Two Clients Changed How I Use AI.

READ TIME: 4 MINUTES

This newsletter was built by talking to Claude.

Not typing a prompt. Talking — the way I'd walk through an idea with a colleague. Then using the memory I've built inside Claude about my business and my stories to shape it into what you're reading now.

I'll explain how that works. But first, two clients who pushed me to get here. 

What Rob built

Most candidates use AI for interview prep the same way: research the company, look up the role, review a few likely questions.

Rob did that. Then he went further.

He pre-loaded his interview stories and answers into Claude as a dedicated project — along with a prompt built around his specific experience and the role he was targeting. 

He built a workflow. 

One that could prepare him for any interview based on his context, not generic advice pulled from the internet.

Then he started recording his interviews. After each one, he uploaded the transcript and used AI to get feedback on what landed and what didn't. We leveraged that feedback to focus on the specific areas of interview prep that needed refinement.

That same transcript became the foundation for his follow-up email.

He wasn't just using AI. He was running a system.

What Michael is building

Michael took a different angle.

He took an AI course to prepare him to step into a new role and leverage AI.  

It didn’t stop at the course.  

While running his job search, he vibe-coded a personal website that showcases his experience — built with AI.  It’s his resume on steroids.  It helps him stand out and demonstrate his ability to learn and implement what he's learned.

He's not waiting for AI to be part of his job. He's making it part of how he shows up as a candidate.

Where AI breaks down in the job search

Candidates coming in with AI-generated resumes. And while parts of them are solid, they're often missing the pieces that actually matter to a hiring manager — the specificity, the context, the language aligned to the target role.

The reason is almost always the same.

They didn't know what a hiring manager looks for. So they couldn't build that into their prompt. And they hadn't clearly defined the role they were targeting. So the resume wasn't built with the end in mind.

The AI did exactly what it was told. The problem was the instructions.

This is where most candidates get stuck. 

AI can help — but only if you know what good looks like. 

In SaaS sales, that means understanding what a recruiter skims for in 10 seconds, what a hiring manager needs to see, and how to translate your experience into the language of the role you want. Across your resume, LinkedIn profile and interviews.  

Without that knowledge, the output is only as strong as the input.

What I learned this weekend

After watching Rob and Michael approach AI from completely different angles, I knew I needed to sharpen my own skills.

I had been using AI to help refine language across emails, social media, and resumes — but my prompts were average at best.

I took a course with Natalie MacNeil targeted for small business owners like me and two things she taught immediately clicked that are applicable for you whether you’re job searching or using AI in your current role. 

Here they are:

1. Memory

• Before you can prompt well, AI needs to know you.

Natalie calls this building your memory — pre-loading the context that makes every output actually relevant. From a business perspective, that's your brand, your message, your story. I've built all of that out inside Claude for my coaching practice.

For candidates, the equivalent is your story bank — your roles, your results, the examples that show how you think and what you've built.

Here's where it gets interesting.

Imagine sitting down and talking through your experience — the way you'd walk me through your background in a coaching session. You give AI your stories. Then you give it a framework for how to structure the output.

The framework I use with clients isn't standard STAR. It's R-STAR.

Results → Situation → Task → Action → Result

Lead with the outcome. Then tell the story. That's what lands in interviews.

With your story bank pre-loaded and R-STAR as the structure, AI can build your interview answer guide for you — tailored to your actual experience, not a generic template.

Rob figured this out on his own. It's one of the reasons his interview prep is sharper than most.

2. The 3 C's

• Once your memory is built, the quality of your prompts determines the quality of your output.

Natalie's framework: Clarity. Context. Cues.

• Clarity: Be specific about exactly what you want — not "help me with my resume," but what is the desired goal and AI’s role. 

• Context: Feed it the right background — the role you're targeting, what a hiring manager in that function cares about, your specific results

• Cues: Tell it how to respond — provide guidance and examples of what good looks like

The difference between a vague prompt and one built on these three things is dramatic.

Before:

Help me prepare for an interview with [company] for the [role].

After:

I need you to help me prepare for interviews at [COMPANY NAME] for the [ROLE] position. Leveraging my background that I shared, I want you to help me answer the following questions.  Please provide a document as the output.

About the company:

• What they sell, their market position, or recent news

• Elevator Pitch on the company

• Ideal customer profile

• What their sales process looks like

Interview prep referencing my background:

• My elevator pitch, connecting my background to the role

• Why do I want to work for this company

• Why I am looking to leave [company] 

• 2-3 relevant deals I should prepare

Same tool. Completely different output.

Where this is heading

Most AI tools aren't built for SaaS sales. They don't know what a SaaS hiring manager is looking for. They can't coach a discovery call the way a sales leader would. They can help — but only if you know how to direct them.

That gap is something I'm actively working on. My goal over time is to build something specific to this world — resume feedback, interview coaching, role-play — grounded in what actually works in SaaS sales hiring. More on that as it develops.

For now, here's the practical takeaway.

AI is available to every candidate. That's not the edge.

Knowing what good looks like, building your memory, and prompting with Clarity, Context, and Cues — that's the edge.

The candidates who figure that out will move faster, show up sharper, and land stronger.

I'm working on ways to make that easier. Tools built specifically for SaaS sales, grounded in what hiring managers actually look for. Still in progress — but this is the direction.

And this newsletter? Built exactly that way. I talked through the ideas, Claude helped shape them, and the memory I've built about my business and my clients made it feel like mine.

Because it is.

Hit reply and tell me: where are you currently using AI in your job search — and where is it falling short? I read every response.

To clarity and confidence in your career path,

Amanda

See you next Sunday.