Tactician: Detailed, specific workplace advice for confusing or political situations

I’m baking everything I learned through my PhD in Organizational Behavior and my years as a professor in the field, combined with my lifelong interest in organizational effectiveness, into Tactician. Tactician isn’t a single advice-bot. It’s a system that combines distinctly different perspectives, careful questioning and hypothesis-testing, and freeform chat to get you evidence-based, actionable advice.

In the live demo I’ll walk through a real workpalce scenario (people come to me for advice with these all the time). We’ll chat with the advisor personas first. Then we’ll give some further tailored details, based on an intake survey that’s dynamically generated based on the chat. We’ll see the combination of these piped back to the advisors, who will suggest little hypothesis tests in the real world so you can figure out what is actually going on. We’ll simulate this in the demo. Once we’re sure of the facts, the advisors present courses of action that seem likely to lead to a integrated good outcome: something that will be beneficial both for you and the organization.

It’s a system based on careful data selection, an agentic workflow (BAML, pydantic), RAG from a vector db with only the choicest organizational texts in it, and (eventually) fully local and private models to offer a complete tailored advice system. Starting by hooking it up to Claude 3.7 sonnet with some prompt engineering for multiple advice personas.

Use-case spiel:

Maybe you interacted with a boss or client recently who said something confusing but important. Maybe you’re in a situation where people expect you to have a lot of people skills and you feel overwhelmed. Use Tactician to figure out a) what’s going on, b) what your options are to get to a good outcome.