New Years Resolution: Stop Treating Generative AI Like a Tool
The advancements in AI models are staggering. It's time to actually tap into them.
Over the past two(ish) years, I’ve been helping creatives, strategists, account managers, and a slew of others navigate the rapidly evolving world of AI. I constantly get questions like, “What’s the best way to prompt ChatGPT to write my email?” or “Do you have a ‘prompt glossary’ I can use?”—as if AI were a vending machine that dispenses answers in response to well-crafted codes. Sure, these prompt hacks are genuinely useful for getting started. But it tells me that people are not grasping the true flexibility and depth of these models. In the upskilling programs I’ve led, I found that for the majority, once people find a formula that works for writing emails, summarizing articles, de-wording slides, or some other mundane task, they stop. No curiosity, no further exploration—just rinse and repeat. It’s akin to using a NASA-grade supercomputer to track your household budget. Yes, you get a job done, but you’re completely ignoring 99% of the computer’s true potential.
Time and again, I’ll demonstrate more advanced AI capabilities—like building a GPT trained on a particular business case and having it analyze my slides or spreadsheets, creating a brand identity analysis assistant that evaluates look, tone, and feel, or whatever the flavor of the day is. The most common response? “I had no idea it could do that!” It’s not a lack of understanding. It’s a lack of experimenting.
The same logic applies to bringing AI into your work. When you limit it to routine tasks, you’re underestimating what it can do for your problem-solving, your creativity, and even your vision. Sure, the basics—emails, summaries, and proofing—are helpful starting points, but they’re just that: a starting point.
The real magic happens when AI becomes an extension of your own cognitive process (See
’s work for some amazing thinking on this)—an ongoing partner that challenges your assumptions, offers fresh angles and co-creates solutions you’d never arrive at alone. The true power of AI lies in making it an extension of your own thinking. Not just a task rabbit.What you get when you treat AI like a tool
Many people see AI in transactional terms:
“Write this email.”
“Generate three taglines.”
“Summarize last week’s market report.”
These tasks are often where we start—because they’re easy wins. But they also tend to reinforce a “one-and-done” mindset. You ask, the AI executes, end of story. In this sense, AI is just a more efficient version of a standard office tool, a timesaver that frees you up for “real” thinking.
Where this mindset falls apart
Tunnel Vision on Immediate Outputs
You see only what’s on the page—an email draft or a quick tagline—while missing the strategic possibilities AI can unlock. The AI’s potential to analyze patterns, spot anomalies, or even suggest cross-industry insights goes untapped.Complacent “One-and-Done”
Instead of pushing the conversation forward, you treat it like an endpoint. I’ve seen leaders try a few prompts, get mediocre results, and conclude “AI isn’t there yet.” But often, the real issue is not using AI iteratively—probing further with follow-up questions, critiques, or scenario testing.Underestimating AI’s “Second Brain” Potential
AI can do far more than replicate text. It can serve as a “second brain” that tests assumptions, models hypothetical futures, or generates out-of-the-box ideas. If you’re only ever asking for a summary or a rewrite, you’ll never see the deeper creative or strategic dimensions AI can offer.
How to shift this mindset
1. Give It More Context
Most people type in a one-liner prompt and expect miracles. But AI thrives on rich information. Feed it entire documents, brand guidelines, data sets, even images or audio transcripts if available. Some platforms (like Claude’s “Projects” or GPT’s “Custom Instructions”) let you create a larger contextual universe.
Example: Instead of “Help me write this blog post,” upload your entire research doc—stats, anecdotes, competitor analysis—and instruct the AI to synthesize it. You’ll get outputs that feel more like a well-briefed consultant rather than a random freelancer.
2. Have it push your thinking
AI isn’t just there to produce a neat final product; it can critique your ideas, point out potential flaws, and even play devil’s advocate.
Example: “Here’s my new go-to-market strategy. Where are the logical weak spots? Critique each step like you’re my harshest investor.”
Outcome: You get a set of challenges or counterpoints you might never have thought of, helping you refine your plan before you even present it.
3. Never stop at one-offs
One prompt is rarely enough to explore the full depth of AI’s reasoning. Turn it into a conversation—iterate, refine, pivot.
Example: Ask AI for a set of brand messaging pillars. Then ask it to re-examine them from a consumer psychology angle. Then ask for a risk assessment if you pivot to a different audience. Each iteration digs deeper.
Generative AI is only going to get more collaborative - get ready for agents
Tune into any leader of an AI company. Agents are all the rage. We’re about to transition from using simple ChatGPT/Claude/Gemini chatbots to deploying highly customized agents—AI systems that retain context, build specialized “memories,” and proactively offer solutions. Tools like ChatGPT’s custom GPTs or Claude’s Projects are already hinting at this next phase. But it’s going to be so, so much more impactful than these.
