AI Chief-of-Staff System Build

Job ID: 40464072

Budget: $250 – $750 USD

I want to stand up a complete AI environment that acts as a “chief of staff” for my company and, beneath it, a network of specialised sub-agents. The core agent must handle Task management, Decision making, and Data analysis and reporting so that routine coordination, prioritisation, and insight generation happen automatically while I stay focused on strategy.

Around that core I need purpose-built agents for Copywriting, Social marketing, Graphic design and broader content creation. They should accept high-level briefs from the chief-of-staff agent, produce draft assets, loop through revisions with me in-chat, and then return the finished work back into the knowledge base for future reuse.

A second phase will pivot this same architecture into a client-facing virtual coaching chatbot. As an executive coach, I want the bot to guide leaders through Goal setting and tracking while delivering truly Personalized advice in a conversational style that reflects my own coaching voice.

I’m comfortable with any modern LLM stack—LangChain, semantic memory stores, vector databases, function calling, agent frameworks—provided the final solution is maintainable and can be expanded with new tools as my practice grows.

Deliverables
• A working “chief of staff” AI agent with the three capabilities above, running in a secure cloud or local container.
• At least three connected specialist agents (copy, social, design) demonstrably executing tasks end-to-end from prompt to output.
• A coaching chatbot prototype that draws from my curriculum, performs goal tracking, and provides personalised check-ins.
• Documentation covering architecture, deployment steps, and how to add new agents.
• A short video walkthrough so I can share the system with my team.

Acceptance criteria will be a live demo where I assign a campaign, watch the sub-agents deliver the materials, and then shift into a coaching session that logs goals and suggestions. I’m ready to get started immediately and happy to iterate in short, milestone-based sprints.

Here is a screen recording that shows a little more of what I am looking for: https://flonnect.com/video/dbe97f12a1a5-4aea-b6b7-db43fd85ac45