Richard Mole @ SDCN: Freight Exchange Tech, Why Copycats Fail

Richard Mole @ SDCN: Freight Exchange Tech, Why Copycats Fail

Richard Mole is the founder of Same Day Courier Network (SDCN) — a well-respected B2B freight exchange marketplace in the UK, built over the last decade without outside investment. Richard has spent his career in transport, growing SDCN into a platform trusted by thousands of couriers, owner-drivers, and large transport companies. In this episode, Richard breaks down how copycats keep failing in this market and why he believes human-first customer service still beats AI in the transport industry. Topics covered: * Why one of SDCN's competitors stopped taking new customers * How Richard built SDCN over 10 years with no investors * Why human-first customer service still beats AI in transport * How competitors literally try to copy SDCN — screenshots, devs, the works * How SDCN helps couriers kill "dead miles" and why TMS integrations are the next unlock If you're a B2B software founder or you plan on building a transport tech solution — this episode is for you. 👉 Follow George: * LinkedIn: https://www.linkedin.com/in/georgehelgesen/ * YouTube: https://www.youtube.com/@georgehelgesen 👉 Follow Richard: * LinkedIn: https://www.linkedin.com/in/richard-mole-2431172b/ * SDCN: https://samedaycouriernetwork.com/

Don't Hire Devshops (I'll Tell You Why)

▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen [https://youtube.com/@georgehelgesen] 👉  Let's connect on LinkedIn — send me a request [https://www.linkedin.com/in/georgehelgesen/] and mention the podcast. In episode #16 of "Backstage Tech", we're walking through a 10-point framework to tell whether you're talking to a real development partner — or a devshop that will burn your time and cash. Pulling from 8+ years working shoulder-to-shoulder with software founders, here's what separates a partner who moves your business forward from a vendor who hides behind documentation the moment something goes wrong: 1. Ownership mindset — devshops spend your money, partners make you money. You feel the difference in the first conversation 2. Founder accessibility — if you can't get anyone with real authority on a call before signing, imagine what happens after you pay 3. Team retention — check LinkedIn before you commit. High turnover is a red flag that tells you everything about the culture 4. Proactive suggestions — order takers wait for instructions. Real partners show up with ideas before you even ask 5. Chase dynamic — if you're always hunting them down for updates, that's your answer. A real partner is chasing you If you own, fund, or lead a software product, this episode gives you a practical checklist to use on your next agency discovery call — before you wire a single dollar. 👉 Want to talk through how to find the right dev partner for your product? Email ogo@procoders.tech [ogo@procoders.tech] or connect with me on LinkedIn [https://www.linkedin.com/in/georgehelgesen/].

Steve Mast: The 3 Steps to Real AI Adoption | Co-Founder @ Twenty44

Steve Mast is an entrepreneur, AI advisor, and co-founder of Twenty44 — a company helping organizations move from AI experimentation to real adoption. Steve spent over 3 decades building digital companies, including Delvinia, where he built Asking Canadians and Methodify before selling to Sago in 2021. Now he's focused on one problem: why 45% of organizations have invested in AI, but only 12% of employees are actually using it. In this episode, Steve breaks down why AI adoption is a people challenge, not a technology one, how Twenty44 diagnoses workforce readiness, and what it actually takes to move organizations from hype to habit. Topics covered: * Why 45% of organizations have AI but only 12% of employees use it * Why most organizations are built on executors — and why that changes everything about AI training * How Twenty44's 3-step framework closes the adoption gap * Why embedding AI inside Salesforce drove more adoption than any standalone app * How to benchmark your workforce's AI readiness before spending on tools * Why AI is the most accessible technology in history — and why that still isn't enough * Whether the Twenty44 assessment platform will become a self-serve SaaS product If you're an enterprise leader or founder trying to turn AI investment into actual results — this episode is the playbook. 👉 Follow George: * LinkedIn: https://www.linkedin.com/in/georgehelgesen/ [https://www.linkedin.com/in/georgehelgesen/] * YouTube: https://www.youtube.com/@georgehelgesen [https://www.youtube.com/@georgehelgesen] 👉 Follow Steve: * LinkedIn: https://www.linkedin.com/in/stevemast/ [https://www.linkedin.com/in/stevemast/] * Twenty44: https://twenty44.co/ [https://twenty44.co/]

Dig Insights Co-Founder: Bolting AI onto legacy SaaS doesn't work

Ian Ash is the co-founder of Dig Insights — a global market research consultancy with its own SaaS platform, Dig One, trusted by McDonald's, Coca-Cola, Meta, Pernod Ricard and dozens of world-leading brands. What started as a traditional consultancy grew into an AI-native market research company with patented algorithms, a 30% compound annual growth rate over its first decade, and a successful exit to Behringer Capital. In this episode, Ian breaks down how Dig Insights evolved from traditional consulting into a tech-driven platform, why "service as a software" is replacing SaaS, and why he came back from semi-retirement because AI is moving too fast to watch from the sidelines. Topics covered: * How Dig Insights went from traditional consultancy to building their own SaaS platform * How their patented "Tinder for products" algorithm predicts market share from simple swipes * Why winning Coca-Cola and Pernod Ricard globally was a step change for the company * Why legacy SaaS companies that bolt on AI get punished * How AI skills and agents are replacing prompt engineering * Why Ian came back after exiting to Behringer Capital If you're a founder, product leader, or investor trying to figure out where AI fits into your SaaS business — this episode lays out the playbook from someone who's lived it. 👉 Follow George: * LinkedIn: https://www.linkedin.com/in/georgehelgesen [https://www.linkedin.com/in/georgehelgesen] * YouTube: https://www.youtube.com/@georgehelgesen [https://www.youtube.com/@georgehelgesen] 👉 Follow Ian: * LinkedIn: https://www.linkedin.com/in/ian-ash-dig/ [https://www.linkedin.com/in/ian-ash-dig/] * YouTube: https://www.youtube.com/@ianash8585 [https://www.youtube.com/@ianash8585] * Dig Insights: https://diginsights.com [https://diginsights.com]

✨ AI Agent Prototyping at $20? 5 Steps From Idea to Production

▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen [https://youtube.com/@georgehelgesen] 👉 Let's connect on LinkedIn — send me a request [https://www.linkedin.com/in/georgehelgesen/] and mention the podcast. In episode #13 of "Backstage Tech", we're walking through a simple 5-step framework to build a custom AI agent for your software product — without blowing your budget on something your users will never touch again. Pulling from 8+ years working shoulder-to-shoulder with software founders, here's what separates the teams that ship AI agents that work from the ones that waste $20-30K and ship nothing: 1. Start with the right problem — not every workflow deserves an agent. Ask yourself: where do your users spend 80% of their time? That's your starting point 2. Define input and output before anyone opens a code editor — a plain-text description of what goes in and what comes out is worth more than 3 weeks of dev time spent guessing • Validate for the price of a coffee subscription — a Claude Project or MyGPT with your real data can tell you if the idea holds water before you spend a dime on engineering 3. Turn your prototype into a spec — the master prompt you tested becomes the foundation of your PRD. It's not glamorous, but it's the thing that keeps your build from going sideways 4. Understand what you're actually paying for — LLM costs can be invisible until they're not. Knowing your token burn per action is the difference between a smart feature and a financial surprise If you own, fund, or lead a software product, this episode gives you the exact playbook to go from "I have no idea where to start" to a tested, documented, cost-aware AI agent. 👉 Want to talk through how to implement this for your product? Email ogo@procoders.tech or connect with me on LinkedIn [https://www.linkedin.com/in/georgehelgesen/].