Marketing
We'll Rebuild Your Website — Free
There's a particular kind of website you've almost certainly used this week. You looked up a local charity, a community group, a tradie, a café — and the site fought you the whole way. The menu didn't work on your phone. The text was grey on a slightly-less-grey background, unreadable in daylight. You scrolled looking for a phone number or a form...
There's a particular kind of website you've almost certainly used this week. You looked up a local charity, a community group, a tradie, a café — and the site fought you the whole way. The menu didn't work on your phone. The text was grey on a slightly-less-grey background, unreadable in daylight. You scrolled looking for a phone number or a form and found neither, just a wall of text and a photo from 2014. Maybe you couldn't find the site at all, because searching the organisation's own name turned up everything except them. We see it constantly. And the frustrating part is that behind a lot of these sites are people doing genuinely good work — not-for-profits running real programs, small businesses that are excellent at what they do — being quietly let down by the one thing that's supposed to bring people to their door. In a hurry? This whole article leads to one offer: we'll rebuild a simple website for free for Australian not-for-profits and small businesses. See the free website...
Marketing
GEO, LLMO, AEO: Getting Recommended by AI, Explained Simply
You've heard of SEO — getting found on Google. There's a newer thing now, and it's arrived with three confusing acronyms: GEO, LLMO, AEO. People throw them around like you're supposed to already know...
You've heard of SEO — getting found on Google. There's a newer thing now, and it's arrived with three confusing acronyms: GEO, LLMO, AEO. People throw them around like you're supposed to already know what they mean. Here's the good news: they're all the same simple idea, and you don't need to be technical to get it. LLMO — Large Language Model Optimisation GEO — Generative Engine Optimisation AEO — Answer Engine Optimisation Three names, one meaning: making sure that when someone asks an AI assistant a question your business could answer, you're one of the names it gives them. That's it. Where SEO is about ranking on Google, this is about being recommended by AI — ChatGPT, Claude, Google's AI answers, Perplexity, Copilot. Different place, same goal: be the one people are pointed to. More and more, people don't Google — they ask. "Who does bookkeeping for tradies near me?" "What's a good men's support group in Melbourne?" "Where can I get help with a home-insurance claim?" The AI...
AI Strategy
Be More Ambitious With AI: Become a Maker
You have a thing you've always wanted to make. A book. An app. An album. A body of work you'd actually hang on a wall. A podcast you'd be proud to publish. You've carried it around for years — and...
You have a thing you've always wanted to make. A book. An app. An album. A body of work you'd actually hang on a wall. A podcast you'd be proud to publish. You've carried it around for years — and you never made it, because it needed a skill you don't have, time you couldn't find, or a team you couldn't afford. That excuse just expired. Here's the thing nobody tells you about making something: the idea is the easy part. What stops people isn't imagination — it's the 95% of unglamorous craft between the idea and the finished thing. The second draft. The mixing and mastering. The boilerplate code. The research. The formatting. The tedious, skill-hungry, time-devouring middle that turns a spark into a real object in the world. That 95% is what used to require an expensive team, or years of practice, or both. And that 95% is exactly what AI now does. Which leaves the 5% that was always the point: taste, intent, the reason the thing should exist, and the judgement of whether it's any good....
AI Strategy
Moving Off Bubble: Converting Your App to Code You Own
For five years, Bubble.io was how we built almost everything — so when we talk about moving an app off Bubble, it isn't platform-bashing. We were one of the world's leading Bubble agencies: 50+ projects, a certification-committee seat, hundreds of developers trained. We know exactly what Bubble is worth, and exactly where it stops being worth it....
For five years, Bubble.io was how we built almost everything — so when we talk about moving an app off Bubble, it isn't platform-bashing. We were one of the world's leading Bubble agencies: 50+ projects, a certification-committee seat, hundreds of developers trained. We know exactly what Bubble is worth, and exactly where it stops being worth it. What's changed isn't Bubble. It's that the alternative — a real codebase you own — used to be expensive and slow to build, and now it's neither. Modern development has collapsed the cost of building production software, and years in the Bubble trenches mean we can scope a conversion accurately rather than quoting the fear. Together, those turn "rebuild it as real code" from a daunting quote into a clear decision. A full-stack app is the whole thing: a front end your users see, a database that holds your data, and a backend that runs the logic in between. Converting means rebuilding that as real, owned code — not a proprietary app trapped...
Marketing
Do You Know Where Your Leads Come From?
Here's a question every business owner should be able to answer instantly, and most can't: where did your last ten leads come from? Not "marketing, probably." The specific answer. Which came from...
