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Poor usage
Good usage
Advanced usage
Free / Constrained
Free ChatGPT, free Claude, basic Copilot, bundled tools
Treating it like a search engine. Generic answers pasted into slides. Unedited robot emails.
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Using it as a thinking partner within its limits. Sharper prompts, heavier editing, realistic expectations.
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Working around the ceiling. A personal prompt library. Knowing exactly when the tool will fail.
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Pro / Competent
Paid ChatGPT, Claude Pro, Gemini Advanced
Owning a Ferrari and driving it in first gear. No custom instructions. Starting every chat from scratch.
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Custom instructions configured. Projects with files loaded. Pushing back on first outputs. Check, Edit, Own.
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A personal operating system. Skills or Custom GPTs for recurring tasks. Sharing them with your team. Infrastructure, not a tool.
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Agentic / Frontier
Claude Code, ChatGPT Codex, Google Gemini CLI
Failing to set up your workspace. Letting the agent run unsupervised. "Build me an app" without clearly specifying the problem. Automating a broken process.
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Setting up your custom instructions, rules, and tool permissions. Supervised stages. Explicit boundaries. Checkpoints where a human reviews before continuing.
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Entire workflows designed around agents. Humans design the system and check the output. Teams of people with teams of agents.
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The real problems
The real problem with Gen 1a

Free tools do teach foundational skills. That's helpful. But the limits are so severe that the opinion people form is "AI is mediocre." They learn to expect poor results. They stop pushing. The tool poisons the well: not by being useless, but by being just useful enough to seem representative.

The real problem with Gen 1b

The skill gap. It still takes considerable skill and knowledge to do long, complex tasks. You can generate a PowerPoint slide well, but not a hundred. You can do a piece of research well, but not a whole market research project in one go. The tools are capable; the techniques for sustained, complex work are not obvious.

The expectation gap. People get excited by what these tools can do for individual tasks. They immediately jump to wanting longer and more complex work, and get frustrated at the limits. The gap between excitement and sustained value is where most people get stuck, and where most quietly give up.

The real problem with Gen 2

Almost nobody in a corporate environment is here yet, and the main reason is perception, not capability. People think these tools are for developers. They're just as powerful for senior executives and junior analysts, but they're not perceived to be for them.

And because they're so powerful, they require care: clear boundaries to stop individuals making costly mistakes, and governance to manage security. But the first barrier is simply that most of the people who would benefit most don't know these tools are for them.

What to do about it

If you're on Gen 1a, push to Pro as soon as you can. The foundational skills transfer; the ceiling doesn't. If free tools are all you have for now, push to advanced usage as fast as you can — it's genuinely powerful, and it will change how your team works.

Simultaneously, advocate for Gen 2 being deployed in your organisation. That conversation usually starts with a single senior sponsor who's seen what's possible and can make the case to IT and leadership together. It doesn't need to be a company-wide rollout. A controlled pilot with the right people is enough to demonstrate the value.

We have a demo environment you can try. If you want to explore what agentic AI looks like in practice, ask us for a login and we'll set you up. We're happy to work with your IT and leadership teams to help them understand what this enables.

The question for leadership isn't "are we using AI?" It's "which cell are most of our people in, and is that good enough?"

To understand where your organisation sits as a whole, take the diagnostic. To see where the value is and how much you're capturing, try the value map.