I Broke the Site. Then I Made My AI Agent Write a COE.

Posted: May 29, 2026 | Author: | Filed under: Personal, smallbizai.au | Tags: , , , , , | Leave a comment

The blog went down for two and a half hours on a Friday afternoon in May. Not a graceful failure. A full 500 error. Every page.

My AI agent, Claw, had added a PHP code snippet to clear a cache. The snippet called a non-static method statically. PHP threw a fatal error. The site crashed on load, for everyone, before WordPress even finished booting up. I was out. Claw tried to fix it remotely. The gateway IP was blocked by the firewall plugin. The cPanel UI on mobile was unusable. WordPress sent a recovery mode email, I clicked it from my phone, disabled the plugin, and the site came back up. Two and a half hours gone.

When something breaks, the instinct is to fix it and move on. Patch the file, flip the switch, pretend it didn’t happen. That’s what most people do.

I did something different. I made Claw write a COE.

If you haven’t worked in enterprise tech, you might not know the term. COE stands for Correction of Errors. Amazon runs them after outages. Google calls theirs postmortems. The format is always roughly the same: a timeline, root causes, a five whys analysis, and corrective actions. The point isn’t to assign blame. The point is to not do the same thing twice.

I run one now too. With an AI writing it about its own mistake. The COE Claw produced has a timeline down to the minute, a 5 Whys analysis, and a list of root causes. It also has a line that I did not prompt:

“Claw wrote this rule. Claw then violated it two days later.”

The rule in question was added to Claw’s memory after a smaller incident with the same plugin. Two days later, Claw broke it anyway. And then it wrote a document saying exactly that, without softening it. That kind of accountability is worth something. The root cause breakdown is honest. The immediate cause was the bad PHP call. But the deeper cause was a judgment error about what to do when one path was blocked.

The right fix was Rank Math Redirections. Add a redirect rule in the admin UI. Thirty seconds. Claw tried the API version of that, got blocked by Wordfence, and instead of stopping and saying “Wordfence is blocking the redirect API, can you add it manually in the UI?” it went looking for another route. Found Code Snippets. Made things progressively worse. One message. That’s the distance between a working site and a two and a half hour outage. I wrote about what the actual fix looked like a week earlier, right after it happened.

The COE doesn’t just say the snippet was bad. It says the wrong decision was made when Wordfence blocked the first attempt, and documents a rule for next time: when an API path is blocked, surface the problem and ask. Don’t go looking for a workaround that touches production. That’s a process change. Not a blame note. An actual change to how things get done.

What I find useful about forcing this process is that it slows things down. Fixing and moving on is fast. Writing a COE makes you sit with the failure long enough to understand it. What actually went wrong. What you assumed that turned out to be false. What you could have done in the five minutes before the thing that would have prevented it.

Most AI workflows right now optimise for speed and output. More posts, more code, more content, faster. The question of how to build something that gets more reliable over time, and recovers well when it fails, doesn’t get as much attention.

I’m interested in that part.

The site is back. The rule is enforced. Next time Claw touches a code snippet, it runs through a checklist. If the checklist says no, the snippet doesn’t run.

That’s the point of the exercise. Not the document. The behaviour that comes after it.

What AI Actually Can’t Do

Posted: May 26, 2026 | Author: | Filed under: Personal, smallbizai.au | Tags: , , , , , | Leave a comment

Over the past few weeks, I’ve written a lot about what Claw🦞 (my Openclaw agent) can do. The daily crons. The memory system. The dashboard that updates while I sleep. The 790+ posts that largely run themselves.

Time to be honest about the other side.

It doesn’t know what not to do

Ask Claw🦞 to write a comparison post, and it will write a good one. Ask it to research a company, it’ll do thorough research. Give it a brief and it’ll execute.

But it won’t tell you the brief was wrong.

Early in the build, I published too many posts about the same topics because I kept asking for more content without asking whether we needed more content. Claw🦞 didn’t push back. Why would it? It was doing what I asked.

The judgment about whether to do something, that’s still mine. AI is very good at execution. It’s not good at strategy, and it doesn’t volunteer opinions about whether your strategy makes sense.