Here's a question every business owner should be able to answer instantly, and most can't: where did your last ten leads come from? Not "marketing, probably." The specific answer. Which came from Google, which from a referral, which from that blog post, which from the ad you're paying for right now. If you can't answer it, you're flying a plane with the instruments taped over — and it's fine right up until the weather turns. When the pipeline's full, lead flow is easy to ignore. Work comes in, you're busy, and nobody stops to ask why it's coming in. That's exactly when the discipline slips. Then one quarter it goes quiet. And the question that decides whether you recover fast or panic is: which lever do I pull? More content? Turn the ads back up? Chase referrals? Revisit SEO? If you've been tracking, you know which channel actually produces clients and you pull that lever with confidence. If you haven't, you're guessing with money — and you can't retroactively collect data you never...
AI Strategy
SEO vs LLMO: Where They Overlap, Where They Don't, and What to Actually Do
Every week someone asks us a version of the same question: "People are asking ChatGPT instead of Googling — is SEO dead, and should we be doing this new LLMO thing instead?" The honest answer is more...
Every week someone asks us a version of the same question: "People are asking ChatGPT instead of Googling — is SEO dead, and should we be doing this new LLMO thing instead?" The honest answer is more useful than the hype: it's not either/or, and it's not a replacement. The best way to hold it in your head is that the goal has shifted — from ranking a page to being the answer — and that shift keeps most of what you already do while adding a new layer on top. Here's exactly where the two overlap, where they genuinely diverge, and what to do about it. Start with the reassuring part, because it's true: good SEO is a strong base for LLMO. Both a search engine and a language model are trying to find trustworthy, relevant, well-organised content and understand it. So both reward the same foundations: Crawlable and fast — content a bot can actually reach and read (not walled behind heavy JavaScript) Genuinely useful, expert content — Google's E-E-A-T and "helpful content" push is, almost line...
Marketing
The AI-Native Marketing Stack: Replacing SaaS With AI, Git and No Lock-In
Open a typical marketing team's billing page and you'll find a stack of rentals: a copywriting AI, a landing-page builder, an email platform, a social scheduler, an SEO suite, an analytics dashboard, a form tool. Each is $30–300 a month. Each holds a slice of your data, your templates and your workflows — and each is a little harder to leave than...
Open a typical marketing team's billing page and you'll find a stack of rentals: a copywriting AI, a landing-page builder, an email platform, a social scheduler, an SEO suite, an analytics dashboard, a form tool. Each is $30–300 a month. Each holds a slice of your data, your templates and your workflows — and each is a little harder to leave than the last. That's not a marketing stack. It's a stack of tenancies. There's now a different way to build it, and we run Momentum's own marketing on it: go direct to the model. A capable AI model — we work with Claude today and rate it highly, but any frontier model will do — plus a Git repository plus your own platform accounts replaces most of the "thinking layer" you're currently renting. Here's the argument, including where it doesn't apply. The core move is to keep the valuable part — the thinking — as plain text in a Git repository you own. Your brand voice, tone rules and banned words. Your campaign playbooks. Your prompts. Your content,...
AI Strategy
From Bubble to AI coding: why one of the world's leading Bubble.io agencies changed how it builds
For five years, Bubble.io was our answer to almost everything. We started Momentum in 2020 as a specialist Bubble agency. We grew a team of 25 around it, delivered more than fifty projects on it,...
For five years, Bubble.io was our answer to almost everything. We started Momentum in 2020 as a specialist Bubble agency. We grew a team of 25 around it, delivered more than fifty projects on it, trained hundreds of people through Momentum Academy, and sat on the Bubble certification committee. If you've read anything in our archive, you've read us at our most Bubble-convinced — and most of what we wrote was true, and much of it still is. So this isn't a takedown of no-code. It's an honest account of why an agency with every commercial reason to keep selling Bubble now builds with AI coding tools — mostly Claude Code — and what that means if you own a Bubble app today. Be clear about why Bubble won in the first place, because it explains what's changed. Traditional software development was slow and expensive. A meaningful web app meant engineers, DevOps, months of runway — and most SMEs simply couldn't buy in. Bubble collapsed that: one capable builder could ship a real product in...
AI Implementation
Bolt-On AI vs DNA-Level AI: Why Surface-Level Adoption Fails
Every week I talk to a founder or operator who says some version of the same thing: "We're using AI, but we're not seeing the results everyone talks about." When I dig into what "using AI" means,...
Every week I talk to a founder or operator who says some version of the same thing: "We're using AI, but we're not seeing the results everyone talks about." When I dig into what "using AI" means, it's almost always the same pattern. Someone on the team has a ChatGPT subscription. Maybe they've turned on Copilot in Microsoft 365. A few people use AI to draft emails or summarise meeting notes. There might even be an AI feature enabled in the CRM. On paper, they're "using AI." In reality, they've bolted AI tools onto fundamentally unchanged workflows. And that's why the results aren't there. Bolt-on AI is what happens when you adopt AI tools without rethinking the processes they're meant to improve. It looks like this: Adding ChatGPT to help draft customer emails — but the email workflow itself hasn't changed Using AI to generate marketing copy — but the content strategy, approval process, and distribution are the same manual steps as before Enabling AI features in your CRM — but the...