What is an AI agent, really?
An AI agent is more than a chatbot or search engine. It’s a system that not only responds to your immediate questions but also operates with a degree of autonomy, proactively learning from context, storing relevant information as “memory,” and adapting its actions over time.
Unlike simple “prompt-response” setups, AI agents can handle multi-step objectives without requiring you to micromanage every move. They maintain an ongoing awareness of your goals, constraints, and preferences and use that information to refine their outputs. In practical terms, this might mean scheduling tasks, analyzing data, anticipating problems, or even recommending strategic pivots—all while retaining the broader context of your project or organization.
By pulling in domain-specific knowledge—whether that’s legal frameworks, financial analytics, creative direction, or something else entirely—agents effectively become digital collaborators that reduce friction across your entire workflow. Rather than just fetching quick answers, they can help you discover blind spots, generate innovative ideas, and even challenge your assumptions.
At their best, AI agents shift from being a static tool you “use” to an active partner you “collaborate with”—integrating into your processes, scaling to meet multiple needs, and continuously evolving to mirror your strategic, creative, or operational mindset.
Why it matters (Co-Intelligence at scale)
Scalability on Steroids
Traditional teams get overburdened doing multiple tasks simultaneously. An agent can handle numerous parallel tasks—processing new data, generating fresh strategies, and analyzing KPIs—without losing focus. This is especially game-changing for teams running lean.Deeply Adaptive Intelligence
Over time, the agent “learns” your brand’s aesthetic, your risk tolerance, your strategic preferences. It stops feeling like an outsider and more like a team member who just “gets it.”Horizons Beyond Human Bandwidth
Human teams have limited time and mental energy. An agent never tires—it can keep generating and testing novel hypotheses around the clock, fueling you with new perspectives every day. The result is a form of co-intelligence that extends your own thinking beyond its typical boundaries.
The bottom line
The more you explore and push the boundaries of today’s models, the better positioned you’ll be to ride the agent wave when it crashes onto your desk.
Shifting from a “tools mindset” to an “collaboartive mindset”
Embrace AI as a thought partner
To realize AI’s true potential, you must move from a “tools mindset” to a “collaborative mindset.” It’s not a single leap—it’s a series of micro-shifts in how you engage, experiment, and iterate with AI.
Engage Curiosity
Surface-Level Prompt: “Summarize this report.”
Augmented Prompt: “Attached are the 5 most recent reports. What are the hidden trends or potential blind spots in this report? Critique my interpretation and propose alternative angles I might be missing.”
Outcome: Instead of a summary, you get a more thorough analysis that challenges your assumptions.
Experiment Relentlessly
Why: AI thrives on inputs and iterative feedback. When you push its boundaries, it can reveal creative solutions or highlight your biases.
Example: Don’t just use AI for marketing copy. Ask it to design an end-to-end customer journey, from awareness campaigns to post-purchase engagement. Then build a GPT trained on that journey and have it write the copy you need.
Customize for Depth
Contextual Integration: Feed your AI relevant data (brand voice documents, style guides, sales history, etc.) so it “knows” your world. Give it as much context as possible and use GPTs and Projects so you don’t have to repeat the process.
Outcome: Richer, more nuanced outputs that feel highly tailored—like a colleague who’s been part of your team for years.
The rationale for these shifts
Depth vs. Breadth: The “tools mindset” is about breadth—handling many tasks quickly. The “collaborative mindset” fosters depth—collaborating on specific tasks but uncovering richer, more transformative insights.
Integration: Rather than popping in and out of AI when you remember, let the AI remain a persistent thread in your workflow.
Cognitive Extension: When trained correctly, AI can be an extension of your cognition. When fully integrated, your thinking capacity expands significantly.
Conclusion: the magic is in the mindset
Treating AI like a tool is the biggest waste of its potential—and yours. It’s an invitation to remain at the shallow end of what’s possible. True augmentation happens when you start seeing AI as an active collaborator, capable of sparring with your ideas, pushing your creativity, and broadening the scope of your strategic thinking.
Parting Challenges:
Reflect: Next time you open a chat interface, challenge yourself to go beyond a simple request. Ask AI to test your assumptions, propose alternative angles, or even adopt different persona lenses (like an economist, a sociologist, or a futurist).
Integrate: Pick one project or process this month where AI becomes a consistent partner, not just a sporadic tool. Keep track of how it shifts your thinking or uncovers hidden insights.
Evolve: Create feedback loops for both you and your AI. Let it critique your ideas—and critique it right back.
By letting AI step into a co-creator role, you expand your own capacity to think, create, and solve.
So the question remains: are you content with using AI to just scratch the surface, or are you ready to dig in and discover the gold?