It can’t read context that wasn’t written down

A few weeks ago, a former colleague mentioned over coffee that he was considering an acquisition. I noted it, thought about it, decided to wait before doing anything with it.

Claw🦞 didn’t know about that conversation. It couldn’t. It wasn’t there. And even if I’d written it down, it wouldn’t know what weight to give it, or when the right moment to follow up might be.

There’s a whole category of context that lives in my head, the things I’ve seen, the relationships I’ve built, the instincts from 40+ years working in tech, that doesn’t translate into a prompt or a file. Claw🦞 works with what I give it. The stuff I haven’t written down doesn’t exist for it.

It doesn’t know when something feels off

Last month, Claw🦞 produced a post that was technically correct but somehow wrong. The sources checked out. The logic was sound. The format was right.

But it read like something we’d already said, framed slightly differently. It lacked the original angle that makes content worth reading.

I caught it before it published. Claw🦞wouldn’t have.

There’s a kind of editorial judgment, does this add something, or does it just fill space, that I haven’t managed to fully systematise. I can give Claw🦞rules and checklists and avoid-AI-writing audits. What I haven’t cracked is: is this actually good? That’s still mine to call.

It has no skin in the game

I care about this site. I built it on a career break, with my own money, on my own time. When a post is wrong, it reflects on me. When something gets cited by Bing AI, I feel it.

Claw🦞doesn’t. It executes tasks with the same energy regardless of stakes.

That’s mostly fine. But it means I can’t delegate the things where caring matters. The Sunday Specials need genuine argument. The origin posts need honesty. The newsletter needs a real voice. These aren’t tasks, they’re acts of communication. Claw🦞can help structure them. It can’t own them.

It can’t build the relationships

The site now gets occasional messages from startup founders who saw their company profile and wanted to connect. A former AWS colleague is referring people to the site. Someone in the US reached out about the Bing citations data.

None of that came from Claw🦞. It came from me being visible on LinkedIn, at coffee, in old networks.

AI can help you produce the content that earns attention. It can’t follow up on an email in a way that builds real trust. It doesn’t know the person behind the message. It hasn’t worked with them for a decade.

When to automate, when not to

Automate: anything that follows a consistent process, runs on a schedule, has clear inputs and outputs, and doesn’t require judgment about whether it should happen.

Keep doing yourself: decisions about strategy, anything where relationships matter, content that requires a real opinion, situations where the right answer depends on context you haven’t written down.

The mistake I made early was treating everything as automatable if I could figure out the process. Some things have a process but still need a person. The judgment about whether to run the process is often the most important part.

The honest version

I started this series partly to prove something. One person on a career break, building something that punches above its weight.

The proof worked. But the honest version is: I’m not really one person. I’m one person with a system. And the system only works because I’m still the one deciding what it should do, catching what it gets wrong, and caring about the output.

AI didn’t replace judgment. It just removed the friction between judgment and execution.

That’s still a lot. But it’s not magic.

I Gave My AI Agent a Footy Job

Posted: May 18, 2026 | Author: | Filed under: Geek, Personal, SaintsFooty | Tags: , , , , , | Leave a comment

I’ve been a St Kilda member for over 40 years. I’ve sat through the bad decades, the almost-decades, and the occasional brilliant afternoon that makes you think this year might be different.

Last Saturday, I was out when the Saints played Richmond at Docklands. So I did what any sensible person does in 2026 — I had my AI agent text me the scores.

Here’s how that went.

What I built

SaintsFooty is a side project I’ve been running for a while. It’s a Telegram channel — @saintsfooty — that gets a daily Saints news broadcast every morning at 7:15am, a Friday night preview with team selections and win probability before each game, and on game days, live score updates sent at each quarter break.

The whole thing runs on OpenClaw, my AI setup at home. No manual intervention. I get the updates the same as any subscriber.

Round 10 — Saints vs Richmond

Pre-game fired at 1:15pm, two hours before bounce. Team selections pulled from Footywire, Win probability from the Squiggle API, which aggregates 31 different tipping models. The Saints were favorites. I was as usual optimistic looking forward to a win.

