Olivia Watson

I had my agent hallucinate the wrong day of the week three times in a row simply because I let it calculate timestamps on its own instead of using a basic system script. Moving all structured data generation like JSON fields file paths and dates away from the model and into deterministic Python scripts completely fixed our pipeline stability.

LLMs are great for writing plain text and copy but terrible at programmatic math. Do you still let your agents handle raw config values or do you lock those down with scripts?

I had a point where automated memory started dragging old context or weird habits from past sessions into brand new chats and half my time went into correcting it. Turning off automatic memory and just keeping a simple local file for important project notes felt like a huge relief. It s way easier to clean up a text file than trying to untangle what an algorithm remembered for you.

How do you manage your project notes across different sessions do you let the tool remember everything or do you keep a manual log?

Relying on factory-provided descriptions is a fast way to get buried in search results.

When hundreds of stores use the exact same two sentences from the manufacturer, search engines have zero reason to rank your page over anyone else's.

We fixed this by mixing real buyer feedback and common questions straight into our product blocks instead of writing everything from scratch manually. It gave us a solid traffic boost in just a few months.

How do you handle unique content when your catalog has thousands of similar items?