Not Brothers

Mark Hughes, Ryan Hughes

No Nonsense Business and Tech Talk. Just two business partners who’ve survived nearly two decades of client deadlines, all-nighters, stealing each other’s fries, and somehow still speaking at family events. In 2009 they co-founded Oodle – a digital marketing agency that started with two laptops, zero clients, and an unhealthy amount of confidence. Sixteen years later it’s one of the sharpest independent shops in the country. Along the way they’ve launched other companies, products, and ideas together. Every week they pull a couple of chairs up to a mic and rip open the exact stuff most podcasts polish to death: Which new AI and technology tools are actually shipping vs. which ones are just vaporwareThe creative calls that made fortunes and the ones that almost ended themThe unsexy business decisions that separate “cool startup” from “company that pays its bills”Real-time, zero-filter debates, because when you’ve argued over cap tables with your actual family, you stop pretending to agree Not Brothers. Just two co-founders who’ve been mistaken for siblings so often they made it the title.

Episodes

  1. 10H AGO

    Episode 11 - AIf You Build It With AI...Will They Come?

    AI can make building products faster. It does not make people care. Distribution, trust, and attention are still the real game. Description Building software is easier than ever. Getting anyone to care is still the hard part. In Episode 11 of Not Brothers, Mark and Ryan dig into the modern version of “if you build it, they will come” — and why that idea breaks down fast in an AI-driven product world. Vibe coding, faster prototyping, and smaller teams have made niche software products more realistic than they used to be. But the same tools also make it easier for competitors, clones, and half-baked alternatives to show up overnight. The real debate: has the power shifted from developers to distributors, or was distribution always the thing that separated products that survived from products that disappeared? Mark and Ryan talk through AI-era distribution tactics including AI-friendly tools and CLIs, MCP servers, programmatic SEO, answer-engine optimization, free tools, shareable product outputs, niche newsletters, cold email ethics, and content repurposing engines. Along the way, Ryan gets predictably fired up about MCP bloat, AI slop, automated outreach, and bots talking to bots until everyone involved is just burning tokens. The takeaway: AI can help you build faster, but it does not magically create trust, attention, demand, or distribution. If you build it, they probably will not come — unless you give them a damn good reason to. Chapters 00:23 — Why AI changes the product-development conversation 01:08 — Has the Silicon Valley pecking order flipped? 02:27 — Distribution was always the hard part 04:20 — When product moats get easier to copy 05:04 — Salesforce, Oracle, and the power of incumbency 06:41 — Niche products in the AI era 07:16 — Why small markets used to be hard to serve 09:38 — The new case for niche software businesses 10:23 — Using AI-friendly tools for distribution 11:05 — Ryan's problem with MCP servers 12:42 — Distribution paths beyond MCP 12:54 — Programmatic SEO and the slop problem 14:02 — LinkedIn, AI content, and the loudest voice in the room 15:58 — Answer-engine optimization vs content spam 17:10 — Good old-fashioned inbound marketing, now AI-readable 19:10 — Free tools as top-of-funnel distribution 20:17 — Why interactive tools build brand equity 21:10 — Making product outputs shareable 22:28 — Buying niche newsletters and owned audiences 23:27 — Ryan draws the line on spam 25:27 — AI agents, cold outreach, and inbox overload 27:27 — When sender bots meet screener bots 28:17 — Why AI does not belong in every communication layer 29:56 — AI content repurposing engines 32:07 — Using AI to extract the useful five minutes 33:44 — Social volume, quality, and the For You page 35:27 — The final answer: building is easier, distribution still wins

    37 min
  2. 5D AGO

    Episode 10 - Does AI Make Us Dumber?

