▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen

👉 Let's connect on LinkedIn — send me a request and mention the podcast.

In this episode of my micro-podcast, I break down the 3 business ops B2B software and service founders should automate first — the ones that quietly eat 40–50% of revenue.

Most founders scale the expensive way. More clients means more people to deliver, and operating costs climb right along with revenue. That's running faster on a treadmill — a lot of sweat, same spot.

After 8+ years in the service business, I see the same three areas bleed money in almost every company I look at. All three are mostly copy-paste work, and AI automation cuts 30, 50, sometimes 80–90% of that cost — without cutting people:

1. Proposals — stop rebuilding the same 80% across Google Docs, Canva, and PowerPoint every time. Your rep sends the offer while the deal is still hot
2. Contracts — when the client says "I'm ready," the contract goes out in 15 minutes, not two days. Pick options from a questionnaire instead of typing fields by hand
3. Invoicing — one click after signature: the invoice lands in QuickBooks, the payment link goes out, and the payment matches itself. This saved one client 20+ hours a month

I also walk through the 3-level scoring system I use to grade each area — Level 0, 1, or 2 — so you know exactly where your money and time leak today.

If you own, fund, or lead a B2B software or service company and your ops costs grow every time you land a new client, this episode shows you where to start.

👉 Want to talk through how to cut your ops costs and scale your company? Email me at [email protected] or connect with me on LinkedIn.

▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen

👉 Let's connect on LinkedIn — send me a request and mention the podcast.

In this episode of my micro-podcast, I break down 7 roles where AI lets you grow output without growing headcount — pulled from real automations I've built with B2B founders.

Pulling from 8+ years working shoulder-to-shoulder with software founders, here's where AI takes the first pass so your small team can take the money pass:

1. Sales Rep — an AI voice bot calls warm leads minutes after they submit a form, before a human rep even sees the notification. The human takes over the second the lead is engaged
2. Web Designer — ship the MVP or landing page while your team's offline. AI does ~90%, a designer with taste refines the rest. Speed wins deals
3. QA Engineer — as dev speeds up, testing matters more. Point AI at the branch, check it against the specs, run it in the browser, and hunt for what's broken
4. Copywriter — feed it everything you've written, set the voice and audience, and it drafts blog content that actually sounds like you — not generic AI mush
5. Data Researcher — turn a name and a corporate email into real research on the company and the person, then pipe it straight into the first call or email
6. SMM Manager — one person runs the whole content pipeline at today's speed: clips, voice, video, lipsync, and graphics
7. Software Engineer — the one role you DO hire. Engineers don't write code by hand anymore. Your harness — not the model — decides how productive they are

If you own, fund, or lead a software product with a small team that struggles to deliver, this episode shows you how to move faster and win more business without growing your monthly burn.

👉 Want to talk through how to scale your software company? Email [email protected] or connect with me on LinkedIn.

Thomas England is the CTO of Origin Smart Controls — a company building software for IoT device management in commercial buildings. Origin came out of the mechanical and electrical engineering world, not the software world. That's the whole point: mechanical engineers and software engineers build the platform together, so it solves the problem the way a building engineer understands it, not the way a developer assumes it. Their clients include the NHS and a major UK broadcaster.

In this episode, Thomas breaks down why velocity is the most dangerous thing AI gave engineering teams, and why point-solution SaaS companies should be watching their pricing very closely.

Topics covered:

• Why most IoT dashboard platforms fail — they give you a toolbox, not a solution
• The engineering triangle: quality, accuracy, velocity — and why AI breaks the balance
• Why you can't blame Claude or Codex when your production breaks
• Two types of AI resistance in engineering teams and how to handle each
• Why point-solution SaaS is in trouble — and what Atlassian should be worried about

If you're an engineering leader figuring out AI adoption, or a founder building in an old-school industry — this episode is for you.

👉 Follow George:

• LinkedIn: https://www.linkedin.com/in/georgehelgesen/
• YouTube: https://www.youtube.com/@georgehelgesen

👉 Follow Thomas:

• LinkedIn: https://www.linkedin.com/in/thomas-england-09334280/
• Origin Smart Controls: https://originsmartcontrols.com/

▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen

👉 Let's connect on LinkedIn — send me a request and mention the podcast.

In this episode of my micro-podcast, I'm breaking down everything I learned in 8 years building software with B2B founders — 10 lessons in 12 minutes.

Pulling from 8+ years working shoulder-to-shoulder with software founders, here's what separates the products that scale from the ones that stall:

1. Integrate from day one — don't ask people to change how they work. Plug into their existing tools. People don't resist technology, they resist change
2. Distribution is not an afterthought — your product won't sell itself. Pay partners for customers who subscribe AND pay, not just signups
3. Prototype at zero cost — build the interface in Claude, show real users, validate, THEN spend on development. No more $50K MVPs nobody wanted
4. Every dollar needs an ROI — run the numbers on every single feature. 5x return? Ship it. No clear return? Skip it, no matter how cool it is
5. Product plus service — sell the service first, then let the product scale what the service delivered. Vsimple and Dig Insights both lead with service
6. Use external teams as extensions — outsource the boring stuff so your core team stays excited. Happy engineers build better products
7. Become AI-native — record every call, automate everything you can, but keep a human in the loop. AI is your co-pilot, not your autopilot

If you own, fund, or lead a software product, this episode gives you a practical 10-lesson framework to audit how you build — before you burn budget on things nobody wanted.

👉 Want to talk through how to scale your software company? Email [email protected] or connect with me on LinkedIn.

▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen

👉 Let's connect on LinkedIn — send me a request and mention the podcast.

In this episode of my micro-podcast, I'm breaking down 7 things every software founder must do to survive while AI eats the SaaS market around them.

Pulling from 8+ years working shoulder-to-shoulder with software founders, here's what separates the products that become indispensable from the ones that get copied over a weekend:

1. Educate your customers — if they can't figure out your product without emailing support, your onboarding is broken. Build real walkthroughs, not help docs
2. Fix customer experience — pick up the phone. Email support is a churn accelerator. Adyen does it right. Stripe doesn't. That gap is a competitive advantage
3. Be more than software — stop selling a login, start selling outcomes. Dig Insights and Vsimple bundle services with their product. That's how you become a growth partner, not a vendor
4. Sell value, not features — Leadfeeder calculated my 25x ROI in the first five minutes. ContactOut just sold me contacts. One closed the deal, one didn't. Train your team accordingly
5. Remove UX bottlenecks — your users aren't telling you where they're stuck. They're just leaving. Use heatmaps and session recordings. Fix what's broken before it kills retention

If you own, fund, or lead a software product, this episode gives you a practical 7-point checklist to audit your product right now — before your customers start building their own version.

👉 Want to talk through how to make your SaaS indispensable? Email [email protected] or connect with me on LinkedIn.

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/

▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen 👉 

Let's connect on LinkedIn — send me a request 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 [email protected] or connect with me on LinkedIn.

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/
• YouTube: https://www.youtube.com/@georgehelgesen

👉 Follow Steve:

• LinkedIn: https://www.linkedin.com/in/stevemast/
• Twenty44: https://twenty44.co/

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
• YouTube: https://www.youtube.com/@georgehelgesen

👉 Follow Ian:

• LinkedIn: https://www.linkedin.com/in/ian-ash-dig/
• YouTube: https://www.youtube.com/@ianash8585
• Dig Insights: https://diginsights.com

▶️ Watch the full video on YouTube: https://youtube.com/@georgehelgesen

👉 Let's connect on LinkedIn — send me a request 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 [email protected] or connect with me on LinkedIn.