:00] Why AI makes protectionism harder—you can't hide that you're not using the tools

* [24:15] People who don't adopt will look obviously incompetent compared to those who do

* [27:30] Traditional education is completely misaligned with what's needed now

* [30:45] The credentialism trap: spending $100k on degrees that don't teach relevant skills

* [33:20] "Buy a Mac Mini, get Wingman, spend a year learning—you'll be miles ahead"

* [36:15] Touch Don't Look workshop debrief: people helping each other, energy in the room

* [38:40] The realization moment: "Wait, this is on my phone? It's real?"

* [42:00] Why cohort-based learning works: people bounce ideas off each other

* [45:30] Speedrun positioning: build a CRM, website, and agent onboarding in 4 hours

* [48:15] Marginal gains model: monthly rapid prototypes for the community

* [51:20] The 1000 True Fans model: economics work when you deliver to a cohort

* [54:00] Why Nostr-based infrastructure solves authentication and authorization for free

* [56:30] "I can just give them a key, they never see it, they can sign into a thousand things"

* [58:00] Pete's excitement: "I've got big plans. Insanely excited about where this goes."

* [59:00] The education business wrapped around tech enablement with AI

* [1:01:19] Final thought: "We've landed on a nice spot"

Quote: "The fundamental fallacy is assuming that the work and the industry and the company is all packaged the same and not that there's some disruption to the business model."

# The Good Stuff, with Pete and Andy - Episode 35: The State of AI Tools

**Hosts:** Pete and Andy

**Guest:** Anthony (Dead Man Oz) - AI enthusiast, open source developer, Perth local Pete and Andy sit down with Anthony at the back of the van to discuss two and a half years of using AI coding tools. From surviving the Claude degradation period to building custom tax software, they explore multi-model planning workflows, the death of white-collar jobs, and what work looks like when kids enter the workforce.

## Key Moments:*

[01:23] Anthony's journey: two orders of magnitude improvement in AI tools over 2.5 years*

[02:14] The Claude degradation period—when the model went retarded for a month*

[04:21] The elaborate fake application: Claude invented entire interfaces that weren't wired to anything*

[08:31] Multi-model planning: Gemini says yes early, Claude next, Codex is anal retentive to the nth degree*

[14:07] Specialized sub-agents that actually work: Atomic Committer and Git rebasing tools*

[16:27] Claude as a "moany little bitch" that always wants permission*

[21:50] Corporate IT won't move quickly—they're too scared of risk assessments*

[23:45] The Excel analogy: vibe coding is the new making an Excel sheet that does a thing*

[27:33] "Previously I would have been like, what? You're going to rock up with Claude Code."*

[35:35] Anthropic study: 1,250 people, 90% find value, but 70% say there's stigma using AI*

[39:05] Protectionism: "If I admit I'm using it, can't they just replace me with AI?"*

[42:01] Pete's hot take: LLMs understand language, not facts—use databases for facts*

[47:38] Do creatives using AI tools become 100x more valuable in the short term?*

[53:04] AI conference shock: 1 in 6 submissions had fabricated references and quotes*

[54:35] Speed isn't raw speed—it's removing the lag of waiting for people and debugging cycles*

[57:09] The breakaway model myth: "Your whole premise is incorrect about escape velocity"*

[59:08] Anthony eliminated his tax agent: built custom software in two weeks*

[1:02:01] The death of SaaS: they need 10 million users, you need it to work once a year*

[1:07:19] Touch Don't Look, Speedrun, Marginal Gains—the full business model explained*

[1:10:20] Beacon project: could integrate with M-Pesa through WhatsApp, perfect for Kenya*

[1:12:09] Anthony's summer project: K-pop demon hunters crossed with Pokemon*

[1:17:09] "You can now do these things. You have more agency. You can experiment more."

The Good Stuff Episode 33: On AI and Design**Hosts:** Pete and Andy **Guest:** Jarrad Grigg, Chief Product Officer at Adapter

Pete and Andy sit down with Jarrad Grigg to explore how AI is transforming design. From Figma Make to DreamFlow, they discuss the gold rush for next-generation design tools, whether AI can be truly creative, and why craft still matters. The conversation challenges assumptions about delegation vs. doing, reveals why Excel runs enterprise, and explores how iteration speed has become the new competitive advantage.

## Key Moments:* [03:22] Jared's "oh shit" moment: train station photo with watch, GPT tells him which train to catch

* [04:46] The design tooling journey from Photoshop 6 to Figma's workflow revolution

* [10:00] The AI design tools gold rush: Figma Make, DreamFlow, and who will win

* [11:03] Hot take: design systems are mostly a waste of time (except now with AI training data)

* [13:42] Why every AI design tool starts with a text box—and why designers hate it

* [17:40] DreamFlow's approach: infinite canvas + prompting + fine-tuning controls

* [20:00] Where does the user come into the design process with these new tools?