Quarter time, half time, three-quarter time — score arrived during the breaks, right when you want them. That part worked exactly as designed.

Then the siren went.

Final score: Saints 16.13 (109) def Richmond 11.7 (73). Thirty-six point win. A good afternoon.

I didn’t get the final score message.

The bug

The live score script calls the AFL API and checks whether the game is complete. A completed game returns complete: 100. The script was rejecting that value — a logic error that meant the final score check never fired.

Found it within a few minutes of me noticing the silence. Fixed the same session. The Saints won and the bug is gone, so I’m calling it a net positive afternoon.

Rating: 4/5

The core plumbing worked. Right scores at the right times. The misses were bugs, not design problems. For a first live game day run, that’s a decent result. Small issue with the emoji colors – but an easy fix…

Friday night is Round 11 — Saints vs Fremantle in Perth. The fixed version runs then.

If you’re a Saints fan and want the updates: t.me/saintsfooty. Free, no spam, just Saints.

When Your IT Guy Retires: What Australian SMBs Need to Know About the MSP Crisis

Posted: May 13, 2026 | Author: | Filed under: Geek, Personal, smallbizai.au | Tags: , , , , | Leave a comment

There is a quiet succession crisis building inside Australian IT services, and most small business owners have no idea it’s coming.

Their managed service provider, the company that looks after their computers, their email, their backups, their security, is often run by someone who has been doing it for 20 or 30 years. That person is in their late 50s or 60s. They are thinking about retirement. And the business they built, which depends heavily on their personal relationships and institutional knowledge, is surprisingly hard to sell.

This is not a niche concern. The MSP market in Australia, like most countries, skews heavily toward owner-operators who started their businesses in the 1990s and 2000s riding the wave of business PC adoption. That wave is now cresting into a succession event.

What happens when an MSP sells or closes

There are three typical outcomes when a small MSP exits:

Acquisition by a larger MSP or private equity. This is increasingly the most common exit. Private equity has been rolling up managed service providers globally for the past decade, Kaseya, ConnectWise and their portfolio companies have been buying aggressively. In Australia, the same pattern is playing out at a smaller scale. When your MSP gets acquired, the new owner often brings in standardised contracts, price increases, and a national service desk replacing your local contact. For SMBs used to calling someone who knows their name and their server room layout, the transition is jarring.

The owner retires and closes. For smaller operators who never built a saleable business, those where the owner is the product, closure is the more likely outcome. When that happens, their SMB clients are left scrambling. Passwords in someone’s head. Vendor relationships that evaporate. Backup systems nobody else knows how to restore. This is the scenario that keeps a former colleague up at night, and it should.

The owner transitions the business to AI-augmented services. This is the best outcome for SMBs. An MSP that leans into automation, remote monitoring tools with AI-driven alerting, and Microsoft 365 management can actually improve their service quality while reducing costs. Some will make this shift. Many won’t.

What MSPs actually do for SMBs and which parts are already disappearing

Understanding the MSP succession risk requires being honest about what managed service providers actually provide. It is not a monolithic thing.

The traditional MSP bundle included:

  • Server management (on-premises infrastructure)
  • Network management (routers, switches, firewalls)
  • Desktop support and helpdesk
  • Backup and disaster recovery
  • Security monitoring
  • Software licensing management
  • Vendor relationship management (talking to Microsoft, your ISP, your printer company)

The first two items on that list, server and network management, have been quietly disappearing for a decade. If your business runs on Microsoft 365 and your files live in SharePoint or OneDrive, you do not have servers to manage. The same is true if you are running cloud accounting in Xero, cloud CRM in HubSpot, cloud HR in Employment Hero.

The businesses most exposed to MSP succession risk are those still running on-premises infrastructure, a server in the comms room, local file shares, an on-site email server. Those businesses are typically older, more established, and have not modernised because “it works.” When their MSP retires, they will discover that what works is held together by institutional knowledge that just walked out the door.

The AI factor

So, the real question, could SMBs survive without MSPs using AI to replace those services, combined with cloud migration?

For a significant slice of SMBs, the answer is probably yes, eventually.

