Hey there 👋

I hope you’re work-year is off to a great start!

This week, we’ll take a closer look at how to use AI as a strategic thought partner that challenges your assumptions, asks uncomfortable questions, and synthesizes data points to help you think things through.

We'll cover the techniques for extracting deep insights from AI, the framework for building a marketing plan using AI reasoning, and the art of strategy prompting to make your life easier as a marketer.

Let’s go!

Only a few companies are realizing extraordinary value from AI today, things like surging top-line growth and significant valuation premiums. Many others are also experiencing measurable ROI, but their outcomes are often modest—some efficiency gains here, some capacity growth there, and general but unmeasurable productivity boosts. These results can pay for themselves and then some. But they don’t add up to transformation. [Source: PwC] 

Mastering Prompt Engineering: Why Your Skills Are More Critical Than Ever for the AI Agent Revolution. Prompt engineering is hot again. Not that it ever went away, but there was a hot minute when every AI expert said that prompting was dead and no one would ever need to learn it. Well, that was before agents. And I don’t just mean the big, heavy,  super technical ones. [Source: Christopher S. Penn]

Best practices for LLM prompt engineering. The goal of prompt engineering is to design inputs that guide LLMs to generate desired outputs. The quality of a prompt directly influences the relevance, accuracy, and coherence of the model's responses. [Source: Palantir] 

The journey from using LLMs as content generators to using them as strategic advisors represents a shift in how we think about AI in business. It requires a different mindset, different prompting techniques, and a different understanding of what LLMs are capable of.

At the most basic level, LLMs are sophisticated pattern-matching engines. You give them a prompt like "Write a social media post about our new product," and they generate content based on patterns they've learned during training. This is useful for execution, but it's not strategic thinking.

At a higher level, modern LLMs can reason. They can take multiple pieces of information, synthesize them, and draw logical conclusions. They can analyze trade-offs, identify risks, and suggest alternatives, and this is where strategic thinking begins to emerge.

At the highest level, advanced LLMs can engage in true strategic thinking when given sufficient context. They can understand your business, your market, your competitive position, and your constraints. They can then help you think through complex strategic decisions, challenge your assumptions, and explore scenarios you might not have considered.

The key difference between Level 2 and Level 3 is context.

A Level 2 LLM can reason about a problem in isolation, while a Level 3 LLM can reason about a problem in the context of your specific business situation, market dynamics, and strategic objectives.

Instead of using AI to write copy or generate ideas, you can use AI to help you think through your strategy. You can ask it to analyze your competitive position, identify market opportunities, synthesize customer research, and help you build a coherent strategic plan.

The benefit is better strategies and faster strategy development.

What used to take weeks of research and analysis can now be done in days, which frees up your team to focus on the harder work.

The first principle is to provide the LLM with a comprehensive context, including information about your business model, target customers, competitive landscape, current performance, and strategic objectives.

The more context you provide, the better the LLM can reason about your specific situation. A generic question will produce generic answers, and a detailed question will produce much more valuable insights.

Example:

Generic: "What should our marketing strategy be?"

Strategic: "We're a B2B SaaS company in the project management space. Our target customers are mid-market enterprises (100-1000 employees) in tech, finance, and professional services. We have 5,000 customers with 40% annual churn. Our main competitors are Asana, Monday.com, and Jira. Our differentiation is a superior mobile experience and AI-powered task automation. We have a $2M annual marketing budget. What should our 12-month marketing strategy focus on to reduce churn and accelerate growth?"

The second principle is to ask the LLM to show its reasoning, and not just provide answers. This serves two purposes: it helps you understand how the LLM arrived at its conclusion (so you can evaluate it), and it often leads to better answers because the LLM is forced to think through the logic.

Example:

Weak: "What channels should we prioritize?"

Strong: "For each marketing channel (content marketing, paid search, paid social, partnerships, events), analyze: (1) the potential reach within our target customer segment, (2) the expected conversion rate based on our product and positioning, (3) the cost per acquisition, and (4) the lifetime value impact. Then recommend which channels to prioritize and explain your reasoning."

The third principle is to treat strategy prompting as an iterative process. You ask an initial question, evaluate the response, then ask follow-up questions to dig deeper or explore alternatives.

This iterative approach helps you move from surface-level insights to deeper strategic thinking. Each iteration builds on the previous one, allowing you to explore different angles and refine your thinking.

Example Iteration:

The fourth principle is to actively challenge the LLM's assumptions and push back on its reasoning (because it gets sh*t wrong all the time!). This helps you avoid accepting answers just because they came from an AI. It also often leads to better thinking because it forces the LLM to defend its reasoning or reconsider its approach.

Example:

AI Response: "You should focus on content marketing because it has the lowest cost per acquisition."

Your Challenge: "I understand the cost per acquisition is low, but what about the time to conversion? Our sales cycle is 6 months. How does that change the analysis?"

The fifth principle is to remember that the LLM is a thought partner, while you remain the decision-maker. The LLM can provide analysis, identify patterns, and suggest options, but the final decision should rest with you, informed by your business judgment, intuition, and knowledge of your organization.

The best results come from combining AI analysis with human judgment. The AI provides the reasoning and analysis while provide the context, intuition, and decision-making.

Use this comprehensive prompt with your preferred advanced LLM to develop a 12-month marketing strategy for your organization.

The Scenario: You are the VP of Marketing for a mid-market B2B SaaS company. Your CEO has asked you to develop a comprehensive 12-month marketing strategy that will drive 30% revenue growth while reducing customer acquisition cost by 15%.

The Prompt:

You are a strategic marketing advisor. I'm going to provide you with information about our company, market, and current performance. Your role is to help me develop a comprehensive 12-month marketing strategy that achieves our growth objectives while improving our unit economics.

Here's the context:

Company: [Insert your company name, mission, and value proposition]

Product: [Insert product description, key features, and differentiation]

Target market: [Insert target customer profile, market size, and growth rate]

Current performance: [Insert current revenue, customer count, churn rate, CAC, LTV]

Competition: [Insert main competitors and competitive positioning]

Constraints: [Insert budget, headcount, and organizational constraints]

Strategic objectives: Grow revenue by 30% and reduce CAC by 15% within 12 months.

Now, please help me develop a 12-month strategy by addressing these questions:

For each section, please explain your reasoning and highlight any assumptions or trade-offs.

Here's a prompt to make cute little diorama lamps:

A [subject] is [doing something] in a [place]. Isometric 3D cube diorama with internal lighting, cute chibi figurine style, matte PVC material, big head/small body. Neutral background on a table in a dark room. Enclosed in a cube. Fill the diorama with many cute little details. Add delicate imperfections like dust, scratches, and textures to make it real.

The "Invisible AI" Strategist is a thought partner that helps you think more clearly, more quickly, and more comprehensively. It gives you the ability to ask better questions, to consider more options, and to make more informed decisions.

Brands that employ strategy prompting develop better strategies faster, adapt to market changes more quickly, and execute more effectively, and they do it with smaller teams and tighter budgets, because they've figured out how to think with AI.

Until next time, keep exploring the horizon. 🌅

Alex Lielacher

P.S. If you want your brand to gain more search visibility in Google AI Mode, ChatGPT, and Perplexity, reach out to my agency, Rise Up Media. We can help you with that!