* [23:00] Pete's sovereign engineering experience: shipping a new app every week in 5 hours

* [26:00] The $94 million Bureau of Meteorology website disaster story

* [31:00] Will AI lead to standardized, homogenous design everywhere?

* [35:00] The creativity question: AI-generated purple gradients and training data limitations

* [36:08] Pete's pipeline experiments: AI personas walking and talking through problems

* [38:44] Set and setting for AI: changing how we interact beyond the text box

* [42:37] Creativity needs time to breathe—dialogue over delegation

* [46:00] Why UI isn't dead and voice interfaces won't replace visual design

* [49:01] The typing vs. speaking debate: Andy filters ideas through writing

* [50:04] Pete's Excalidraw whiteboard workflow: red boxes, green boxes, organized chaos

* [54:04] Uncomfortable truth: loosely-coupled Excel sheets run the entire world

* [56:45] The cottage industry opportunity: building better tools for individual problems

* [1:00:10] Enterprise problems aren't technical—they're risk, compliance, and people

* [1:05:00] The craft question: does AI destroy or enable it?

* [1:08:18] The essay analogy: learning happens in ancillary exploration, not the output

* [1:10:11] Doing vs. delegating: why delegation produces mediocre results

* [1:13:40] The horse drawing meme: craft is passion and effort over time

* [1:15:01] AI gives designers more time for craft and exploration

* [1:16:32] Pete's realization: work becomes fulfilling when you own the creation process

* [1:19:53] Energy drain vs. energy gain: doing what you want with AI scaffolding

* [1:22:32] It's all about loops: iteration speed is the new competitive advantage

* [1:23:34] The quality triangle shifts when you change the underlying technology

**Quote:** "It gives us more time for craft. It's a freeing tool. If you really enjoy something it's not a job—you're constantly playing with it."

The Good Stuff, with Pete and Andy - Episode 31: Where We've Changed Our Mind on AI

00:22 - Theme: What have we changed our mind on in the last 31 weeks?01:48 - Australian Christmas: hot, beautiful, and reflective03:17 - Human at the edge model: the big shift03:34 - Why being at the edge means understanding less05:10 - Bionic human approach: involved in all decisions09:01 - Working in dialogue with AI (Gigi's approach)10:12 - Collaboration vs abdication of work10:21 - Why collaborative work is more entertaining12:15 - 10x vs 100x speed: choosing fun over max efficiency14:14 - Collaborative work as energy-giving16:02 - Permission-less collaboration: no judgment, no mood18:35 - Prompting tricks: "you're 160 IQ" and senior engineer20:02 - Writing as collaboration, not delegation21:50 - The embodied self: what AI lacks22:49 - Collaboration as the natural way to work with AI25:04 - Multi-agent systems add unnecessary complexity25:10 - Single agent with context from folders27:32 - "Do not write tests, I will test"29:04 - Diminishing returns on complexity29:53 - Test-driven development doesn't work with AI29:59 - Multi-agent systems: sounds good, doesn't work (mid-curve)30:36 - Filling gaps vs doing everything yourself39:31 - Buy vs build philosophy: the big pivot41:07 - Existing organizations are messy creatures42:31 - Timing shift: 5-year to 10-year game42:55 - Knowledge diffusion problem: nobody understands it yet45:41 - Build then buy: prove it first before acquisition46:20 - First principles vs practitioner reluctance46:43 - Paradox: successful businesses resist change most47:48 - Building capital vs burning time on acquisition48:45 - Learning by doing the job yourself50:40 - Backing operators: working in and on the business51:49 - Change management at scale: years of complexity52:03 - Gravitating back toward building from scratch53:20 - Building is more fun than acquiring53:41 - Positive vs negative energy: layoffs vs growth55:42 - Barriers to entry and regulatory hurdles56:46 - Not interested in government-regulated businesses58:37 - Small acquisition vs starting from scratch58:55 - Ownership of growth vs resistance to change01:01:28 - Why sell AI services into large companies?01:01:52 - Leverage paradox: why sell your time?01:02:53 - Nobody really understands AI implementation yet01:03:16 - Soundbite knowledge vs actual understanding01:04:06 - Wrong product: strategy requires understanding first01:05:08 - Training and education as the real market need01:05:31 - Proof of work: you have to do it01:06:01 - Speed running six months of learning