We run an automated pipeline that drafts articles for our product. During our first test attempts we let the model do almost everything, including the mechanical bits: fixing dashes and quotes, tracking which stage each article was in, creating SEO json, naming image files etc. It worked, but the quality was uneven, sometimes the model would miss some things, and, of course, it was rather expensive in terms of tokens.
Then we changed our approach and started treating AI like a creative employee and providing it with "software" (python scripts) to help with any mechanical tasks that could be automated by code. The model only does the part that actually needs intelligence and creativity now.
And honestly, the result surprised me - quality went up, because we now let it focus on what it's actually good at. As a pleasant bonus - the costs of running the pipeline dropped too. One of the first things we scripted was stripping the em-dashes the model loves to add but my co-founder has an allergy for

How do you improve the quality of your AI results, especially automated pipelines?

I realized I probably couldn't stay away from the internet for an entire day. :D

Partly because I want to keep my Product Hunt streak, but also because:

• I try to nurture my community and engage with them every day (essential for growing).

• I handle customer support daily.

• Missing important news from the tech world gives me FOMO.

Hi Product Hunt

Hey everyone, I'm Ehtesham, a solo developer based in the UK.

For years, I tried almost every to-do app, but they all had the same problem: I had to remember to open them. If I didn't, my tasks were out of sight and out of mind.

So I decided to build TaskWall.