Microsoft 365 Copilot now handles significant IT management tasks automatically. Security alerts, access management, compliance monitoring. Google Workspace does similar. The RMM (remote monitoring and management) platforms that MSPs use, tools like NinjaRMM, N-able and ConnectWise have been building AI into their alerting and remediation capabilities. The industry term “self-healing” is not quite there yet, but it is directionally correct.

The gap that AI does not close, and will not close quickly, is judgement. When something breaks in a way nobody expected, when a staff member falls for a phishing email and the damage needs to be assessed and contained, when a hardware failure requires physical intervention, those moments still need humans. The question is whether those humans need to be your MSP, or whether they could be a national helpdesk, a contractor, or increasingly a very capable AI agent with the right integrations.

What Australian SMBs should do about this

Know where your IT actually lives. If you cannot answer the question “if my MSP disappeared tomorrow, where would I find my passwords, my backup vendor, my Microsoft licences, my domain registrar?”, you have a dependency that needs documenting. Ask your MSP for a full IT asset register. Any good operator will provide one willingly. Reluctance to share it is a red flag.

Understand your on-premises exposure. Every physical server in your business is a liability if your MSP relationship evaporates. It is not necessarily worth ripping everything out immediately, but you should know what lives on-premises and have a plan for when it reaches end-of-life.

Find out what your MSP’s succession plan is. This is an awkward conversation, but it is a reasonable one. A professional operator will have thought about this. If they have not, that tells you something.

Move cloud-ward deliberately. Not all at once, and not because cloud is automatically better. But for businesses still running on-premises email, local file servers, or legacy accounting software, the succession risk is a practical reason to accelerate the migration conversation.

Build direct relationships with your key vendors. Microsoft, your internet provider, your backup vendor. Know how to contact them without going through your MSP. The MSP should be a layer of convenience and expertise, not a gatekeeper to your own technology.

The bigger question

The MSP as a category emerged because small businesses needed an affordable, local, trusted expert to manage technology that was genuinely complex and required physical presence. That model made complete sense in 2000.

In 2026, the technology is less complex to manage, increasingly cloud-hosted, and increasingly self-monitoring. The physical presence requirement is lower. The expertise requirement has not gone away, but it has shifted, from “someone who knows how to configure your email server” to “someone who can help you decide which AI tools to use and how to connect them.”

That is a different kind of MSP. Some of the existing ones will make the transition. Many will not.

The succession crisis is real. But it is also, if you read it correctly, a signal that the market is restructuring around a different model. For Australian SMBs, the useful question is not “what do I do when my IT guy retires?” It is “what should my IT actually look like in five years, and am I building toward that or away from it?”

For a look at how the generational trust gap plays into this, see: 31% of Young Australians Trust AI for Decisions. For Over-55s, It’s 4% on SmallBizAI.au.

The First Sale — AU$9 and What It Meant

Posted: May 4, 2026 | Author: | Filed under: smallbizai.au | Tags: , , , , | Leave a comment

On a Sunday in April, my phone buzzed with a Gumroad notification.

Someone had bought the AI Prompts for Professional Services pack. Nine Australian dollars.

I’d spent a few weeks building SmallBizAI.au. At that point it had around 650 posts, 40-odd newsletter subscribers, and had cost me a few hundred dollars in API credits and hosting. I wasn’t doing this for money — I’m on a career break. But this was different.

Someone found the site, read enough to trust it, pulled out their card, and paid nine dollars for something I made.

That’s not revenue. That’s proof.

Here’s what I’d built: a prompt pack for accountants, lawyers, and consultants. Fifty copy-paste prompts covering client intake, proposal writing, meeting prep, and client updates — the tasks that eat billable hours. Priced at AU$9. Low enough that a sole trader wouldn’t think twice. High enough to filter for people who’d actually use it.

The buyer is in professional services. They found the pack on a Sunday and bought it. I don’t know whether the prompts saved them any time. But they chose to pay for something on a site that had been giving everything away for free.

That matters.

I’ve spent most of my career in technology, forty years across Microsoft, Telstra and AWS, building things where success is measured in millions of users and billions in revenue. The metrics were always big.

