# 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."