Daniel Joseph

When we were starting out we set our prices super low just to get anyone through the door.

It worked for getting initial sign-ups, but it accidentally trapped us with low budget users who demanded endless custom help while we severely undercharged enterprise teams getting massive value. Raising prices on those early adopters months later was an absolute operational nightmare. For founders who had to rework their tiers after launch how did you handle migrating early users to higher plans without destroying trust?

Hey PH
One use case keeps coming up with agencies, so we wrote it up properly so others can reuse the template.
The problem: an agency runs 10 clients through ChatGPT, Claude and Gemini. Every writer pastes a different version of the style guide, two clients end up in the same thread, and freelancers take their prompts with them when they leave. The result is voice bleed: Client A's copy starts sounding like Client B.
How teams are solving it with AI Context Flow:
One memory bucket per client: voice rules, audience, banned terms, on-brand and rejected examples, compliance limits
Shared buckets: contributor and viewer roles, an activity log of who changed what, and version restore
The MCP server: the same client voice in Claude, ChatGPT, Cursor, Copilot, Windsurf and headless agents. The AI pulls only the relevant context and writes client feedback back to the bucket
Full playbook, including a copyable voice-bucket checklist: https://plurality.network/blogs/...
If you run an agency or a multi-brand content team, I'd love to know how you handle client voices today, and what's still breaking, maybe we could make a custom built setup done-for-you. lmk below

Thanks for following Comcent! We're starting a series of short tutorials, one task each.

The first one is the whole setup: sign up, create your organization, connect the Twilio number you already have, choose who its calls ring, and answer a real call in the browser.