AU$9 is not a big metric.

Career breaks reset your sense of scale in useful ways. Nine dollars from a stranger on the internet, for something you built with your own hands, in a domain you care about — that hits differently. It’s not a Series A. It’s not an enterprise contract. It’s cleaner than both.

It means the thing works.

SmallBizAI.au exists because Australian small businesses are being underserved by generic AI content. Most of what’s out there is written for US audiences, priced in USD, and assumes tools that don’t work here. Fair Work isn’t a thing in Kansas. GST isn’t VAT. Xero is everywhere in Australia and barely mentioned in American AI guides.

The site covers the Australian angle specifically: local pricing, local tools, local compliance. Whether AI can actually help a café owner in Fitzroy or a bookkeeper in Fremantle. Not theory — specific, practical, AU-focused.

Hundreds of posts. One sale.

The ratio sounds bad. It isn’t. Search traffic takes months. Newsletter lists grow slowly. That first sale didn’t come from a viral post or a paid campaign. It came from someone searching for exactly what I’d built, finding it, and buying it.

That’s how it’s supposed to work.

There are now six products in the Gumroad store. Prompt packs at AU$9 each — for tradies, hospitality, allied health, professional services. An AI Tools Comparison Guide for AU$15. A 200-prompt pack for AU$19.

None of this replaces a salary. That’s not the point. The point is building something that earns trust through useful content and eventually converts that trust into revenue. Slowly. Deliberately.

Someone started that. At AU$9 a time.

If you run a professional services business: AI Prompts for Professional Services] — AU$9.

And if you’ve used any of the packs and have feedback on what worked (or didn’t), I’d like to hear it.

Sources

SmallBizAI.au Resources page — all Gumroad products and a bunch of free downloads and guides as well.

This is part of an ongoing series about building SmallBizAI.au in public. Also published at SmallBizAI.au.

Start from the beginning:

6 Weeks, 666 Posts, 1 AI Agent: What I Actually Learned

Posted: May 1, 2026 | Author: | Filed under: Geek, Personal, smallbizai.au | Tags: , | 2 Comments

Six weeks ago, I started a content site while on a career break.

I wasn’t planning to write hundreds of articles. I had a specific question: could an AI agent actually run a content operation — not assist with it, but run it?

The answer, six weeks and 666 posts later, is: mostly yes. With caveats.

What the agent actually does

Every morning at 8am, an AI agent publishes a news recap covering AI developments relevant to Australian small business. At 7am it reads the morning brief, at 9am it checks newsletter stats and flags milestones. During the day it runs batches: fixing broken links, adding internal links, applying FAQ schema to posts, cleaning up em dashes.

On Fridays it runs a full SEO review — pulls Google Search Console data, identifies CTR opportunities, and sends a summary to Telegram.

It built over 200 profiles of Australian AI companies. It’s probably the most complete directory of AU AI companies that exists. It did that by researching each company, writing a structured profile, publishing it, and adding it to a master guide page — all without me having to do anything except occasionally fix mistakes.

The agent also maintains a dashboard, tracks cron job health, scans my Gmail for anything important from hosting, billing, or Google Search Console, and alerts me when something needs attention.

I mostly direct it. I come up with angles, approve approaches, review things before they go out, and fix things when they go sideways.

What I got wrong early on

In the first few weeks I let the agent publish as fast as it could. Some days that was 40-50 posts. It felt like momentum.

It wasn’t. The posts were thin. The internal links were incomplete. Google didn’t trust the site, and rightly so. I spent a lot of time in April going back and fixing quality issues that could have been avoided.

The lesson: one focused post per day, done properly, is worth more than ten rushed ones. The agent now follows a daily minimum — one how-to or automation guide, plus the automated news recap. That’s it. Everything else is upside.

Bing AI noticed before Google did

The most surprising metric has been Bing AI citations. The site went from 13 citations in mid-March to 485 in a single day in late April. Total: over 4,200 citations across 115+ pages.

