Resources
Everything on this page is free and on-page. No email required. No downloads. No forms. If something here helps you think more clearly about your business and AI, that is enough.
AI Readiness Assessment
10 questions. Plain language. An honest result with a clear next step — specific to where you are right now.
Question 1 of 10
When you hear the phrase "AI for your business," what is your honest first reaction?
Question 2 of 10
How would you describe the current state of your business processes — the way things actually get done day to day?
Question 3 of 10
Think about the most repetitive task in your business right now — the one that takes time every week without requiring your real expertise. What best describes it?
Question 4 of 10
Have you tried any AI tools in your business — ChatGPT, a chatbot, an automation tool, anything?
Question 5 of 10
How do leads currently find out about your business — and what happens after they do?
Question 6 of 10
If an AI system made a mistake while representing your business to a client — gave wrong information, made a promise you can't keep — how prepared are you to handle that?
Question 7 of 10
How would you describe your comfort level with technology in general?
Question 8 of 10
What is the biggest thing holding your business back from growing the way you want it to?
Question 9 of 10
How do you feel about the idea of AI representing your business to a potential client — answering questions, qualifying them, routing them to the right next step?
Question 10 of 10
When you think about investing in AI infrastructure for your business, what best describes where you are?
Questions to Ask Any AI Vendor
If a vendor can't answer these clearly, that is your answer. Save this page. Use it every time.
AI Glossary
No textbook definitions. No jargon dressed up as explanation. Just what these words actually mean for your business.
AI Agent
A system that can take action on its own — answer questions, route requests, escalate to a human — without being manually operated for every interaction. Not a chatbot. A chatbot follows a script. An agent reasons.
Large Language Model (LLM)
The underlying technology that powers most AI tools — ChatGPT, Claude, Gemini. It processes language and generates responses based on patterns learned from enormous amounts of text. The model is not the product. What's built on top of it is.
Prompt Engineering
The practice of crafting the instructions you give an AI to get better outputs. It matters — but it is the surface layer, not the foundation. A well-prompted bad setup is still a bad setup.
Knowledge Base
The body of information an AI is trained on or given access to. For a business AI agent, this is what makes it yours — your services, your voice, your answers. The quality of the knowledge base determines the quality of every response.
Guardrails
Defined limits on what an AI will and will not do. What it answers, what it escalates, what it never touches. Guardrails are not restrictions — they are what make an AI system trustworthy enough to represent your business.
Human-in-the-Loop
A design approach that keeps a human in the decision chain at the right moments. The AI handles what it can handle well. When it reaches its limit — or when the stakes are too high — a human steps in. Built in on purpose, not bolted on after a problem.
Automation
Using technology to perform a task without human intervention each time. Automation is not AI — a light on a timer is automation. But AI can power automation that adapts and responds rather than just executing a fixed sequence.
Hallucination
When an AI generates something that sounds confident and correct but is factually wrong. It is not lying — it is pattern-matching without knowing the difference. Guardrails and a well-scoped knowledge base are how you limit this in production systems.
RAG (Retrieval-Augmented Generation)
A method of giving an AI access to a specific body of information — your documents, your FAQs, your knowledge base — so its responses are grounded in your actual content rather than general training data.
Fine-Tuning
Training an AI model further on specific data to shape its behavior for a particular use case. Not always necessary — and often overkill for small business applications. RAG is usually the right starting point.
API
Application Programming Interface. A connection point that lets one piece of software talk to another. When your AI agent connects to your CRM, your calendar, or your website — it does that through APIs. You don't need to understand how they work, but you should know they exist.
AEO (Answer Engine Optimization)
Structuring your content so AI-powered search tools — ChatGPT, Perplexity, Google's AI Overviews — can accurately represent your business when someone asks a question relevant to what you do. The next layer beyond SEO.
Before You Build
These are not technical questions. They are business questions. If you can answer all of them clearly, you are ready to build. If you can't, that is where to start.
What is the one specific problem I want AI to solve?
Not AI in general. One problem. Lead qualification, after-hours responses, appointment routing — pick one. Businesses that try to solve everything at once end up solving nothing reliably.
What does success look like — specifically?
If you cannot define what winning looks like before you build, you cannot measure whether you won after. A number, a behavior, a time saved — something concrete.
What information does the AI need to do this job well?
Every AI system is only as good as what it knows. What services do you offer? What are your prices? What are the most common questions you get? What should it never say? This is your knowledge base — and it starts here.
Where does the AI stop and a human begin?
There are interactions that belong to you — conversations that require your judgment, your relationships, your authority. Know where that line is before anything goes live. This is your guardrail architecture.
What happens when it gets something wrong?
It will. Not often if it's built right — but eventually. What is the recovery process? Who finds out? How is it corrected? A business that hasn't thought through failure mode isn't ready to deploy.
Do I own what gets built?
Your knowledge base, your agent, your deployment — these should belong to you. Not to a vendor's platform, not to a subscription that disappears when you stop paying. Confirm ownership before you build anything.
Who maintains this after it goes live?
Your business changes. Your services, your pricing, your clients' questions — all of it evolves. An AI system that isn't maintained becomes outdated and then unreliable. Know who is responsible for keeping it current.
Ready to move from clarity to action?
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Hello. I'm Soli — I know this business inside and out. What can I help you figure out today?