RC
This is for teams that already run more than one AI agent across sales, marketing, or customer success (a prospecting agent here, a CRM-hygiene agent there, a Slack assistant answering pipeline questions) and are now deciding what those agents should run on. Most teams are already in this position: 66.4% of agentic AI deployments are multi-agent (Landbase / Market.us, 2025). The single-agent purchase is the exception.
Two years ago the question was which agent is best. That question is mostly settled. What doesn't work is the stack around the agents: memory is per-agent, connection is scattered, and governance is missing. So the buying question moved down a layer. It is no longer which agent. It is: what do all of our agents share, and who controls it?
The full framework gives you a way to answer that before you sign anything:
Four architectures on the market (CRM-bundled suites, point-solution agents, DIY frameworks, and an independent operating layer) with an honest "choose this when" and "watch for" for each.
Eight evaluation criteria: shared memory, connect once, governance on every action, outcome attribution, a feedback loop, ownership of the GTM brain, openness, and total stack cost, each with the question to ask, what a good answer sounds like, and the red flag.
A scorecard rating the four architectures against all eight.
Thirteen RFP questions you can paste in, and the five red flags that should end a conversation.
A disclosure of where wysdym sits, so you can weight it accordingly.