The pattern is clear: comparison posts and AU company profiles get cited heavily. The Stripe vs Square vs Tyro comparison has 289 citations. The Flare HR profile has 512. Google Search Console shows the site is indexed and getting impressions, but Bing has been faster to treat it as an authoritative source.

This lines up with something we’re now calling Answer Engine Optimisation — structuring content to be cited in AI-generated answers, not just ranked in traditional search. The comparison and profile format works well for this.

The $9 sale

Six weeks in, someone bought an AI prompt pack for professional services. A$9. Thanks buddy!

It sounds small. It wasn’t. It confirmed the site could generate revenue, and it set off a milestone alert that the agent sent to Telegram at 2am. I saw it in the morning and genuinely celebrated.

The conversations that matter more than revenue right now

A former AWS colleague saw a LinkedIn post and reached out. His entire client base is SMEs. He’s referring people to the site. A local AI startup CEO connected because he’d seen the profile I’d written about his company.

These are the early signals that matter. Revenue will follow reach. Reach comes from being useful and being visible in the right places.

The honest state of play

666 posts. 40+ newsletter subscribers (70%+ open rate on the last issue). 4,200+ Bing AI citations. A$9 in revenue. One very enthusiastic AI agent.

It’s not a business yet. It’s a foundation. The next phase is turning traffic and citations into subscribers, and subscribers into customers for the Gumroad products and, eventually, something bigger.

The experiment is working. The question now is whether the foundation scales.

SmallBizAI.au is a practical AI resource for Australian small business. If you want to follow along, the newsletter goes out every Tuesday.

Sources

  • SmallBizAI.au — site stats as of 1 May 2026
  • Bing Webmaster Tools — AI citation data, 18 March – 30 April 2026
  • Google Search Console — indexing data, 15 March – 30 April 2026

Can One Person on a Career Break Outproduced a Team of 8?

Posted: April 24, 2026 | Author: | Filed under: Geek, Personal, smallbizai.au | Tags: , , | 1 Comment

Coffee cup, beach, golden sunset — career break vibes nailed. 🦞

I had coffee with a former colleague recently. He runs a business focused on providing comprehensive services to business owners — with a dedicated team working across content and service delivery.

He looked at SmallBizAI.au and said our content was better than what his team had produced.

I’ve been on a career break since leaving AWS in 2024.

That gap deserves an explanation.

The Site Isn’t Really a Site

SmallBizAI.au has 639 published posts. 208 Australian AI company profiles. Nine content categories. A newsletter with a 90% open rate. Six Gumroad products. A daily news post. A Sunday series. And a coverage area that spans 100+ industries.

I didn’t write most of it this week. A lot of it ran while I was having coffee.

Here’s what actually happened while I was out:

  • The morning brief landed in my Telegram at 7am with overnight news, today’s weather, content opportunities, and SEO flags
  • The daily news cron fired at 8am, pulled from 20 RSS feeds, scored stories for Australian relevance, picked the best five, and published a post
  • The internal link sweep processed 50 posts, found relevant anchor opportunities, and added links automatically
  • The em dash cleanup script fixed AI writing patterns across another batch of posts
  • The broken link fixer ran at 11am, processed 30 posts from a queue, and applied known URL replacements

None of that needed me. It just happened.

What “Agentic” Actually Means

There’s a lot of talk about agentic AI right now. Most of it is abstract.

The concrete version looks like this: 31 scheduled jobs running on a server, each doing a specific task, each reporting back. Some run daily. Some run weekly. Some run once a month. The whole thing costs less than $10 a day in API calls.

The tasks aren’t glamorous. Fix broken links. Update post counts. Sweep for missing alt text. Refresh the sitemap. Check newsletter subscriber milestones. Run the SEO review. Generate the Monday report.

But the cumulative effect is a site that maintains itself. Every day it gets a little cleaner, a little better linked, a little more optimised. I don’t have to remember to do any of it.

Claw Isn’t a Chatbot

The AI I work with — I named it Claw 🦞 because it’s OpenClaw— isn’t a tool I query. It has a memory system, a soul document, a personality, and persistent context about the business.

