Intelligence Snacks

Intelligence Snacks
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Intelligence Snacks is a low-fi dialogue with Pete Winn and Andy David. Each week, we share our everyday experiences working with artificial intelligence and how it's fundamentally changing the rules of work and business, the economy, entrepreneurship, and human potential. Expect a mix of chats out of the back of a van at the beach, walking interviews and general use of dialectic and discussion with insightful guests that lift the lid on complex topics. Chilled out, minimal jargon, authentic.

  1. 8h ago

    Intelligence Snacks 79 - Cloud Agents

    Can AI agents work for you without having a permanent computer? Pete and Andy explore cloud agents, temporary computing environments and why an agent's identity, memory and tools can persist even when its computing resources don't. Pete explains his work on Wingman Lite and agent swarms through Ambulando and NStack, and how shared infrastructure could make capable agents cheaper and easier to use. The conversation also turns to how people actually work with agents. Pete's Kanban boards are becoming records of work rather than instructions for humans, while Andy is asking Lara to supervise tasks and orchestrate his Snack Studio pipeline. They discuss building apps before knowing what you want, why some software becomes unnecessary after you've built it, and when you still need to work closely alongside an agent. From there, Pete and Andy examine the limits of human supervision, information security between personal and shared agents, and what happens when AI makes execution and compliance dramatically cheaper. Could smaller companies take on projects once reserved for much larger organisations? And how much of what's possible are we missing because we're still thinking in terms of yesterday's constraints? Key Moments: [01:19] Welcome to Episode 79 and why agents are changing Kanban boards. [03:22] Using Lara to triage another agent's tasks. [04:32] Pete's visual task trees and shaping work without writing every task. [06:54] Does every workflow need its own app? [08:46] Activity dashboards, posting more and changing habits. [09:40] Building a BD app before knowing what it should look like. [11:43] Why it's easier to say what's wrong than specify what's right. [14:57] Snack Studio and discovering you don't need the app you built. [17:23] Why full agent workspaces still have a place. [19:16] Managing agents versus working alongside them. [20:51] Pete's children and AI-powered research wikis. [23:44] Wingman Lite and easier access to local agents. [26:18] Cloud agent swarms that spin up only when needed. [28:38] Shared infrastructure and the economics of agent computing. [30:11] How agent identity persists without a permanent computer. [32:37] Persistent computers versus isolated cloud agents. [35:16] Personal and shared agents, identity and data access. [39:09] Event-triggered agents that produce reports and shut down. [41:38] Why permissions need to make sense to humans. [44:09] Can human supervision keep up with agent swarms? [45:38] Why AI slop is a problem of care and attention. [47:47] Falling legal costs and new opportunities for smaller businesses. [50:12] Morphic fields, intuition and how things take shape. [54:50] Why changing constraints could reshape whole businesses. [56:52] "Why not us?" and unlearning limits on ambition. [59:33] How AI could reduce the advantage of big organisations. [01:02:08] Being early without running out of money. Projects and ideas mentioned: Ambulando, NStack, Wingman, Wingman Lite, Autopilot, Snack Studio, Lara, Rick, Kindling, Excalidraw, Manus, Muse, cloud agents, agent swarms and morphic resonance. Find out more: ambulando.io, intelligencesnacks.com Closing thought: "Be early, be solvent." — Pete