Careers
Why Most Software Developers Are About to Become Business Analysts and QA Engineers
Here's an observation that I think most developers aren't ready to hear: the job you trained for is becoming two other jobs — and neither of them is writing code. As AI takes over the act of code generation — and it is, rapidly — the work that remains for human developers looks remarkably like two roles that have existed for decades: the business...
Here's an observation that I think most developers aren't ready to hear: the job you trained for is becoming two other jobs — and neither of them is writing code. As AI takes over the act of code generation — and it is, rapidly — the work that remains for human developers looks remarkably like two roles that have existed for decades: the business analyst and the QA engineer. Understanding what to build. Verifying that what was built is correct. The bit in the middle — the actual writing of code — is increasingly handled by AI. This isn't a distant prediction. It's happening right now in every team that uses IDE-based AI tools seriously. And it has profound implications for how developers think about their careers, how companies hire, and how software gets built. Software development has always been a three-phase process: Understand the problem — figure out what needs to be built and why Write the solution — translate that understanding into working code Verify the output — confirm...
AI Strategy
AI Is Not Faster and Cheaper. It's Better and Different.
There's a narrative about AI that goes something like this: "AI makes things faster and cheaper." It's not wrong. But it's completely superficial. And if that's how you're thinking about AI, you're...
There's a narrative about AI that goes something like this: "AI makes things faster and cheaper." It's not wrong. But it's completely superficial. And if that's how you're thinking about AI, you're going to make bad decisions about where to invest your time and money. AI is not just faster and cheaper. It's better and different. And the gap between those two framings is where all the real opportunity sits. When people think of AI as "faster and cheaper," they look at their existing processes and ask: "How can AI do this quicker?" That leads to predictable moves. Automate the email replies. Generate the blog posts faster. Speed up the data entry. Fine. You'll save some time. But you're still doing the same things you were doing before — just with a slightly faster engine. This is like getting a Ferrari and using it to do your weekly grocery run. Yes, you'll get there quicker. But you're missing the point entirely. Here's what "better" actually means. AI can process hundreds of data...
AI Strategy
The Maths on AI Is Wrong
Everyone's talking about AI replacing jobs. The headlines write themselves: millions of roles automated, entire industries disrupted, mass unemployment on the horizon. But the maths is wrong. Not...
Everyone's talking about AI replacing jobs. The headlines write themselves: millions of roles automated, entire industries disrupted, mass unemployment on the horizon. But the maths is wrong. Not completely wrong — AI will replace some jobs. If your work is routine, repeatable, and well-documented, then yes, a model can probably do it faster and cheaper than you can. That's real, and it's already happening. But here's what the doom-and-gloom predictions miss: if your job is highly skilled or creative, AI isn't replacing you. It's actually creating more work. Since I started using AI seriously, I've launched over twenty projects to explore what it's capable of. Not toy demos — real work. Books, apps, reports, marketing strategies, data analysis. Here's what I've found: my output is 10–100x what it would otherwise be as a single human. I can write a 30,000-word book. I can produce a 10,000-word report. I can build apps, create marketing personas, summarise thousands of notes and analyse...
Founder Lessons
AI Burnout Is Real
Since really digging into the latest AI tools in 2026, I've started more projects than in the previous five years combined. Ideas that would have taken months now take days. Things I never dreamed I could build are suddenly within reach. And I'm burning out. Not from the work itself. From the possibilities. Every time I finish something, three new...
Since really digging into the latest AI tools in 2026, I've started more projects than in the previous five years combined. Ideas that would have taken months now take days. Things I never dreamed I could build are suddenly within reach. And I'm burning out. Not from the work itself. From the possibilities. Every time I finish something, three new ideas appear. Every new feature release opens another door. Every capability improvement makes something else feel achievable. The project list grows faster than I can work through it. The ideas compound. The half-finished experiments pile up. And the nagging feeling that I should be doing more — building more, trying more, shipping more — never goes away. This isn't traditional burnout. Traditional burnout comes from doing too much of the same thing for too long. AI burnout is different. It comes from too much novelty. Too many possibilities. Too many directions that all feel urgent and exciting and achievable. The overwhelm isn't from...
AI Implementation
Do Your Staff Send Confidential Data to AI Servers?
I need you to sit with an uncomfortable truth for a moment: your staff are almost certainly sending confidential business data to third-party AI servers. Right now. Today. They're pasting client...
