Back From Vacation, Straight Into AI Efficiency Talk
Hi all 👋
I'm back, and I have to admit it took some willpower to trade great weather and family time for a full inbox again. Now that I'm caught up, I'm genuinely excited to see the momentum from a busy summer carry into the fall.
What's Happening in AI
A stat from Meta is making the rounds: developers using AI wrote 220% more code and shipped 36% more features. They also produced 40% more incidents and spent 70% more time firefighting.
These developers were suddenly producing about six times more work. But the process meant to catch mistakes before they went out the door never grew to match it. Quality dropped, and every mistake that slipped through got more expensive to fix. Flood any system with more than it's built to check, and this is what happens, AI or not. Triple a sales team's leads without adding anyone to screen them, or double a factory's output without adding anyone to check quality, same result. Meta just ran the experiment on code generation.
If you're rolling out AI anywhere in your business, don't just track how much more is getting produced. Ask whether the people and process that catch mistakes grew along with it. If they didn't, you're not actually getting more done, you're just pushing the cost down the road, and it shows up later as incidents and firefighting instead of a clean "AI failed" headline.
This Week's Case Study
Every supplier invoice that a fast-growing company can't process fast enough is a vendor relationship quietly getting worse.
One e-commerce client had outgrown their accounts payable (AP) system. So we automated the manual part: reading invoices, matching purchase orders, and feeding clean numbers straight into their financial system.
- Roughly $55,000 to $80,000 a year back in AP processing costs
- Manual processing hours dropped about 70%, from 2,000 hours a year to 600
- Real-time visibility instead of a monthly reconciliation surprise
Worth asking: Is there a process in your business that wasn't wrong when you bought it, just never built to grow with you?
→ Read the full case study.
A Useful Resource
One question I get quite often is: "How do I know if a process is actually worth automating?"
That's why we built the Administrative Tax Calculator. It shows you how much you're paying premium salaries to do low-value work, chasing updates, manual entry, bridging gaps between systems. Before you hire another person, see how much you're already losing to broken processes.
That's it for this week.
— Robbie
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Hi all 👋
I'm back, and I have to admit it took some willpower to trade great weather and family time for a full inbox again. Now that I'm caught up, I'm genuinely excited to see the momentum from a busy summer carry into the fall.
What's Happening in AI
A stat from Meta is making the rounds: developers using AI wrote 220% more code and shipped 36% more features. They also produced 40% more incidents and spent 70% more time firefighting.
These developers were suddenly producing about six times more work. But the process meant to catch mistakes before they went out the door never grew to match it. Quality dropped, and every mistake that slipped through got more expensive to fix. Flood any system with more than it's built to check, and this is what happens, AI or not. Triple a sales team's leads without adding anyone to screen them, or double a factory's output without adding anyone to check quality, same result. Meta just ran the experiment on code generation.
If you're rolling out AI anywhere in your business, don't just track how much more is getting produced. Ask whether the people and process that catch mistakes grew along with it. If they didn't, you're not actually getting more done, you're just pushing the cost down the road, and it shows up later as incidents and firefighting instead of a clean "AI failed" headline.
This Week's Case Study
Every supplier invoice that a fast-growing company can't process fast enough is a vendor relationship quietly getting worse.
One e-commerce client had outgrown their accounts payable (AP) system. So we automated the manual part: reading invoices, matching purchase orders, and feeding clean numbers straight into their financial system.
- Roughly $55,000 to $80,000 a year back in AP processing costs
- Manual processing hours dropped about 70%, from 2,000 hours a year to 600
- Real-time visibility instead of a monthly reconciliation surprise
Worth asking: Is there a process in your business that wasn't wrong when you bought it, just never built to grow with you?
→ Read the full case study.
A Useful Resource
One question I get quite often is: "How do I know if a process is actually worth automating?"
That's why we built the Administrative Tax Calculator. It shows you how much you're paying premium salaries to do low-value work, chasing updates, manual entry, bridging gaps between systems. Before you hire another person, see how much you're already losing to broken processes.
That's it for this week.
— Robbie