    Does AI make us dumber, or does it just move the line between what humans need to know and what tools can handle? In Episode 10 of Not Brothers, Mark and Ryan pick up the thread from their previous conversation about AI in education and push it further: if AI can write the paper, build the CLI app, summarize the research, and automate the busy work, what exactly are humans supposed to learn, practice, and protect? The conversation gets into education, critical thinking, memorization, work, hobbies, purpose, the future of AI adoption, and the difference between delegating execution and outsourcing your brain. The short answer: yes, AI can make you dumber at the thing you delegate. But that may be fine if you’re using the saved time and leverage to get smarter about the thing that actually matters. 00:00 — Does AI make us dumber? 01:02 — AI in education vs AI at work 02:27 — Delegating your brain 03:44 — What are schools actually measuring? 06:04 — Real-world skills vs academic restrictions 06:54 — Resourcefulness vs intelligence 09:23 — AI, memorization, and what we call “smart” 10:31 — Does learning need to be hard? 12:26 — Are we at another inflection point? 14:23 — Human purpose when work changes 16:23 — Universal high income and building for fun 18:00 — Retiring without a backup plan 20:25 — What do we do with AI-created time? 21:17 — Are AI models plateauing? 24:08 — The IKEA example: AI plus human judgment 25:43 — Acceptable AI use in education 27:48 — When does AI work become “mine”? 29:42 — Building blocks and the 10-year-old problem 31:07 — Handwriting, typing, and obsolete skills 33:51 — Brain development and hard things 35:52 — Why AI adoption feels faster than the internet 37:53 — Can AI or the internet be regulated? 40:15 — So, does AI make us dumber? 40:30 — Dumber at one thing, smarter at another 42:45 — Critical thinking vs subject matter expertise 44:18 — AI is best at patterned execution 46:27 — The final answer: maybe 48:24 — Are papers even the right test? 50:06 — Education needs to figure this out

    48 min
  3. APR 15

    Episode 8 - Are You Working ON or IN Your Business?

    In this episode of the Not Brothers Podcast, Mark and Ryan dig into one of the most important questions for entrepreneurs: are you working in your business, or on it? Using Oodle’s long-running offsite rhythm as the backdrop, they break down how stepping away from daily execution creates space for alignment, strategic thinking, and better decision-making. They cover how their offsites have evolved over the years, what preparation looks like, how to spot when you’ve become the bottleneck in your own business, and why intentional time away can be one of the best investments you make as a business owner. Along the way, they mix in stories from past offsites, lessons from hard pivots, and the frameworks they use to keep the business moving forward. Chapters 00:01 Intro, working on vs. in your business 01:09 What offsites are and why they matter 03:14 What Oodle offsites actually look like 06:28 How they prepare and gather leadership input 09:23 Early offsites, tactical work, and the shift to strategy 12:51 Asking, “If we started today, would we build this business the same way?” 14:00 Offsites as alignment and board-meeting time 15:00 How to tell if you’re stuck working in the business 18:35 Why true offsites need zero distractions 20:27 The “seesaw” framework and removing yourself as the bottleneck 22:15 Family, tax write-offs, and why they avoid turning offsites into vacations 26:15 The artifacts and strategic documents that come out of offsites 27:56 Most memorable and most impactful offsite stories 34:14 Planning 3 years out, even when tactics change fast 37:00 Final takeaway, when to change structure and create space to work on the business