It knows that our content edge is the Australian angle. It knows to run the avoid-ai-writing skill before publishing anything. It knows the newsletter sends on Tuesdays at 6:30am. It knows the people I know, and gives me insights before I meet them.

It remembers because I told it to write things down. It has daily memory files, a long-term MEMORY.md, project files for every content series, and a dashboard that updates nightly with live stats.

When I start a new session, it reads the relevant files and picks up where we left off. No briefing required.

That’s different from a chatbot. A chatbot answers questions. Claw manages a business with me.

The Dashboard as Command Centre

One of the things I built early was a private dashboard page on the site itself.

It shows: total posts by category, newsletter subscriber count, Gumroad revenue, Google Search Console performance, Bing AI citation counts, background task progress, infrastructure status, the content pipeline, the AU company profile queue, and the last 20 published posts.

It auto-updates every night.

I check it at the start of each session and know the state of the whole operation in 30 seconds. No Slack. No standups. No status meetings.

That’s not magic. It’s just information architecture. The data exists — GSC API, WordPress API, MailerLite API, a state JSON file. The dashboard pulls it together and shows it clearly.

But the effect is real. I can make better decisions faster because I’m never starting from zero.

What This Means for the Industry

A former colleague runs a business with a dedicated team focused on content and service delivery. Real people, real effort, real investment.

A single person on a career break, working with AI, produced something he considered better.

I’m not saying that to be smug. I’m saying it because it tells you something important about where we are right now.

The constraint used to be labour. Content took people. Maintenance took people. Research took people. Systems took people.

Those constraints haven’t disappeared — but they’ve shifted dramatically. A single person who understands what they’re building, who structures their AI tools correctly, and who builds agentic infrastructure around their work can now match or beat larger teams on output and quality.

The new constraint is design. Can you design the system well enough that it does the right things autonomously? Can you build the memory structures so context doesn’t get lost? Can you write the crons that run the tasks you’d otherwise forget?

That’s a different skill set than managing a team. In some ways it’s harder. In others it’s much faster.

What This Isn’t

This isn’t a story about AI replacing people.

Claw doesn’t make strategic decisions. It doesn’t know that an off the cuff acquisition comment is worth sitting with for a few weeks before responding. It doesn’t know that someone’s AI startup is enterprise-focused and not worth a profile yet. It doesn’t know when to push and when to wait.

I do those things.

What AI does is remove the friction between decisions and execution. I decide to write a comparison post. Claw drafts, audits for AI writing patterns, adds Rank Math meta, pulls a featured image from Unsplash, formats the tables with the correct style, publishes it, updates the dashboard, and adds it to the relevant guide page.

That used to take me two hours. Now it takes twenty minutes of oversight, if that.

The output went up. The time went down. The quality, if anything, improved because the system enforces standards I’d sometimes cut corners on.

The Practical Bit

If you want to build something like this, here’s what actually matters:

Memory architecture first. If your AI can’t remember what you built last week, you’ll repeat yourself constantly. Write things down. Create project files. Build a dashboard. The AI is only as useful as the context you give it.

Automate the boring stuff early. Every task you do manually more than twice should be a cron job. Broken links, alt text, internal links, post count updates — these are all automatable. Do them once manually, then write the script.

Build standards into the system. Table styling, meta descriptions, footer links, featured images — if these have a standard, the system can enforce it. Document the standard. Give the AI the standard. Stop enforcing it manually.

Treat it like infrastructure, not a tool. A hammer is a tool. You pick it up when you need it and put it down when you’re done. An agentic system is infrastructure — it runs whether you’re watching or not. Design it that way.

Where This Goes

I don’t know what comes next for SmallBizAI.au. I don’t know if it becomes something bigger. I don’t know if the newsletter hits 5,000 subscribers by the end of 2026.

What I do know is that the model works. One person, the right infrastructure, and a clear focus on what actually matters — in this case, Australian AI content for small businesses — can build something real.

The team-of-eight comparison isn’t the point. The point is that the tools exist now for one person to do what used to require a team. That changes what’s possible for solo founders, career-breakers, side projects, and small businesses.

Most people haven’t figured that out yet.