  2. Oct 29

    Intelligence Snacks 78 - The Last Invention

    Is AI humanity's last great invention? Pete and Andy question whether it's really the biggest technological breakthrough in history, comparing it with electricity, the steam engine and the internet. Is AI fundamentally different, or does every generation believe it's living through an unprecedented revolution? They explore what intelligence means, whether AI can possess agency without desires of its own, and why humans still need to find problems worth solving. Could cheaper intelligence unleash an explosion of innovation, enable much smaller companies to tackle bigger problems, and change the value of human work? Pete shares his latest work on Ambulando's native apps, while Andy discusses designing software through interactive canvases. They also question the predictions surrounding AGI, the future of software businesses, and whether AI might be another chapter in humanity's long history of technological change. Key Moments: [01:19] Pete's new native Mac, iPhone and Android apps. [03:46] Andy's interactive canvas and the future of Figma. [06:25] Why chat is a blunt instrument for AI agents. [07:59] Is AI history's biggest technological breakthrough? [09:47] Comparing AI with electricity and the printing press. [11:12] Lessons from previous technological revolutions. [12:20] Multiplying intelligence versus physical labour. [14:54] Energy, hardware, regulation and AI's constraints. [16:16] The human bottleneck in AI workflows. [18:12] When AI agents spend too long testing. [21:01] The advantage of knowing how to work with AI. [22:34] Is AI just another tool? [25:04] What does intelligence actually mean? [27:07] Can intelligence exist without desire or agency? [28:22] Why automating marketing doesn't guarantee customers. [31:24] Could AI unleash an explosion of inventions? [33:23] Invention versus innovation and solving real problems. [35:47] Why human experience matters to problem-solving. [38:52] Could embodied AI develop its own needs? [39:45] Smaller companies tackling much bigger problems. [41:41] Why AI slop is really about care and attention. [42:52] B******t jobs, displacement and UBI. [45:57] The human role when intelligence is on demand. [49:22] Could humans leave the internet to AI agents? [50:22] AGI, recursive self-improvement and magical thinking. [52:13] Subordinated agency and delegating decisions to AI. [56:02] Human beings, human doings and robotic work. [59:37] Why original thinking becomes more valuable. [01:00:38] Autonomous mining trucks and changing constraints. [01:03:02] Why AI could reshape traditional SaaS businesses. [01:06:57] Are we overestimating AI's historical significance? [01:08:48] Why every breakthrough might feel like the last. Projects and ideas mentioned: Ambulando, Wingman, Nostr Browser, Zap Store, Swift, Kotlin, Figma, Claude, ChatGPT, Basecamp, Salesforce, Jevons Paradox, Maslow's hierarchy of needs, AGI, recursive self-improvement, universal basic income and autonomous mining trucks. Find out more: ambulando.io, intelligencesnacks.com Closing thought: "If AI can't experience the problem, how is it gonna solve the problem?" — Andy

  3. Oct 23

    Intelligence Snacks 77 - New Ways to Work With AI

    What comes after AI chat? Pete and Andy explore why traditional chat interfaces struggle as AI agents take on more work, and how visual workspaces, interactive canvases and personalised interfaces could offer more natural ways to think, plan and collaborate with agents. Pete shares his latest experiments with Ambulando, building a spatial canvas where documents, task lists, whiteboards and small applications sit alongside each other, connected to the same underlying information. The discussion turns to how AI is changing the economics of work. When agents can build something faster than humans can read its specification, traditional approaches to planning, documentation and project management start to make less sense. They also explore how individuals might develop their own ways of working with AI, from voice-driven agents to visual planning environments, and what this means for businesses. Could companies become dramatically smaller as agents take on more execution? And if automated production becomes available to everyone, do human judgment, originality and trusted relationships become more valuable? Key Moments: [01:40] Pete introduces visual interfaces and the challenge of managing multiple AI agents. [03:41] From terminal sessions to Autopilot and Ambulando, evolving how agents are managed. [08:30] Experimenting with spatial canvases and small applications called naplets. [11:06] Combining structured data, whiteboards and task lists in one visual workspace. [13:37] Bringing live documents and project information into a canvas through Nostr Stack. [17:01] Andy on the limitations of chat and his experiments with agent-accessible visual planning. [19:48] Exploring interface designs, comparing versions and editing directly on a canvas. [23:00] Why AI-generated documentation is becoming harder for humans to keep up with. [25:00] Which documents still matter when building is quicker than specifying? [28:13] How AI is changing the timescales behind planning and software development. [31:11] Why visual schematics can make complex systems easier to understand. [38:43] Temporary workspaces and the challenge of managing multiple projects. [40:44] Turning comments into conversations with agents directly inside a canvas. [43:51] One set of information, multiple interfaces, including voice-driven agents. [46:00] Why long-running chat threads become difficult to manage. [49:02] Personalised AI workflows versus standardised enterprise software. [51:30] Automating photo editing through Claude without changing familiar workflows. [54:58] Should organisations prescribe how people work or focus on outcomes? [57:41] Different interfaces for dispatching, discussion and strategic planning. [59:55] Building prototypes as a way of thinking through ideas. [01:02:33] How multiple humans collaborate when everyone has their own AI agents. [01:04:42] Could AI make four- or five-person companies the optimal size? [01:08:34] Why automated marketing production may lose value as it becomes ubiquitous. [01:11:32] Authenticity, originality and trust in an internet filled with AI-generated content. [01:13:15] Kevin Kelly's 1,000 True Fans and the value of established relationships. Projects and ideas mentioned: Ambulando, Autopilot, Wingman, Flight Deck, Nostr Stack, naplets, Rick's Artifacts, Bitcoin Bush Bash, Excalidraw, Miro, Claude, ChatGPT, Lightcraft, Matt Pocock's Grill Me and Wayfinder, Pieter Levels and Kevin Kelly's 1,000 True Fans. Find out more: ambulando.io, intelligencesnacks.com Closing thought: "Maybe this is what I was building to all along." — Pete

