Context: The Hidden Key to Better AI
A guide to understanding the importance of context when using AI, and how providing the right background and prompts can lead to more meaningful and accurate results.
Here’s the truth: Most people get mediocre results from AI because they don’t give it what it needs — context.
Think about it like hiring a new employee. You don’t just say, “Write me a report.” You onboard them. You give them background, goals, examples. You help them understand what good looks like.
Same with LLMs.
At Atheni, we see context in two layers:
- Foundational context — What goes into your Claude Project Areas or custom GPT setup. This is your tone, your role, your values, your workflows. Once it’s in, every prompt builds on it. It's kind of like the initiation pack you might give a new employee.
- Prompt context — What you include in each ask. “I’m heading into a board meeting and need a one-pager that hits X, Y, and Z.” It's like the chat you'd have with a junior before you set them off on a project.
When people say “the AI isn’t getting it,” the AI probably isn’t being told what “it” is.
That’s why Atheni starts with configuration. We collect your communication style, your team dynamics, even your blockers — so you don’t have to re-teach your AI every time.
Don’t just ask for output. Give your AI a map. Context isn’t optional — it’s the key to leveraging AI for value.
