134 | Context Changes Everything

We talk a lot about AI tools and their capabilities, but there's one crucial element that often gets overlooked in all the excitement: context. It's the secret sauce that transforms a mediocre interaction into something genuinely helpful, whether you're talking to a colleague, a board member, or an AI assistant.

Context is simply the background information, constraints, and relevant details that help someone—human or machine—understand not just what you're asking for, but why you're asking and what would actually be useful. It's the difference between "Can you help me with a grant proposal?" and "Can you help me draft a compelling two-page summary for our arts education program's $50,000 grant application to the Johnson Foundation, which prioritizes measurable community impact?"

In the nonprofit world, where every conversation matters and time is precious, getting context right can make all the difference.

Real-World Example: The CEO Meeting

Recently, I had scheduled a meeting with the CEO of a nonprofit where I serve as board chair. We were planning to discuss how technology could support operations¹. A couple of days before the meeting, I realized I wouldn’t have access to my car, so I reached out to her thinking that we’d need to postpone the meeting. Instead of simply rescheduling, I shared that detail about the car with her (largely because we’ve become good friends over the years of our collaboration, so sharing a personal insight felt natural!). Knowing I lived nearby, she immediately suggested we meet at her home instead. That small piece of context turned a logistical hiccup into a simple, efficient solution—and reminded me how often the right context can spawn much better results.

This simple example shows how context works in human interactions—and the same principles apply when you're working with AI tools.

Three Types of AI Interactions—and the Role of Context in Each

In a recent StrefaTECH article (132 | Engineering Conversations: Moving Beyond the Perfect Prompt), I discussed how not all AI conversations are created equal. Understanding the different types of interactions can help you calibrate how much context to provide and when.

Transactional: Quick Q&A

These are your rapid-fire, get-an-answer-and-move-on interactions. Think of asking for a quick definition, a simple calculation, or a straightforward template. You don't need to write a novel, but even a sentence or two of context can dramatically improve the results.

For example, instead of "Write me an email template," try "Write me an email template for thanking first-time donors to our food bank, keeping it warm but professional." The difference in quality will be immediately apparent.

This is exactly like our CEO meeting example—a little context goes a long way, even in brief interactions.

When you give AI your prompt for a Transactional exchange, include all the context in your initial prompt that you think will help frame your query.

Conversational: Back-and-forth chats

These are the conversations where you're building something together with AI over multiple exchanges. Maybe you're brainstorming fundraising ideas, working through a communications challenge, or refining a program design.

Context on Conversational exchanges can be layered—you might start with the basics and add detail as the conversation develops.

The beauty of conversational interactions is that you can clarify and course-correct as you go. "Actually, I should mention that our target audience is primarily Spanish-speaking families" or "Let me add that we're working with a really tight timeline—the event is in three weeks."

Deep Research: The context-hungry category

This is where AI tools really shine, but only if you set them up for success. When you're asking for help with strategic planning, comprehensive research, or complex problem-solving, context becomes absolutely critical.

These interactions benefit from what I call "briefing a smart new team member." You want to provide the background, constraints, goals, and any relevant history that would help someone understand the full picture. Think about questions like: What's our organization's mission and size? What's worked or failed before? What are our resource constraints? Who are our key stakeholders?

When using Deep Research, the time you invest in providing good context upfront pays dividends in the quality and relevance of what you get back.

Tips for Providing Context Effectively

Think of it as briefing a smart new team member. You're not talking to someone who's been at your organization for years. Provide the background that would help a capable newcomer understand the situation and give you their best thinking.

Include relevant constraints, goals, and background. What are you trying to achieve? What limitations are you working within? What's the broader context that would help shape the response? These details help ensure you get suggestions that are actually actionable for your situation.

Don't assume the AI remembers everything (unless it does!). Some AI tools such as ChatGPT maintain context across a conversation, others don't. When in doubt, remind the AI of key details from earlier in your interaction, especially if you're building on previous exchanges, or ask it to summarize what it knows.

Be specific about your role and organization. "I'm the development director at a mid-sized environmental nonprofit" gives very different context than "I'm a volunteer coordinator at a small community center." The same question might get very different—and appropriately tailored—responses.

Better Conversations Start with Better Context

The habit of providing clear, relevant background information makes you a better collaborator with humans as well as with AI. When you brief your board chair, update your program manager, or explain a situation to your teenager², the same principles apply.

The good news is that context is a muscle you can build. Start experimenting with your next AI interaction. Try adding just one extra sentence of background or constraint. Notice how the quality of responses improves. Then try a more comprehensive briefing for a complex question.

Remember, AI tools are designed to be helpful, but they can only be as good as the information you give them. Context is what transforms a generic response into something genuinely useful for your specific situation and organization.

And finally, the choice is yours: Ask for generic advice, or invest a moment in the background details that get you solutions tailored to your actual situation. As you prepare to enter that next prompt, as always…

Make good choices.

1. As a note, this meeting resulted in me spending some time vibe coding with Replit. I have a prototype app for the nonprofit that I’m going to polish/finish over the next few weeks, plus ideas for an upcoming StrefaTECH article series on “the vibe coding experience.” It really is addictive (for geeks like me!).

2. OK, in the case of interactions with teens, brief is better, so perhaps take this with a grain of salt!