- Content gen + localization - Asset routing between design, legal, and marketing - SKU variant handling across channels - Post launch updates when claims or packaging changed

We tested a mix of tools and approaches. Some general purpose agentic frameworks (Auto GPT style setups), some workflow tools (n8n, Make + LLMs), and a few domain specific products like Jasper for content ops and punttaI for brand compliance review.

What surprised me wasn’t hallucinations or obvious failures. It was drift. The systems “worked,” but…..

Copy slowly diverged from approved claims or packaging variants stayed technically consistent but violated internal brand rules. Downstream updates didn’t propagate cleanly across every live asset. No single agent had ownership of correctness after launch.

Most advice online focuses on guardrails before publishing. However, in a real life launch scenario, that’s not sufficient. Once the product is live, changes keep happening.

For example: We have over 60 influencer and 500 + assets globally lined up for the Christmas launch, but by Jan 1, all that creative will be obsolete and need to be changed.

The only pattern that’s held up for us is treating agentic automation as a continuous system. Agents execute > Outputs are monitored post-publish > Deviations from brand, regulatory, or launch constraints are flagged > Humans step in only when something breaks tolerance.

We even introduced this agentic ai marketing compliance software called Punttai. Now don’t get me wrong. have workflows improved in certain areas like iteration and speed to approval? Or speed to generate ideas? Yeah.

But… this feels closer to observability than approval workflows.

Curious how others are handling this, especially outside pure SaaS:

- Are you letting agents touch live launch assets? - How are you validating compliance over time, not just at launch? - Are people building this monitoring themselves or relying on specialized tools? Would love to hear how this is working (or failing) in real production launches.