Hi Brandi Z., Cassie W. -- Thanks for bringing this up. This is something people are thinking about, sometimes even over weekends, but aren't speaking about.
I really empathise with what you both are saying. Watching from close quarters and picking up what’s working is a smart and deliberate strategy. I’d still call that a proactive plan.
"Between prompts, docs, dashboards, and random chat threads, it feels like everyone’s building ideas and insights in ten different places at once" -- This needs to be controlled within GTM as much as vibe coding needs to be controlled for Development.
"start in platform 1 and do X, then it runs through platform 2, before landing in final destination of platform 3" - is kicking the can down the road for some hardworking, selfless RevOps person to do the clean up. Not sustainable.
This prompt chain reaction needs guardrails, and preserved context to remain useful over longer periods of time for a team/org.
That said, the temptation to tinker was real, especially after years in BizOps and ProductOps, seeing these gaps up close.
I started looking at areas where older tools had hit their limits:
- 1.
When I couldn’t punch through the fuzziness of data.
- 2.
When my GTM team was spending hours researching instead of doing timely action for prospects or customers.
- 3.
When wiring external signals at scale was either costly or too clunky.
I began as a skeptic, but more as a curious tinkerer. Early LLMs made basic mistakes like misreading numbers in tables or failing to calculate a median (give this a try with group by, you'll know), but they improved faster than expected.
Through hundreds of conversations with founders and CROs made one thing clear: dashboards and research have become commodities, and adding to the cognitive load. The real gap isn’t in finding insights, it’s in getting them to the right people at the right time, without adding noise.
We’re living through this pain ourselves while building an antidote to these “jumping through the hoops” point solutions. The easy fixes always shift the burden back to users. We decided to take the harder route—figuring out how to move data to insights to action in a repeatable, cross-department way.
It’s not plug-and-play, but it’s the only approach that’s actually reducing chaos instead of adding more. Sometimes the hard way ends up being the only sustainable way.
We start by using AI to fix data; cleaning what’s messy or incomplete and making unstructured data useful. Then we create templates that make insights repeatable and easy to share. Finally, we layer external signals on first-party data so it becomes richer and more actionable.
Most teams already do parts of this in silos. The real unlock comes when it works seamlessly across teams. That’s where value compounds and real, durable revenue impact begins to show.
DM me if you are interested in knowing what exactly we have been up to, and if you could gain from any of our hard work. I can share some recordings of real world, durable impact.