  4. Oct 15

    Intelligence Snacks 76 - Humanmaxxing

    Pete and Andy welcome Skyler from Finite.Computer to discuss building agents that give people more room for human work: exercising judgment, developing taste, finding meaningful problems and connecting with others. Skyler introduces Finite.Computer, the company he is building with Paul Miller, and its hands-on agent camps for freedom-focused organisations. He describes his shift from design work to building AI products, and why taste still matters when software becomes cheap to create. Knowing what is good, explaining why and deciding whether something should exist remain skills worth practising.It then takes a philosophical turn into embodiment, faith, beauty and what gives work meaning. “Humanmaxing” becomes the organising idea: let computers handle the digital drudgery while people lean into the experiences and relationships that make them human. **Key Moments:** - [00:05] Welcome to Episode 76 with special guest Skyler. - [01:13] Introducing Finite.Computer: agents built toward sovereignty, paired with in-person training. - [03:44] Early agent camps, working with Paul Miller and turning the training into a product. - [06:04] Skyler’s move from client design work to experimenting with AI and building a company. - [07:58] Defining taste: knowing what is good or bad and being able to explain your reasons. - [10:55] Novelty, differentiation and why good taste also means understanding the context. - [13:33] Enterprise software and the economics that pushed products toward standardisation. - [18:55] Could an agent become a protective barrier between you and distracting interfaces? - [21:10] Pete introduces Ambulando: managing agents while you go out walking. - [24:03] Reviewing proposed changes through live visual prototypes and comments before implementation. - [26:00] Andy on computer use, personal preferences and turning repeatable work into code. - [29:27] Beyond the builder bubble: does everyone actually want to make their own software? - [31:30] Pete’s case for a more local software industry with accessible providers. - [33:16] Finite’s human approach: training, shared meals and helping people work through ideas. - [35:11] Turning an HRF presentation into a shared canvas where comments become agent-made edits. - [41:27] Real-world experience and community help people discover which problems need solving. - [43:09] Teaching design thinking and the five whys alongside agent skills. - [46:31] Skyler questions a picture of humanity centred entirely on intelligence. - [51:11] Cathedrals, beauty and building for something beyond immediate economic rewards. - [52:39] How everyday practices shape what people value and desire. - [57:48] Could AI help bring back the individuality and community of the old high street? - [59:50] Humanmaxing: freeing people from digital drudgery and leaning into human abilities. - [01:02:52] Why ownership matters when a business becomes software and agents. - [01:04:44] Open-weight models for everyday work and the pull of frontier capabilities. - [01:06:15] Andy makes the case for raising ambition alongside more capable models. - [01:09:53] Pete introduces Nostr Stack and using a shared identity across applications. - [01:11:42] Authentication, key management, backups and recovery remain difficult design problems. - [01:15:31] Where to find Finite.Computer and a preview of its shared organisational apps. **Projects and ideas mentioned:** Finite.Computer, agent camps, Human Rights Foundation, Paul Miller, Ambulando.io, Rick’s Artifacts, Nostr Stack, Tinfoil, open-weight models, the five whys, Bitcoin Bush Bash and *Desiring the Kingdom* by James K. A. Smith. **Find out more:** finite.computer, ambulando.io **Closing thought:** “Lean into your unique abilities as a human and let the computer do the computer work.” — Skyler