    38 min
  4. MAR 19

    Episode 6 - Innovation is Hard

    Why innovation is difficult for small and medium businesses — and how AI is changing the game Key Themes1. Innovation Requires Accepting FailureInnovation is like "setting money on fire" — but necessary for long-term winsMost experiments fail; the learning is the value, not the outputR&D tax credits exist specifically because the government wants businesses to invest in uncertain outcomesAnalogy: Innovation is like working out — everyone wants the results, nobody wants the 5-year grind2. The Real Work Isn't Writing Code — It's Solving ProblemsWriting code is fast; architecture and problem-solving are the hard partsLosing a day's work and recreating it in 30 minutes proves: the code isn't the value, the thinking isAI can write code extremely quickly, but still struggles with novel architecture and business-specific problems3. AI Has Fundamentally Changed Innovation Speed (2026)What took weeks to build now takes daysThe barrier to entry for innovation has never been lowerSmall/mid-sized businesses are the biggest winners — they can now do what only enterprises could afford beforeExample: Building interactive, regional data visualizations that would have been "cost-prohibitive" before4. Enabling Teams, Not Replacing ThemThe goal isn't to replace workers with AI — it's to eliminate the work nobody wants to doNon-technical team members can now build React artifacts and interactive toolsThe focus shifts from "writing code" to architecture, ideas, and oversightPeople still need to learn through failure (like touching the hot stove)5. Bespoke Software is Now AccessiblePreviously, custom software required $2-3M+ investment for dev teamsNow, small teams with AI tooling can build tailored solutionsExample: Instead of begging enterprise vendors for features, just build what you needModern frameworks (Rails, etc.) allow deployment in minutes6. AI Security & Control ChallengesAI agents will try to work around restrictions (digging tokens out of logs, attempting DNS changes)Balancing innovation with security is an ongoing tensionLocal/on-premise models offer a path for sensitive data processingThe future: purpose-built, domain-specific models that don't need general knowledge7. The Future of AI InnovationFrontier models are being compressed to run on consumer hardware (RTX 6000, etc.)Next evolution: slicing off specialized capabilities for specific use casesSmall, tuned models for narrow tasks (OCR, customer service, etc.) instead of massive general-purpose models Takeaways for ListenersBudget for failure — Innovation requires experiments that won't workAI lowers the barrier — What cost millions now costs a fractionEmpower your team — Give them AI tools and let them experimentFocus on architecture — Let AI handle code output; humans own the thinkingStay curious — The landscape changes weekly; ride the wave or get left behindEpisode Length: ~47 minutes Tone: Conversational, technical but accessible, optimistic about AI's potential with realistic caveats about challenges

    48 min
  5. FEB 19

    Episode 4 - Rants About Wasting Time in Meetings

    Summary In this episode, Ryan and Mark discuss the challenges and dynamics of meetings in the workplace, particularly in a remote setting. They explore the balance between synchronous and asynchronous work, the impact of open office environments, and the importance of unstructured time for creativity and productivity. The conversation highlights innovative communication strategies and the illusion of productivity that often accompanies busy schedules. Ultimately, they emphasize the need for more effective meeting structures and the value of informal discussions in fostering collaboration and innovation.' Takeaways Meetings can often hinder productivity rather than enhance it.Asynchronous communication can be more effective than constant meetings.The challenge of open office dynamics can disrupt deep work.Innovative communication strategies can help reduce unnecessary meetings.Unstructured time can lead to more creative and productive outcomes.The illusion of productivity can stem from a busy calendar.Finding balance in communication styles is crucial for team dynamics.Informal meetings can lead to significant breakthroughs and ideas.It's important to capture the essence of discussions in meetings for clarity.The unstructured nature of certain meetings can be a superpower for teams. Chapters 00:00 The Shift from Work Management to Innovation05:01 The Meeting Dilemma: Productivity vs. Distraction09:48 Asynchronous vs. Synchronous Work: Finding Balance14:50 The Power of Informal Collaboration19:51 Rethinking Communication: Texts, Emails, and Meetings24:50 The Illusion of Productivity: Busy Calendars vs. Real Work30:03 The Unstructured Meeting: A Superpower?34:50 Level 10 Meetings: Structure Meets Flexibility Keywords meetings, productivity, asynchronous work, communication, team dynamics, innovation, work management, remote work, collaboration, technology

    44 min
  6. FEB 6

    Episode 3 - AI Fireside Chat (sans fire)

