Program · Small businesses
AI Assistant Stack for Small Teams
A practical program for small teams who want a handful of focused AI assistants — for email, docs, support, and internal workflows — instead of a random mix of tools nobody trusts.
We'll define which assistants your team actually needs, design clear “jobs” and boundaries for each one, and wire them into the tools you already use — with guardrails and simple review habits.
Program overview · Audio
A short overview of the program: who it's for, what we cover, and how to get the most value out of it as a busy professional.
What your team will be able to do after this program
Less “everyone has their own AI hacks,” more shared assistants your whole team can rely on.
- • Identify the 2–5 assistants that actually move the needle for your team.
- • Design prompts, policies, and behaviors that make those assistants predictable and useful.
- • Connect assistants to the right docs and SOPs without leaking sensitive information.
- • Launch a small assistant stack your team understands and feels comfortable using.
- • Keep improving (or retiring) assistants based on how they perform in the real world.
Who this is for
- • Small teams with multiple people “experimenting” with AI
- • Owners, ops leads, and team leads who want some structure around assistants
- • Businesses that don't need a full platform yet, but want more than one-off prompts
What you'll work on
- • Real roles: support, ops, sales, internal ops
- • Actual assistants your team will use day to day
- • A simple stack diagram and playbook for your assistants
Curriculum at a glance
Four modules to go from scattered experiments to a small, intentional AI assistant stack.
Module 1
Mapping the work and choosing assistant “jobs”
- • Identify repetitive, text-heavy workflows across your team
- • Decide which assistants you actually need (and which you don’t)
- • Define clear “jobs to be done” and boundaries for each assistant
Module 2
Designing prompts, policies & personalities
- • Create prompt scaffolds that are reusable across tools
- • Set boundaries: what each assistant can and cannot do
- • Keep tone and behavior consistent with your brand and values
Module 3
Wiring assistants into your actual tools
- • Configure assistants in ChatGPT, Gemini, or similar tools
- • Connect to your docs, SOPs, and knowledge base safely
- • Pilot assistants with a small group and refine based on real use
Module 4
Launch, guardrails & improvement loops
- • Roll out assistants to the broader team with simple training
- • Add light guardrails, feedback channels, and basic metrics
- • Plan the next 2–3 assistants you might add later (or retire)
1. Mapping the work and choosing assistant “jobs”
Start with what your team actually does all week — then decide where assistants make sense.
We begin by walking through the work of your small team: support tickets, internal questions, sales follow-ups, content, and operations. From there, we choose a few clear “jobs” that assistants can help with.
- • Inventory common questions and recurring tasks
- • Group tasks into candidate assistant “jobs”
- • Decide which assistants should exist and which ideas can wait
- • Sketch responsibilities and boundaries for each assistant
Assistant job cards
You’ll leave this module with simple “job cards” for each planned assistant:
- • Name, purpose, and channels (email, docs, chat, etc.)
- • What the assistant should and should not do
- • Who owns it internally (and why it exists)
2. Designing prompts, policies & personalities
Make each assistant predictable by design — not a mysterious black box.
Next, we design the “inside” of each assistant: how it speaks, what instructions it follows, and what policies it must respect (tone, promises, escalation rules).
- • Create a reusable prompt scaffold for assistants
- • Add role, tasks, constraints, and style guidelines
- • Specify escalation rules: when to hand off to a human
- • Keep prompts maintainable so you can update them later
Assistant design templates
We’ll co-create a simple set of templates you can reuse:
- • “Assistant spec” docs (job, tone, rules, examples)
- • Prompt skeletons for new assistants
- • A short checklist before enabling an assistant for the team
3. Wiring assistants into your actual tools
Assistants are only useful if they live where the work already happens.
In this module, we configure your assistants in tools like ChatGPT, Google Gemini, or similar platforms, and connect them to the right documents, SOPs, and knowledge bases.
- • Set up assistants in the platforms you already use
- • Attach relevant docs, SOPs, and FAQs — without exposing sensitive data
- • Decide which channels each assistant belongs in (helpdesk, docs, internal chat, etc.)
- • Pilot with a small group and gather feedback
Assistant stack sketch
You’ll assemble a simple stack sketch that shows:
- • Which assistants exist and where they live
- • Which tools and data sources they connect to
- • How a typical request flows through the stack
4. Launch, guardrails & improvement loops
A small stack is only useful if people adopt it — and someone owns it.
Finally, we design the rollout: how you introduce assistants to the team, capture feedback, watch for issues, and decide what to adjust, add, or retire over time.
- • Plan a simple internal launch and training session
- • Create a feedback loop for “this worked / didn’t work”
- • Add light guardrails for safety and brand alignment
- • Keep a short roadmap for assistant improvements
Assistant stewardship playbook
You’ll leave with a small playbook that covers:
- • Who owns which assistants internally
- • How to request changes or new assistants
- • How often you’ll review usage and quality
Format & logistics
Built for small teams who need to keep serving customers while they upgrade how they work.
Schedule
- • 3–4 weeks total
- • Weekly live working sessions (60–90 minutes)
- • Assistant design and testing between sessions
Team
- • 3–8 participants
- • Mix of ops, support, sales, and a technical/contact person if you have one
- • Private cohorts per business
What you leave with
- • 2–5 live assistants wired into real workflows
- • Assistant specs, prompts, and stack documentation
- • A clear owner and improvement plan for each assistant
FAQ: AI Assistant Stack for Small Teams
Questions small teams usually ask before turning scattered AI use into a shared stack.
Do we need engineers to do this?
Not necessarily. Many assistant stacks can be configured in tools like ChatGPT, Gemini, or similar platforms with no-code features. If you do have technical folks, we can go a bit deeper on integrations — but it’s not required to get value.
How is this different from everyone just “using ChatGPT” on their own?
The difference is shared structure: clear assistant jobs, documented prompts and policies, and a sense of which assistants exist and how to use them. Instead of random one-off hacks, your team gets a simple, stable stack they can trust.
Is this safe with our customer and internal data?
Safety is part of the design. We'll talk about which data is appropriate to connect, how to use features like enterprise/“no training” modes when available, and how to keep sensitive workflows human-owned or tightly controlled.
What if we already have a couple of assistants configured?
Great — we’ll treat those as starting points. We can refine them, document them properly, and design the surrounding stack so they’re part of a coherent system instead of isolated experiments.
Ready to turn scattered AI experiments into a simple assistant stack?
This program helps your small team define, design, and ship a focused set of assistants that support your real work — without overbuilding a platform you don’t need yet.
If you’d like to pair this with AI-Powered Inbox & Docs, Simple Helpdesk, or Owner Dashboard, mention that in your note and we'll suggest a track.