The pressure to "upskill with AI" is everywhere. Every day brings a new tool, a new headline, and a new list of "prompting hacks" you're supposedly falling behind on. It's no wonder so many people feel overwhelmed by the hype—and unsure where to begin if they want real, lasting proficiency.
I recently attended a one-hour AI proficiency session and walked away with insights that were both unexpected and deeply practical. The session was led by expert Ashley Gross, who used these principles not only to redesign her own workweek, but also to help an enterprise organization generate an additional $25 million in pipeline.
These lessons go far beyond clever tricks. They focus on mindset, strategy, and workflow design—the real difference between casual AI users and truly proficient ones. Here are the five most impactful takeaways.
1. Your "Why" Matters More Than Your "How"
Before diving into tools or techniques, Ashley shared her original motivation for mastering AI back in 2020. Her goal wasn't simply to be more productive—it was to reduce her 40-hour workweek to 15 hours so she could become a mom, without sacrificing the quality of her output.
That's a powerful starting point. It anchors technology in a meaningful, personal intention rather than a vague desire for "efficiency."
But the story doesn't stop there. By championing these same AI-driven workflows inside an enterprise organization, Ashley helped the company overachieve its pipeline targets by $25 million in just three months.
Key Insight: Using AI to improve workflows is a good reason. But having a deeper reason for why you want to be more efficient or productive is what makes the transformation stick.
2. The AI Learning Journey Is a Roller Coaster—and That's Normal
One of the most reassuring points was the acknowledgment of AI's inconsistency.
One day, you have an interaction with a large language model (LLM) that feels magical. The next day, you reuse the same prompt and get a confusing or completely incorrect answer that makes you wonder if the tool is even worth your time.
Ashley emphasized that this "wonky" roller-coaster experience is completely normal. Upskilling with AI is not a straight line, and expecting perfection only leads to frustration.
Helpful Reframe: We are currently interacting with the worst versions of generative AI we'll ever use in our lifetimes. From here, the tools only get better. That makes right now the best possible time to experiment, learn, and build confidence.
3. Use AI to Evaluate Other AI—Especially on Privacy
In the wild west of new AI tools, privacy policies matter—but they're often dense, legalistic, and hard to interpret. The solution Ashley shared was counterintuitive and brilliant: use one AI to vet another.
Her workflow was simple and empowering:
- Find the URL for a company's privacy policy (she used Anthropic, the makers of Claude, as an example).
- Paste that URL into a different AI tool, like ChatGPT.
- Ask it to summarize the policy in plain language—breaking it down by data collection, data sharing, user rights, and security practices.
Why It Works: This approach makes it easy to compare tools and understand how your data is being handled, without wading through legal jargon. It's a smart way to use AI to make safer, more informed decisions.
4. Go Beyond Prompts and Personalize Your AI's "Brain"
Good prompts matter—but Ashley pointed out something even more powerful: setting up your AI's long-term context.
She described features like ChatGPT's Custom Instructions as the AI's "brain." This is where you tell the system who you are, what you do, how you communicate, and what you expect. You can define your role, your audience, your writing style, and even formatting preferences (for example: "use bullet points," "avoid corporate jargon," or "keep responses concise").
If you're not sure how to write these instructions, Ashley recommended a meta-skill: ask the AI to help. Explain your role and goals, then ask it to draft communication instructions for you.
Ashley's Advice: "You can iterate on prompts all day, but if the AI doesn't understand your language, style, and communication rules at a foundational level, the output will never quite meet your expectations."
5. Audit Your Workflows with the "David Attenborough" Method
So how do you figure out which parts of your day are best suited for AI augmentation?
Ashley introduced a creative and memorable technique she calls the "David Attenborough" method.
Here's how it works:
- Start a video call with only yourself (using a tool like Google Meet).
- Turn on recording and transcription.
- Perform a routine work task while narrating everything you're doing and why—like a nature documentarian observing a creature in its habitat.
- When you're finished, take the transcript and paste it into an LLM with this prompt:
"Based on this workflow, tell me exactly where I can save time or improve with AI. Be specific. Point out steps that could be automated, done faster, or improved using ChatGPT. Categorize each as a manual or muscle task."
The Result: This method reveals inefficiencies and repetitive steps you might otherwise overlook—and highlights where AI can deliver the biggest gains.
A Final Thought
The overarching theme of the session was clear: true AI proficiency isn't about memorizing dozens of hacks. It's about building a thoughtful system grounded in intention, self-awareness, and strategy.
When you pair a clear "why" with smart workflow design and realistic expectations, AI becomes more than a tool—it becomes a genuine partner in creating both freedom in your life and measurable impact in your work.
So now that you have the strategies, the real question is:
What's the "why" that will drive your AI journey?