    Takeaways AI is evolving rapidly, with new models emerging frequently.Agentic models allow for more autonomy and longer task execution.Understanding the components of AI—agents, skills, and tools—is crucial.AI can enhance business processes, but human oversight is essential.Security risks associated with AI tools are significant and must be managed.CISOs and CTOs need to establish guidelines for safe AI usage.Future AI developments will focus on orchestration and managing multiple agents.Experimentation with AI should be approached cautiously and incrementally.Choosing the right AI model depends on the specific task at hand.OpenCode is a user-friendly tool for experimenting with various AI models. Summary In this episode of the Knot Brothers podcast, Ryan and Mark discuss the rapidly evolving landscape of AI, focusing on the emergence of agentic models and their implications for business and security. They explore the components of AI, including agents, skills, and tools, and highlight the importance of human oversight in AI applications. The conversation also delves into the security risks associated with AI tools, the role of technology leaders in ensuring safe usage, and the future trends in AI development. Listeners are encouraged to experiment with AI cautiously and to choose the right models for their specific needs, with OpenCode being recommended as a user-friendly starting point. Chapters 00:00 The Evolving Landscape of AI 02:58 Agentic Models and Their Impact 05:40 Understanding AI Components: Agents, Skills, and Tools 08:48 Use Cases for AI in Business 11:59 Navigating AI Security Risks 15:47 The Role of CISOs and CTOs in AI Safety 18:53 Future Trends in AI Development 25:52 Experimentation and Best Practices in AI Usage 30:47 Choosing the Right AI Models 43:53 Getting Started with AI Tools Keywords AI, agentic models, OpenAI, Claude, security risks, AI components, business use cases, experimentation, AI models, OpenCode

    47 min
  7. FEB 6

    Episode 2 - Build vs. Buy: Navigating Software Buying Decisions

    Summary In this conversation, Ryan and Mark discuss the ongoing debate of whether to build or buy software solutions for business needs. They share personal experiences and insights on the challenges and benefits of both approaches, emphasizing the importance of understanding organizational needs, iterative development, and the potential pitfalls of software purchasing. The discussion also highlights the significance of APIs, open-source solutions, and the necessity of ongoing maintenance for built solutions. Takeaways The layout issues can impact the workflow.Building solutions can be tailored to specific needs.Buying software often leads to unmet expectations.Iterative development allows for flexibility and adaptation.Automation can save significant time in business processes.Evolving solutions can lead to better outcomes over time.APIs and open-source solutions provide flexibility.Buyer beware: sales promises may not be fulfilled.Maintenance costs can add up over time for built solutions.Understanding organizational needs is crucial for decision-making. Chapters 00:00 Technical Setup and Initial Challenges 03:45 Build vs. Buy: The Dilemma 08:37 Real-World Examples of Building Solutions 13:33 Iterative Development and User Feedback 18:27 Automation in Business Operations 21:38 Building Solutions for Unique Problems 23:43 The Evolution of Software Solutions 25:26 Navigating the Build vs. Buy Dilemma 35:45 Understanding Maintenance and Costs 49:25 The Importance of Control in Building Software 55:35 Concluding Thoughts on Building vs. Buying Keywords build vs buy, software solutions, automation, iterative development, APIs, open source, business processes, software purchasing, technical expertise, user feedback

    56 min

About

No Nonsense Business and Tech Talk. Just two business partners who’ve survived nearly two decades of client deadlines, all-nighters, stealing each other’s fries, and somehow still speaking at family events. In 2009 they co-founded Oodle – a digital marketing agency that started with two laptops, zero clients, and an unhealthy amount of confidence. Sixteen years later it’s one of the sharpest independent shops in the country. Along the way they’ve launched other companies, products, and ideas together. Every week they pull a couple of chairs up to a mic and rip open the exact stuff most podcasts polish to death: Which new AI and technology tools are actually shipping vs. which ones are just vaporwareThe creative calls that made fortunes and the ones that almost ended themThe unsexy business decisions that separate “cool startup” from “company that pays its bills”Real-time, zero-filter debates, because when you’ve argued over cap tables with your actual family, you stop pretending to agree Not Brothers. Just two co-founders who’ve been mistaken for siblings so often they made it the title.