  5. Oct 8

    Intelligence Snacks 75 - The Internet After AI

    If AI can imitate a person on a video call, what happens to trust online? Pete and Andy discuss the promise of an infinitely patient language tutor alongside the obvious opportunities for scammers. That leads to a broader question about the dead internet - as public feeds fill with bots and disposable content, could more of our useful online lives move into group chats, trusted communities and real-world connections? Andy introduces Sally, a small MacBook notch app that lets him post and schedule tweets without opening the feed. Pete shares his own work on shipping Wingman builds and finding better ways to direct agents. Editable flow diagrams, whiteboards and small custom editors offer ways to review work, show what needs to change and catch misunderstandings before implementation. The conversation turns to how much documentation fast-moving work actually needs. Pete and Andy weigh lasting reference material against plans that become stale within an hour, and discuss why quicker iterations can help people make better decisions. They finish with Andy’s experiment using Jev to review AI writing: flagging abstraction, unnecessary language and signposting so the drafting agent can improve its writing quality. **Key Moments:** - [00:02] Welcome to Episode 75, recorded back at the beach. - [01:25] A human interaction model prompts two immediate thoughts: personal tuition and convincing scams. - [03:00] Dead internet theory, public feeds and the value of connecting with people you trust. - [03:23] Nostr and the difference between a community of connections and a global megaphone. - [06:16] The retreat into group chats and moderated spaces where people can reject unwanted AI content. - [07:28] AI could amplify both productive work and passive consumption. - [08:21] The appeal of experiences where conversations are neither recorded nor broadcast. - [09:51] Andy introduces Sally: posting to X from his MacBook notch without entering the feed. - [13:51] Rescheduling posts across time zones and being more deliberate about social media use. - [15:56] Exercising the shipping muscle; Pete describes automated Wingman builds for TestFlight and Zapstore. - [18:36] Rick’s Artifacts becomes a place to build small tools for editing, comparing versions and reviewing work. - [20:32] Flow diagrams make components, actions and changes of state easier to inspect. - [24:47] Agree on the current state, draw the future state, then give the agent a clear implementation target. - [28:31] Context trees and wiki-style documents help agents find relevant projects, processes and references. - [33:07] How much documentation do you still need when building and changing software becomes cheap? - [37:38] Working as an individual with agents, and why visible wiki links can be easier to trust than a complex graph. - [40:50] Turning exploratory conversations into focused implementation threads across separate systems. - [43:58] Longer agent runs can weaken the feedback loop; Pete wants to see what the finished change will do. - [47:08] Andy experiments with Jev as a separate reviewer for the Intelligence Snacks writing pipeline. - [51:29] Specific review questions and confidence scores help identify passages that need editing. - [52:58] Could generating several drafts and comparing them produce better writing? - [54:24] The aim for the website and newsletter: summaries that are accurate and enjoyable to read. **Projects and ideas mentioned:** Sally, X, Nostr, Wingman, Flight Deck, Tower, Autopilot, Rick’s Artifacts, TestFlight, Zapstore, Obsidian, visual flow diagrams, context trees and Jev. **Closing thought:** “What matters more is that you can connect to people, not necessarily that you are connected to everyone.” — Pete

  6. Oct 1

    Intelligence Snacks 74 - Normie Mode

    Intelligence Snacks 74 Normie Mode AI model rankings are easy to find. Knowing which model to use for a spreadsheet, a design task or a language lesson is harder. Andy introduces Normie Mode, a new site that turns benchmark data into task-based recommendations that weigh capability against cost. It is an early release, and Andy wants feedback on whether the comparisons are useful to people choosing a model for everyday work. Pete and Andy then ask where agents actually help. A story about an agent negotiating a marketplace sale and sharing its owner’s home address shows what can happen when an assistant has too much freedom. They make the case for letting people choose the outcome they want, then handing agents the tedious steps: completing a booking, finding a meeting time or checking an unwanted subscription. The conversation moves from chat and spreadsheets to documents, custom software and changing business models. It closes with a debate about buying traditional businesses to automate them. Pete and Andy see an opportunity, but argue that industry knowledge, staff relationships and the slow work of change cannot be skipped. Key Moments: [00:06] Welcome to Episode 74 and the unusually early choice of a title.[00:27] Andy introduces Normie Mode: model comparisons built around jobs people actually do.[02:24] Why a useful recommendation has to account for cost as well as capability.[04:58] How the site combines public comparison data with its own task-based tests—and where the early data has gaps.[07:50] Could agents use Normie Mode to choose models for their own work?[09:40] The growing gap between rapid AI progress and what everyday users can reasonably keep up with.[11:27] Why a harness tailored to your work can matter as much as the model inside it.[13:43] A marketplace agent accepts a low offer and shares its owner’s address.[15:17] The case for keeping human contact and judgment in negotiations and plans.[19:29] Let an agent handle the administrative steps after you have made the important choice.[25:33] Documents and slides become first-class AI workspaces; Pete argues for editing and commenting directly on the work.[29:35] Spreadsheets as an accessible programming tool—and whether custom software will replace some of their uses.[37:15] Personal agents could expose subscription businesses that rely on customers forgetting to cancel.[42:58] When AI makes polished promotional video cheap, does its value rise or fall?[47:31] Andy considers the advantage of creators who have spent years building audience trust.[50:50] The pitch: buy an established business, automate its workflows and capture the margin.[53:36] The missing detail: industry knowledge, key people and the difficulty of changing a business already in motion.[59:43] Buy or build? The opportunity is real, but patience and listening to operators matter.[01:04:30] Pete’s preference for owners and staff using AI to solve the problems they know firsthand. Projects and ideas mentioned: Normie Mode, Wingman, Flight Deck, personal agents, AI documents, spreadsheets and AI-assisted business acquisitions. Closing thought: “As always I think AI just rewards agency.” — Andy

