Prompting Is Overrated. Context Is Everything.

The Prompting Obsession

Everyone's talking about prompting. There are courses on "prompt engineering." LinkedIn is full of "10 prompts that will change your life." People are building entire businesses around teaching you to talk to AI.

Here's what they're not telling you: Prompting is maybe 20% of the equation.

The other 80%? Context.

What Context Actually Means

Context isn't just "information." It's the accumulated knowledge that makes your organization work:

• Documented processes — SOPs, workflows, how things actually get done
• Institutional memory — Why decisions were made, what's been tried before
• Domain expertise — The nuances only your team understands
• Historical patterns — What works, what doesn't, and why

Most organizations have this knowledge scattered across wikis, Slack channels, Google Docs, email threads, and—most dangerously—people's heads.

Why AI Fails Without Context

When you give an AI a prompt without context, you're asking it to solve your problem with generic knowledge. It's like hiring a consultant who's never seen your business and asking them to redesign your operations in an hour.

The difference isn't the prompt. It's everything the AI knows before you prompt it.

The Shadow AI Problem

Here's what happens when organizations don't build context intentionally:

People start using ChatGPT on their personal accounts. They feed it information about your business piecemeal. Each person builds their own fragmented version of your company's knowledge in separate AI conversations that disappear.

This is shadow AI—and it's happening in your organization right now.

The result: inconsistent outputs, duplicated effort, security risks, and zero organizational learning. Every conversation starts from scratch.

The Context-First Approach

Instead of teaching everyone "better prompts," build a single source of truth that makes every prompt better automatically.

This is what I call ContextOps: the practice of building, maintaining, and leveraging organizational knowledge so AI can actually work.

It starts with a Context Audit:

• Where does your organizational knowledge actually live?
• What's documented vs. what's tribal knowledge?
• Where are people using shadow AI workarounds?

Then you build the foundation:

• Consolidate scattered knowledge into structured documents
• Create a knowledge base that AI can actually use
• Set up systems so context stays current as your business evolves

Once you have context, prompting becomes trivial. You don't need elaborate instructions—you just ask questions and get answers that actually reflect your business.

The Investment Pays Off

Building context takes work upfront. But here's what happens when you do it:

• Every team member benefits from the same organizational knowledge
• New hires get up to speed faster
• AI outputs are consistent and accurate
• Institutional knowledge survives turnover
• You stop answering the same questions repeatedly

The organizations that win with AI aren't the ones with the best prompts. They're the ones with the best context.

What's Next?

If you're ready to build your context foundation, there are two paths:

• Context Engine Sprint — In 2 weeks, we ingest your documents, structure them into an AI-ready knowledge base, and demonstrate immediate value with your data. You walk away with a working system.
• Clarity Session — If you're not sure where to start, a 1-week Clarity Session gives you a context audit, single-source-of-truth blueprint, and 2-3 quick wins to pursue.