Part 4 - Narrowing it down

Imagine being able to work with your AI assistant at any time, at the drop of a hat. That's the reality I'm living with my AI assistants right now.

For instance with Playbook Parts like this one, I go back and forth with Claude 15-20 times, providing feedback and refining the output until it's just right.

The beauty of this process hit home the other day when I was on a London bus, heading to a meeting. There I was, casually running a few rounds of revisions with Claude, further narrowing and improving the newsletter issue I was working on. This flexibility is a game-changer – it's like having a tireless assistant always at your beck and call. But that’s just a nice bonus!

Here’s the real power: the more I engage in this back-and-forth, the better my AI assistant becomes.

It's constantly learning exactly what I want, refining its understanding with each interaction. This is the power of the 'Narrowing' phase, and it's what we're diving into today.

Let’s get started

Why is Narrowing Crucial?

Remember when we talked about the RISEN framework for priming? We dropped the 'N' there, promising to come back to it.

Well, here we are! – Narrowing is that crucial final 'N'.

Narrowing is the process of refining and focusing your AI assistant's outputs through feedback and iteration. Importantly it’s a process. It’s not one and done and it's what transforms a good AI assistant into a great one.

If Priming (covered in Part 2) is like giving detailed onboarding instructions to a new employee then Narrowing is like providing constructive feedback on their tasks.

Both are vital – we'd do both with a human assistant, so why not with an AI?

Instead we get back poor first drafts from an AI and think, "the AI is bad". But that's not the case – we need to help it hone in on what we need, just like we would with a human assistant.

Techniques for Providing Effective Feedback

The key to successful narrowing is providing clear, constructive feedback. Remember, this is a conversation:

1. Use natural language: Just talk to your AI as you would to a human. Imagine you were sitting with a person giving feedback and you’ll do just fine.

2. Be specific: Point out exactly what works and what doesn't, down to individual words if required.

3. Explain why: Give reasons for your preferences. The more context you give the better.

4. Provide both positive and negative feedback: We tend to only give negative feedback but telling the AI what parts you liked is just as important. "This bit is good because..." and "This part needs work because..." are both required to help the AI hone in on your preferences.

5. Take your time: Unlike a human, AI has infinite patience. If it takes 20 rounds of revisions, so be it! Do that with a freelancer or staff member normally and you’d be wasting their time. But the AI doesn’t care!

Iterative Improvement

Narrowing is not a one-and-done process. It's about continuous, iterative improvement.

I like to think of it like sculpting (as if I can sculpt!) - you start with broad strokes, chipping away at the major issues first. This is things like “move this 4th paragraph section further up” or “this intro needs to be more punchy”.

As the shape begins to emerge, you move to finer tools, addressing more nuanced aspects of your AI's output. Maybe it’s written too many numbered lists (Claude loves lists…) and you want more prose - great, feed that back and it’ll go easy on the lists from now on.

Once you are basically happy with an output there’s a powerful final step you can take.

Go ahead and copy/paste or download your output from the AI and complete your final human edits and revisions until the final piece is ready to publish/deploy. For instance I’ll do all my final edits inside my newsletter software beehiiv.

Once all done we want to show our assistant the final product. Copy/paste back your final final version to Claude and tell it that this is end result. This gives it a golden example to learn from, allowing it to compare its work with your polished, human-edited final product. It's like providing a model answer - it helps the AI understand exactly what you're aiming for.

Remember, the goal of narrowing is to create an AI assistant that feels like a natural extension of yourself or your team. It's about infusing your unique knowledge, style, and expertise into the AI.

This might take time. But remember that once you’ve knocked your assistant into a place where it’s consistently producing solid outputs you now have a very powerful tool for repeat work. Training a human takes time and energy - the exact same is true with your AI assistant.