  7. Sep 24

    Intelligence Snacks 73 - Model Explosion

    Pete and Andy unpack a week where AI models seemed to multiply overnight: Anthropic updates, OpenAI’s cheaper models, Meta’s Muse, Grokbot, and the more interesting arrival of Jev. The big question is whether we need ever-bigger frontier models, or whether the real unlock is cheaper, faster, more specialised intelligence that can be sprinkled through workflows. The centre of the episode is Jev: a “system one” decision model built for fast classification, confidence scoring, routing and prioritisation. Pete and Andy explore why that matters for business processes, GraphRAG, tool calling, coding agents, fraud checks, refunds, traffic systems, learning graphs and app economics. Then they zoom out to consumer agents: Meta, WhatsApp, network effects, ad businesses, personal automation and whether people will hand their lives to Zuckerberg or choose to own their own agents. **Key Moments:** - [00:06] Welcome to episode 73, now with faces on YouTube. - [01:20] A big week in model land: Anthropic, OpenAI, pricing cuts and model-name weirdness. - [02:58] Are new models genuinely better, or are we comparing them against nerfed old ones? - [05:29] Pete argues for consistency, speed and cost over “more intelligence.” - [06:26] Jev enters the chat as the week’s most interesting model release. - [06:52] Andy tests Jev through OpenRouter on existing workflows. - [08:16] SEO signals, prioritisation and replacing vibe-based confidence scores. - [10:06] RLHF versus reinforcement learning via calibrated decisions. - [12:27] Why structured JSON decisions matter for automation. - [15:46] GraphRAG, context selection and cutting minutes of agent prep down to seconds. - [16:40] Refunds, fraud checks and business workflows where confidence changes the routing. - [18:28] Human escalation, graph traces and feedback loops for better decisions. - [19:33] The economics: why frontier models are overkill for simple sorting and routing. - [21:57] Jev as automation-native, not chat-native. - [23:45] Browser use is still painful when every mouse move costs time and tokens. - [24:08] Why Jev makes old ideas like Beacon feel interesting again. - [25:44] Open-source Jev-style models and the Intelligence Snacks thesis coming back around. - [27:35] IRL systems: traffic lights, waste, energy and transit routing. - [32:22] What happens to small language models when decision models exist? - [35:12] Intelligence Snack primitives: classification, prioritisation, translation and research. - [38:50] Jevons paradox and near-free judgment everywhere. - [41:47] “Fast is good”: why latency may matter more than bigger benchmarks. - [43:05] Learning graphs for codebases, agents and human understanding. - [47:29] Tool calling, agent loops and where expensive frontier reasoning is wasted. - [50:13] Code graphs, agent context and asking better internal questions. - [52:52] Meta Muse, Grokbot and the mainstreaming of personal agents. - [56:13] Agents versus consumer inertia: insurance, subscriptions and renegotiation. - [59:46] Do network effects beat capability? - [01:02:30] The Meta reservation: agents inside an ad business. - [01:04:43] Torrenting, distribution failures and extractive business models. - [01:08:27] Why own your agent instead of giving everything to Meta or Elon? - [01:12:21] Email is not really about communication; it’s about audit trails and accountability. **Friends of the Pod:** Jared Grigg, John, Justin Moon, Paul **Projects Mentioned:** Jev, TypeSafe, OpenRouter, Anthropic, OpenAI, Astra, Fable, Meta Muse, Grokbot, Instinct, Hugging Face, Beacon, GraphRAG, Autopilot, WhatsApp, Instagram, Amazon, Netflix **Concepts:** Decision models, system one models, calibrated confidence, RLHF, RLCD, model routing, tool calling, GraphRAG, small language models, Jevons paradox, local agents, consumer inertia, ad-driven AI **Quote:** “What you actually want out of these things is very, very quick inference.” — Pete

  8. Sep 17

    Intelligence Snacks 72 - The Internet We deserve w. FIPs!