I need you to sit with an uncomfortable truth for a moment: your staff are almost certainly sending confidential business data to third-party AI servers. Right now. Today. They're pasting client contracts into ChatGPT to summarise them. They're uploading financial spreadsheets to Claude to analyse trends. They're feeding proprietary strategy documents into Gemini to get feedback. They're sharing customer data, internal communications, competitive intelligence, and trade secrets with AI services hosted on servers they don't control, in jurisdictions they haven't considered, under terms they haven't read. They're not doing this maliciously. They're doing it because these tools are genuinely useful, and nobody told them not to. The question isn't whether this is happening in your organisation. It's whether you know about it. Let me paint the picture concretely. In a typical mid-market business with 50 to 200 employees, I'd estimate: 70-80% of knowledge workers use AI tools at least...
AI Implementation
Data Model-Driven AI: Why Your Data Architecture Determines Your AI Ceiling
Every AI implementation that fails has the same root cause. It's not the wrong model. It's not the wrong tool. It's not even the wrong use case. It's bad data. Specifically, it's data that's...
Every AI implementation that fails has the same root cause. It's not the wrong model. It's not the wrong tool. It's not even the wrong use case. It's bad data. Specifically, it's data that's scattered, siloed, duplicated, inconsistent, incomplete, or structured in ways that don't reflect how the business actually operates. And no amount of AI sophistication can compensate for a broken data foundation. This is the conversation that almost nobody is having in the AI adoption space. Everyone talks about tools, models, and prompts. Almost nobody talks about data architecture. And that's why most AI implementations underperform. Think of your data architecture as a ceiling on what AI can do for your business. If your customer data lives in three different tools with no sync, AI can't give you a unified view of a customer. It doesn't matter how good the AI is — it can only see what you let it see. If your product catalogue is maintained in a spreadsheet that's updated manually, AI can't...
Careers
Why People Implementing AI Now May Be Working Themselves Out of a Job
I'm going to say something that might be uncomfortable for people in my line of work: if your primary value is implementing AI solutions, you're building a skillset with a limited shelf life. I say this as someone who runs an AI consultancy. I say it as someone who spends every day helping organisations adopt AI. And I say it because I think...
I'm going to say something that might be uncomfortable for people in my line of work: if your primary value is implementing AI solutions, you're building a skillset with a limited shelf life. I say this as someone who runs an AI consultancy. I say it as someone who spends every day helping organisations adopt AI. And I say it because I think honesty about the trajectory is more useful than pretending the current demand for AI implementation skills will last forever. It won't. And the sooner we're honest about that, the better positioned we'll all be. Right now, AI implementers are in extraordinary demand. Every business wants to get started with AI. They need people who can configure agents, build automations, design workflows, integrate systems, and deploy AI-powered solutions. The market for this skill is hot. Salaries are up. Consultancies are booked out months in advance. But here's the irony: the work of implementing AI is itself a pattern-based, structured activity that AI is...
Founder Lessons
The Golden Age of the Builder-Generalist
I've spent the last decade building things across at least five disciplines I was never formally trained in. Product management, UX design, no-code development, marketing, operations. I was a...
I've spent the last decade building things across at least five disciplines I was never formally trained in. Product management, UX design, no-code development, marketing, operations. I was a physiotherapist for 16 years before any of this. The traditional career advice would say that's a problem. "You need to specialise." "Jack of all trades, master of none." "Pick a lane." I disagree. And in 2026, I think the evidence is overwhelming: we're living in the golden age of the builder-generalist. A builder-generalist is someone with working-level competence across multiple domains — product, design, technology, marketing, operations — who uses that breadth to actually build and ship things. The emphasis is on "builder." This isn't about knowing a little about a lot. It's about being able to execute across multiple disciplines well enough to create something complete and valuable. A builder-generalist can: Define a product based on real user needs Design a user interface that's functional...
AI Strategy
Don't Underestimate the Inertia of the Public Sector
Every AI prediction follows the same script: massive disruption, entire industries transformed, everything changes overnight. And in some parts of the economy, that's roughly true. Startups move...
Every AI prediction follows the same script: massive disruption, entire industries transformed, everything changes overnight. And in some parts of the economy, that's roughly true. Startups move fast. Tech companies iterate weekly. Private sector organisations with strong leadership can pivot in months. But the public sector? For-purpose organisations? Government agencies? They were built to resist exactly this kind of change. And that's not a bug. It's the whole point. There's a reason the world's most successful societies have stable bureaucracies. Predictable institutions, consistent processes, and cautious decision-making create the foundation that everything else is built upon. Business can move fast because government moves slow. Startups can take risks because regulators provide guardrails. Innovation thrives precisely because there's a stable, boring, dependable layer underneath it. The public sector's conservatism isn't a weakness. It's load-bearing infrastructure. And AI —...
