Artificial intelligence is everywhere—but even the best artificial intelligence model can’t do much with random, disconnected information. For AI to deliver real business value, it needs to understand your world, your goals, and your workflows. This is what we mean by “context”—and it’s exactly why Calk AI was built from the ground up to solve the context problem.
Let’s dig into what context means for AI, how large language models (LLMs) actually process information, how to use artificial intelligence in your business for real results, and how Calk AI enables teams across your company to share, use, and build on each other’s knowledge.
What is context in ai? Why does it matter?
Context is everything that surrounds a question, a workflow, or a data set:
- Who is asking (their role, goals, history)
- What is being asked (intent, domain, priority)
- Why it matters (business outcome, urgency, constraints)
- Where and when it’s happening (location, timing, customer, market, etc.)
Traditional AI might give you answers—but if it doesn’t “know” the context, it will give you generic, out-of-touch, or even wrong answers.
With context, AI can:
- Personalize output to your audience
- Avoid costly misunderstandings
- Link data and insights across the company
- Drive actual business outcomes
This is why, if you want to know how to use ai in your business, context is the #1 thing to get right.
How large language models (LLms) actually process data
To understand the “context problem” (and why your first attempt at how to use ai in business can disappoint), it helps to know how LLMs work under the hood:
- LLMs don’t read all your data at once: they process information in “chunks” (pieces of text or data), each limited by a “context window”—the maximum amount a model can handle at once.
- Chunking is critical: if you dump a massive document or multiple sources into an LLM, it will break it into chunks. If these chunks don’t keep the meaning or relevant context together, the model may misunderstand relationships—or simply forget key points.
- The model doesn’t “know” your company by default: unless you give it the right context—integrations, knowledge bases, user history, specific instructions—its outputs are only as good as what you feed it right now.
- Scoping matters: too much irrelevant information? The model gets distracted (or gives vague, generic answers). Too little context? It can’t connect the dots.
That’s why most people’s first attempts at how to implement ai in business feel a little underwhelming. They get the hype, but not the results.
What a context-rich agent prompt looks like in Calk AI
If you’re exploring how to make an a, how to create an ai, or build a truly useful custom gpt, you need more than just access to a model—you need the right prompt, infused with your real business context.
Here’s an example of a context-rich agent prompt used at the heart of a Calk AI agent:
🤝 Expert Outreach Specialist Prompt
Craft highly personalized follow-up messages by analyzing client data, previous interactions, and business context.
📋 Critical Information
- Thoroughly analyze all available client information
- Identify key points of relevance and potential connection
- Determine the appropriate tone and level of formality
- Craft a message that demonstrates genuine understanding of their situation
- Include a clear, specific next step or call to action
✅ Do
- Reference specific details from previous interactions or client research
- Acknowledge any previous touchpoints or conversations
- Connect your message to the client's known challenges, goals, or interests
- Provide genuine value in every outreach (insight, resource, or solution)
- Personalize beyond just using their name (industry challenges, company news, etc.)
- Craft subject lines that are specific and relevant, not generic
- Include a clear, low-friction next step
- Vary your approach based on outreach stage (initial, follow-up, re-engagement)
- Adapt tone to match the client's communication style and industry norms
🚫 Don't
- Use obvious templates or generic language that feels mass-produced
- Focus exclusively on your product/service without connecting to their needs
- Include irrelevant personal details that feel forced or insincere
- Write excessively long messages that require significant time investment
- Use manipulative tactics or artificial urgency
- Ignore the context of previous interactions or outreach attempts
- Send the same follow-up approach to different personas or industries
- Make claims about their business challenges without supporting evidence
A quick primer: how LLMs “think” about context
How LLMs Handle Context
Context window
What it means:
The amount of info the model can “see” at once
Why it matters:
Too much = overload; too little = bad answers
Chunking
What it means:
Splitting data into processable pieces
Why it matters:
Poor chunking loses meaning/context
Scoped input
What it means:
Giving the model only what it needs
Why it matters:
Increases accuracy and relevance
Persistent context
What it means:
Keeping context updated as your org evolves
Why it matters:
No more “resetting” or re-explaining every time
Conclusion: the Calk AI way (and the future of artificial intelligence companies)
To get great results from AI, you need to do more than just “ask questions.” You need a platform that deeply understands your context—and lets you share it across teams, tools, and workflows. That’s the Calk AI way.
Calk AI delivers:
- AI that finally “gets” your company
- Agents that stay in sync with your evolving knowledge
- Teams that work faster and smarter, with true autonomy
- A foundation that supports open source artificial intelligence and lets you orchestrate the best ai apps and models for each job
If you want to know how to use ai in business or even how can I use ai in my business without hiring a team of engineers, Calk AI is your answer.
And as the question shifts from “what jobs will ai replace?” to “what new opportunities will AI create?”—Calk AI is here to make sure your teams stay ahead.
Ready to see Calk AI in action?
Request a demo and discover how shared context, workflow orchestration, and true autonomy can transform your business—far beyond what any “custom gpt” can offer.
👉 Get Started With Calk
