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Crazy Wisdom

Episode #568: AI Is Making Everything More Efficient. What Happens Next?

Episode #568 · August 17, 2026 · 59 min

MP3 · Apple Podcasts · Spotify

About this episode

Stewart Alsop sits down with Juan Verhook, founder of Tender Market, for a second conversation that ranges from the mechanics of European public tenders to the future of how we organize digital information. They cover how Tender Market helps smaller companies work around barriers like SOC 2 and ISO certification requirements, the surprising scale of public procurement (roughly 20% of GDP), and how AI and machine learning are reshaping the bidding process. From there the conversation opens up into bigger territory: the changing tolerance for being wrong in an AI-saturated information landscape, how language and culture shape perception, the reverse Turing test and the challenge of verifying human versus AI identity online, and Juan's daily workflow running eight or nine MCP servers through Claude Code. They close out talking about whether the folder and file system will survive the shift to AI-native interfaces, tying back to Stewart's own Stewart Squared episodes on the history of the PC. You can visit Tender Market at tendermarket.eu.
Timestamps
05:00 — Tender Market's origin story and how they help smaller companies work around SOC 2 and ISO certificate barriers.
10:00 — Public procurement and its scale, roughly 20% of GDP, plus a look at public-private partnerships.
15:00 — Local LLMs on a plane with no Wi-Fi, and comparing local model performance to frontier models.
20:00 — Supply versus demand in AI infrastructure and whether hyperscaler token efficiency is quietly improving.
25:00 — Whether AI will replace knowledge work tasks, and the shifting reality of what lawyers and other professionals actually do.
30:00 — Reverse Turing test, digital identity verification, and the idea of a "pre-AI internet."
35:00 — Model poisoning, RLHF, and the difference between pretraining and post-training.
40:00 — Interleaved tool calling and how Tender Market ties pricing to task deliverables instead of billable hours.
45:00 — RAG versus fine-tuning, prompt engineering, and when context windows actually matter.
50:00 — Deterministic programming versus probabilistic agents, and when to build custom tools versus buy existing ones.
55:00 — Juan's daily MCP stack (Supabase, GitHub, Calendly, CRM), and whether the folder-and-file system will survive the shift to AI-native interfaces.
Key Insights
  1. Certification requirements aren't dead ends—they're routing problems. When smaller companies got rejected from tenders for lacking SOC 2 or ISO certificates, Juan didn't turn them away. He found that EU procurement rules allow bidding as a consortium or subcontracting to a certified partner, turning a disqualifier into a workaround that builds trust with clients.
  2. Public procurement is a massive, underexamined market. Roughly 20% of GDP flows through public purchasing of private-sector goods and services, yet most people have no visibility into how tenders work or how governments post and award these contracts.
  3. Being wrong has become more socially acceptable. Juan traced this shift to the falling cost of information: in the Stack Overflow era, giving a wrong answer was costly, but now that answers are instant and abundant, both mistakes and corrections happen faster, changing how people learn and communicate.
  4. Task-based pricing beats hourly billing for AI-era services. Rather than charging per hour, Tender Market prices around the deliverable, winning a tender, which avoids the perverse incentive of hourly billing to be inefficient and instead rewards actually solving the client's problem.
  5. RAG and fine-tuning solve different problems. RAG helps a model reference large documents without hitting context limits, while fine-tuning changes a model's internal weights so it learns new behavior or style. Juan noted that true RAG use cases needing thousands of pages of context are rarer than the hype suggests.
  6. Deterministic code should replace repeated LLM calls once a pattern is found. Stewart described his own workflow: solve a task with an LLM a handful of times, then convert the repeated pattern into deterministic software so tokens are no longer spent on it, freeing the model for genuinely new problems.
  7. AI agents are never truly autonomous. Both hosts agreed that no matter how many steps an agent chains together, a human operator always initiates the first prompt, meaning accountability and intent trace back to a person even in multi-agent systems.
Episode transcript
Stewart Alsop III00:00

Welcome to the Crazy Wisdom Podcast. This podcast is for you. If you have an insane drive to find the truth of things, it's not the good answers that we seek, but the good questions. I interview a range of different guests from many different fields, all with the intention to uncover the simple truths that are hidden in plain sight. Most people don't want to go there. I go there, my guests go there, and you benefit. Please let me know if you enjoy these episodes and as always, subscribe on itunes, Spotify, or wherever you listen to the podcasts.

Stewart Alsop III00:40

M welcome to the Crazy Wisdom Podcast. I've got Juan Verhoek here, for a second interview, and he is the founder of Tendermarket. Welcome back to the show.

Juan Verhoek00:53

Thanks, Stuart. It's great to be back.

Stewart Alsop III00:57

We talked last time a lot about AI, a lot about Europe, a lot about bureaucracy. What have you learned since then?

Juan Verhoek01:07

Well, some of the interesting things is, finding synergies between the pain points that we're trying to solve, how we can help clients, and being able to be flexible enough at an early stage to understand what kind of, propositions and what kind of value proposition we're going to deliver to clients, and really being open to listening to a lot of pain points and coming up with creative solutions for it. So I'll give you an example. back when we were, like, starting with outreach, we had a lot of companies that were like, hey, it's great. Tender seemed like a great marketplace, but we're probably too small for them. And, at some point they were right. But, there was one common objection we kept getting. It's like, oh, we don't have SOC 2, or we don't have ISO certificates. at the beginning I was like, okay, you're not part of the icp. Let's not work with you guys until you're in a bigger. Until you're a bigger company. And then, that's all right as part of, well, as a pipeline. But since we kind of built this funnel that's, through meta ads, for example, and it's actually people that are qualified, but they might not necessarily be at the right stage to reach out the people that we want to target through Google Ads, it was a lot more expensive. And we're sort of figuring out like, hey, what's this pipeline? Where if we keep seeing that these type of companies keep having issues with certificates, one interesting workaround, or loophole in Europe is you're actually able to apply to a tender as a consortium or even as a main Contractor and hire a subcontractor that fulfills those requirements. So you can outsource part of your software through a partner already has an ISO or a SOC 2 certificate. And then we just partner with some outsourcing company to actually offer this as part of our offerings. When somebody's joining it's like hey, actually great that you don't have that. We actually know people and are well connected into that environment and we let them know about this loophole and then you're instantly building that credibility and the trust. it's a win win for clients of Ross.

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