The result is better than anything else I've interfaced with, thank you Jake and Community! Having worked in Advertising myself, I knew exactly what I wanted out of it and it delivered. Copy submitted manually to GPT image2, with references of previous branding and styles references I created, (I'll have to automate that part next, into a seamless pipeline.).

So this one is the ultimate Clief Notes community bringing disparate threads together post. So reader, consider this your warning upfront. @Alyshia Perri and I were talking and she was keen to get feedback on her entry in the coach competition. I tried to do that in DM to begin with, and then realised I was babbling. I asked her permission to fork it and make my edits so I could *show* her what I was trying to describe and she gave me that permission. None of the rest of this happens without her and she also gave me permission to post this. So here’s a brave woman who’s willing to let me link to a repo showing how I messed with her baby because I couldn’t find better words for the teaching. Please tell her how awesome she is, because that is *gutsy*. One of the coaching offerings in this repo was “board mode” which runs an idea past three different perspectives, each with a different agenda and angle of attack to help the user. I’m going to be upfront and say these sorts of mechanics in AI are generally not to my taste for a bunch of reasons. I don’t think they are effective, let’s keep it to that. But on my mind was the recent podcast by @Curtis Hays and @Brooke Hays showing the impact of using Jungian thinking archetypes / Myers-Briggs profiles to genuinely give the way agents approach things different flavours. What I did: - I got the model to do a sub-agent pass first using the roles as written - I took the three roles as stated and identified which profiles applied to these roles from my point of view - the skeptical stakeholder got “ESTJ”, the peer who has been burned got “ISFJ”, future self got “INFJ”. Then we did it again and compared the outputs - I added two new roles that I felt were missing - the logic stress tester (INTP) and the values-holder (INFP) - I felt off the results of these that Amund as the synthesiser was missing a trick. I tried two separate synthesis passes (over the first rounds, the second round, and all five together) - one using an ENFJ synthesiser and another using an INTJ one.

I run a chunk of my commercial follow-up through agents now, and the wall I keep hitting isn't the writing — it's that the agent doesn't know where the relationship actually stands. Who owes whom a reply, whether we're warm or stalled, what the last real signal was. So I either hold all of that in my head (and I become the bottleneck), or I dump the whole thread history into context and the message comes back generic and expensive. For those of you running outreach or follow-up through agents: how do you represent relationship state as something structured the agent reads and acts on — a status field, a per-contact context file, a "next best touch" the system proposes? And just as important, how do you keep the output from feeling automated on the other end? I'm after the structural fix, not a better prompt. What actually lives in your setup, and what did you try that quietly failed?