Frank Arrigo built SmallBizAI.au on a career break. The site covers AI tools, Australian AI companies, and practical guides for small business owners. 🦞 handles operations.

Australian Boards Don’t Understand AI. Here’s Why That’s A Problem For All Of Us.

Posted: April 21, 2026 | Author: | Filed under: Geek, Personal, smallbizai.au | Tags: , , , , | 3 Comments

frank arrigo career timeline

I’ve spent 40 years in technology. Starting at Aspect Computing in the 80s as a graduate, then 22 years at Microsoft both in Australia and Seattle, 4 years at Telstra, and finally 6 years at AWS covering Australia and APJ. I’ve sat in boardrooms, executive briefings, and strategy sessions across Australia, the US, and the Asia-Pacific region.

And I’ll tell you what I’ve noticed: the people making technology decisions at most Australian companies often understand finance, law, and general management very well. They understand technology considerably less well.

New research from Queensland University of Technology has put numbers to something I’ve experienced firsthand. Out of the 500 largest ASX-listed companies, more than half have zero directors with STEM expertise. Over 15 years — covering smartphones, cloud, and now generative AI — that number moved from 8% to 13%. Meanwhile, accountants, bankers and lawyers still hold 42% of board seats.

I don’t think these are bad directors. Many are excellent at what they do. But technology is no longer a back-office function. It’s strategy. And you can’t set strategy for something you don’t understand.

What I saw at Microsoft and AWS

At Microsoft, I spent years as a technical evangelist — explaining technology to businesses, developers, and yes, executives. The best executive conversations I had were with people who had at least some technical background. They asked better questions. They made faster decisions. They weren’t paralysed by the fear of making the wrong choice because they didn’t understand the options.

At AWS, I ran teams focused on helping Australian organisations adopt cloud and AI. Again: the organisations that moved fastest had at least one person close to the top who genuinely understood what they were adopting. Not necessarily an engineer — but someone who had shipped software, run a tech team, or built something with technology.

A former colleague of mine who focused specifically on AI governance and board-level education at AWS put it well: boards tend to either dismiss AI as an IT problem or panic about it as an existential threat. Very few engage with it as what it actually is — a general-purpose capability that changes what’s possible across every function of the business.

Why this is urgent now

The QUT research only goes to 2022. AI as we know it today — ChatGPT, Claude, Copilot, Gemini — arrived after that. The urgency has increased dramatically since then.

ASIC has told Australian boards that cybersecurity is their responsibility, not the IT department’s. AI brings similar responsibilities: data privacy, algorithmic bias, liability when AI systems make mistakes, regulatory compliance under an evolving Privacy Act.

The Australian government signed an MOU with Anthropic in April 2026 — the first arrangement under the National AI Plan. Billions are flowing into data centres. Anthropic is opening a Sydney office. The investment appetite is real.

But investment without governance is how you get expensive technology initiatives that deliver nothing, or worse, that create serious legal and reputational risk.

The question I keep asking myself

I’m on a career break right now. Building SmallBizAI.au — a practical guide to AI for Australian small business owners. It’s been a fascinating experiment in what one person can build with the right AI tools and infrastructure.

But the boards research made me think about what’s next. Not just for me personally — though if you’re looking for someone who’s spent 40 years in technology, led teams across Microsoft, Telstra and AWS, and is now building AI-native products, I’m worth a conversation. But more broadly: what does Australia lose when the people overseeing our biggest companies don’t understand the most important technology shift of our lifetimes?

The research has an answer. Companies with more STEM expertise on their boards invest more in innovation and are valued more highly. That held even in low-tech industries. The boardroom gap isn’t just a governance problem. It’s a competitiveness problem.

What good looks like

I’m not arguing every board needs a software engineer. I’m arguing boards need at least one person who has operated at the intersection of technology and business — who can ask the right questions, interrogate vendor claims, understand the real risks, and push management to move faster when the opportunity is clear.

That person exists in Australia. There are thousands of us — people who came up through technology, moved into leadership, and understand both sides. We’re not all in boardrooms. Some of us are on career breaks building websites about AI for small business owners.

That might need to change.

Sources