    Pete and Andy dig into FIPS, the Free Internetworking Peering Service, and why it could make the internet feel personal again. Instead of treating your laptop and phone as viewers of cloud servers, FIPS makes devices, apps and agents first-class participants in a private, addressable network. Then the conversation pivots into AI doom, open-source regulation and whether “AI will kill us all” is really a safety argument, or just another attempt by big institutions to keep power centralized. **Key Moments:** - [00:12] Welcome to episode 72, from the beach. - [01:09] A listener request from John turns into the FIPS explainer episode. - [02:12] FIPS as networking tech: reconnecting computers instead of turning them into cloud viewers. - [04:03] Why today’s internet pushes people into domains, tunnels, accounts and API keys. - [07:07] FIPS addresses, Nostr-style identity and private device networking. - [08:07] Self-organising mesh networks and transport-agnostic routing. - [11:10] Why FIPS gets interesting when complex networking becomes invisible to users. - [11:56] The Google Drive problem: why upload files you already own locally? - [14:14] A demo of browsing files from one computer on another. - [16:30] Andy sees the agent angle: “a game changer for agents.” - [19:14] Flight Deck, Tower and Autopilot as a real Wingman use case. - [21:41] FIPS-addressing apps so they can run locally and be reached from anywhere. - [23:57] The Wingman app browser on phone, laptop and desktop. - [25:43] Scan a QR code instead of buying domains and wiring up Cloudflare. - [26:48] Nostr-based Git and agent-native developer infrastructure. - [32:02] “Apps that aren’t apps”: familiar interfaces over data that stays where it belongs. - [35:46] Organisations as distributed computers made from local machines. - [46:34] Pete’s draft NIP for `window.fips` transport. - [47:56] Nostr plus FIPS as enough to rebuild a better internet. - [52:57] “Dropbox killer”: virtual file systems without central infrastructure. - [54:10] The pivot: Dario, Anthropic and the “AI will kill everyone by 2030” debate. - [56:03] Pete’s proposed AI safety fix: make murder illegal. - [57:32] Andy calls the regulatory push classic cartel behaviour. - [01:02:16] Pushback from Jensen and the open-source AI argument. - [01:07:30] Existing antitrust and anti-competitive laws already matter. - [01:11:06] Are models plateauing, and is regulation a moat? - [01:13:21] Paperclips, recursive self-improvement and defensive AI. - [01:14:14] If the labs are serious, why not regulate themselves? **Friends of the Pod:** John on Nostr, Dan (ngit), Jack, Paul **Projects Mentioned:** FIPS, Nostr, Wingman, Flight Deck, Autopilot, Tower, Google Drive, Cloudflare, GitHub, Forgejo, NGit Workshop, GRASP, DaVinci, Blender, FFmpeg **Concepts:** Private mesh networking, Nostr identity, FIPS addresses, local-first software, agent-native infrastructure, self-hosting UX, device keys, browser transports, open-source AI, AI regulation, cartel behaviour, recursive self-improvement **Quote:** “Nostr plus FIPS, it’s enough. We can rebuild everything now.” — Pete

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About

Intelligence Snacks is a low-fi dialogue with Pete Winn and Andy David. Each week, we share our everyday experiences working with artificial intelligence and how it's fundamentally changing the rules of work and business, the economy, entrepreneurship, and human potential. Expect a mix of chats out of the back of a van at the beach, walking interviews and general use of dialectic and discussion with insightful guests that lift the lid on complex topics. Chilled out, minimal jargon, authentic.

Information

  • Creator
    Intelligence Snacks
  • Years Active
    2025 - 2026
  • Episodes
    79
  • Rating
    Explicit
  • Copyright
    © Intelligence Snacks
  • Show Website
    Intelligence Snacks