The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Every migration horror story starts the same way: "we'll do the switch over the weekend."
Friday night, freeze the old system, run the export, run the import, point everything at the new database, go home. Monday morning you find out something didn't come across, and by then you have two days of new data on top of it.
The alternative takes longer and is far less exciting, which is the point.
Run both systems on real traffic first. The old stack keeps serving users exactly as it does today. The new one receives the same writes in parallel and serves nobody. Nothing depends on it, so it can be wrong without hurting anybody.
Then compare. Row by row, on real production data, not a sample. Every mismatch is a bug — a type that didn't translate, a constraint that behaves differently, a timezone assumption nobody documented. You find those on a Tuesday afternoon with the old system still running, instead of at 2am with users locked out.
Only then move people across. One region at a time, in my case. Each with a rollback path that had actually been tested rather than written down.
We moved 12 countries this way. Zero data loss — not because the migration was clever, but because by the time we switched, we already knew exactly what the new system would do.
If your cutover plan is dramatic, that's not confidence. It's a plan with no verification step in it.
Anyone here done a big migration recently? Curious whether you dual-ran it or took the weekend approach.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Trending
retrofuturism
Share your favorite designs from the past exploring the distant future. Or your own take on the aesthetic 🚀
halftone
Dots. Texture. Grain. Let's see your designs using the halftone technique.
Midjourney
Creatives are showing off what they're making with Midjourney.
colorgrade
Video editors sound off: How do you enhance the mood of your video in color grading?
Related posts
YOUR INVENTORY SYSTEM IS NOT FAILING BECAUSE OF EXCEL. IT’S FAILING BECAUSE YOUR STOCK RECORD DOESN’T MATCH REALITY.
Most small warehouses track:
“Stock received”
“Quantity updated”
“Order completed”
None of this matters.
The only metric that matters:
Does the system reflect what is actually on the shelf — right now — without guesswork?
For many small distributors, the answer is no.
Not because the team is careless. Because spreadsheets are weak where warehouse accuracy matters.
This is not a data-entry problem.
This is an inventory reliability problem.
Where systems break:
manual receiving
no barcode verification
wrong bin locations
shortages discovered late
stock counts that drift from reality
In parts distribution, that means:
wrong shipments • missed sales • unnecessary reorders • dead stock
CORE SHIFT:
Stop designing stock spreadsheets.
Start designing verified inventory.
Order → Scan → Match → Confirm → Update
I designed StockPilot around this workflow:
Upload an incoming order.
Scan manufacturer barcodes.
Match expected vs received quantities.
Flag shortages and overages instantly.
Show the correct bin location.
Track on-hand, on-order and safety stock.
Built for small parts distributors sitting between Excel and ERP.
But the real opportunity isn’t another inventory dashboard.
It’s giving a small warehouse the confidence to say:
“We know exactly what came in, where it is, and what we actually have.”
That’s the difference between tracking inventory and controlling it.
If your warehouse software records numbers but can’t verify reality —
you don’t have inventory control.
You have a spreadsheet with a nicer interface.
Check out the full case study here
Book a call with me: cal.com/prince-kane-4gsclj/aiautomation-strategy-call
Clean Data. Better Decisions.
Good data work starts with accuracy.
I help organize, clean, and validate data so that spreadsheets and datasets are easier to use and trust.
From data entry and formatting to identifying duplicates and inconsistencies, I focus on keeping every detail clear and consistent.
Accuracy → Consistency → Reliable data.
A designer commented on my last post that the 3D hangar only works because every station maps to a real business function. He's right. So this one is pure function.
FRICTION: one signup form, filled twice. Form A is the form everyone actually ships - placeholder-only labels, paste blocked on confirm email, password rules revealed one failure at a time, errors that only appear after you hit submit. Form B is the same six facts, designed right.
The page measures your hand while you fill it - every keystroke, backspace and rage click - then draws your cursor path like a session replay and prints the bill on a receipt.
My own run: 3:35 on Form A, 0:57 on Form B. 3.8x slower, 2 rage clicks, 3 submit attempts. Same person, same fake answers. The only thing that changed was the design.
One page, no dependencies, nothing leaves your browser. Run it on your own hand: greenaidigital.com/friction
