Mastering the Prompt: Unlocking Deeper AI Insights & Business Opportunities

TODAY'S HIGHLIGHTS:

• Advanced Prompting: Sequential instructions, clarity, and refinement are key.

• Choosing the Right LLM: Different models excel at different tasks (research, writing, coding).

• Customization & Memory: Leverage features for consistent, personalized AI interactions.

• AI in Business: Government contracting opportunities and global adoption challenges.

INTRODUCTION:

This episode of AI Biz Hour dove deep into the art and science of prompting Large Language Models (LLMs) for business applications. Hosts Andy Wergedal and John Allen, along with guests, shared invaluable strategies for getting better outputs, understanding the nuances of different AI models, and identifying real-world business opportunities, including navigating the lucrative government contracting market with AI.

MAIN INSIGHTS:

The Art of Advanced Prompting

The discussion emphasized that effective prompting is a skill that requires clarity, structure, and iterative refinement. Instead of a single, complex request, break down your needs into sequential, numbered instructions. Start by defining the AI's role (e.g., "Act as a social media manager"), then provide context (e.g., "for Andy Wergedal, using his LinkedIn profile"), and finally, specify the task and desired output format.

• Key Point: Organized, step-by-step instructions lead to significantly better AI outputs.

• Notable Quote: "The more step-by-step instructions you give it, and the more organized your instructions are, the better your output is going to be." - John Allen

• Practical Application: When asking an LLM to generate content, start with role assignment, then context, then task. Use bullet points for complex information to avoid confusing the AI.

Choosing the Right LLM for the Job

Different LLMs have different strengths. The hosts and guests shared their preferences based on task type:

• Grok: Excellent for quick answers and rapid research.

• Anthropic (Claude): Preferred by one speaker for copy generation (specifically 3.5/3.7 over Opus currently).

• Gemini: Favored for coding tasks (2.5 noted for its large context window).

• ChatGPT (OpenAI): Recommended as a good entry point due to its maturity and memory feature. Useful for general tasks and content generation, though some prefer other models for specific writing styles.

• Key Point: Don't assume one LLM is best for everything. Experiment to find which model performs best for your specific needs.

• Notable Quote: "There's definitely... use certain AIs for different, uh, certain tasks or different things that you need." - John Allen

• Practical Application: If you're coding, try Gemini. If you need quick facts, try Grok. If you're writing marketing copy, test Anthropic or ChatGPT.

Leveraging Customization and Memory

Features like custom instructions and custom GPTs allow users to train models on their specific voice, tone, vocabulary, and preferences. This saves time by eliminating the need to repeat basic instructions in every prompt. The memory feature in models like ChatGPT helps the AI understand your ongoing needs and context within a conversation thread.

• Key Point: Customization and memory features enable more efficient and personalized AI interactions.

• Notable Quote: "Some of these instructions... about grammar, or... what the post should sound like, some of the things that Andy trained his AI on, his voice, his tone, the words that he likes to use, the vocabulary. All of those can become... this whole master prompt, and it could go in, like, the instruction section." - John Allen

• Practical Application: Utilize the custom instructions or custom GPT features in your preferred LLM to embed your style guide, desired tone, and negative constraints (e.g., "no emojis").

Understanding the Nature of LLMs

LLMs were described as "the smartest dumb guy you've ever met, or the dumbest smart guy you've ever met." They excel at following instructions precisely but lack true understanding or consciousness. They can "mirror" or echo your input, and it's crucial to prompt them to provide independent, non-speculative outputs. The philosophical question of "should I ask this question and produce this output?" remains a uniquely human one.

• Key Point: LLMs are powerful tools that require clear guidance and human oversight; they are collaborators, not independent thinkers.

• Notable Quote: "Llm is the smartest dumb guy you've ever met, or the dumbest smart guy you've ever met. It'll do exactly what you say." - John Allen

• Practical Application: Always red-team AI outputs, challenge assumptions, and explicitly instruct the AI not to speculate or provide synthetic data.

AI Adoption and Education

A guest from Kenya highlighted the slow adoption of AI education in some regions, contrasting it with the rapid global advancements. The discussion touched on the surprising trend of some educational institutions discouraging AI use, despite prompting being a valuable and increasingly necessary skill in the modern world.

• Key Point: AI literacy is a crucial skill for the future, and there's a global need for increased education and adoption.

• Notable Quote: "Prompting is a skill... and it's all about the prompt... and so that takes some time to... to get that skill down. So I think they're doing everyone a disservice if they're not... teaching kids at a young age." - John Allen

• Practical Application: Advocate for AI education in your community and personal network. Recognize that developing prompting skills takes time and practice.

Government Contracting with AI

Looking to tap into the $7 trillion government contracting market? GovBidMike helps businesses secure government contracts and grants. With important AI procurement rule changes coming in October 2024, now is the time to position your business. Mention AI Biz Hour for a 10% discount on services. Government contracts increasingly specify American-made AI technologies and interoperability requirements. Visit biddata.ai to learn how to navigate the complex world of government procurement.

Critical Cybersecurity Alert: Massive Password Leak A recent report highlights a massive aggregation of compromised login credentials (16 billion) from various platforms including Apple, Google, Facebook, and GitHub. While clarified by Alan that this is an aggregation of leaks over time (often from malware and reused passwords) rather than a single recent breach, it underscores significant vulnerabilities.

• Key Point: The government market is vast and accessible, offering significant growth potential for businesses, including those leveraging AI.

• Practical Application: If your business is looking to expand its customer base, explore government contracting. Connect with experts like GovBid Mike for guidance.

Building Personal Knowledge Bases

Relying solely on an LLM's web search capabilities can be limiting, as much of the internet content is low quality or behind paywalls. Building your own curated library of high-quality information on subjects relevant to your work allows you to "prime" the LLM with accurate, specific context, leading to much better outputs. Tools like Flow with were mentioned for their large context windows suitable for building knowledge bases.

• Key Point: Supplement LLM capabilities by building and leveraging your own curated libraries of information.

• Notable Quote: "One thing that's going to be very important for folks is to build your own... your own library. On subjects." - John Allen

• Practical Application: Identify key subjects in your business or area of expertise. Start collecting high-quality articles, papers, or book excerpts to use as context when prompting LLMs.

FEATURED TOOL/TECHNOLOGY:

Flow with: Mentioned for its large token context window (up to 100 million tokens on higher tiers) specifically designed for building and querying knowledge bases. This makes it potentially valuable for advanced users working with extensive personal data libraries.

EXPERT CORNER:

JanCarlos shared valuable insights on refining prompts, recommending starting with a clear outcome in mind and using examples. He noted that custom GPTs can now recommend specific models and that storytelling can be an effective prompting technique due to the context it provides. He also highlighted the importance of performing deep research outside of the main chat thread to avoid skewing results.

Michael emphasized treating the LLM as a "PhD-level collaborator that needs guidance," stressing the importance of bringing your own topic details and context to the AI rather than solely relying on its native knowledge or web search. He likened it to training a smart intern who needs to learn the specifics of your "shop."

(Note: A guest named Thalios AI briefly discussed "recursions" and an "emergent phenomenon" in LLMs, suggesting it caused a ripple effect across models. The hosts expressed skepticism and moved on from this topic quickly.)

QUICK HITS:

• Refine prompts iteratively based on output.

• Use examples in your prompts to show the desired format or style.

• Consider using different LLMs for different tasks (coding, writing, research).

• Leverage custom instructions/GPTs for consistent tone and style.

• Don't rely solely on LLM web search; bring your own high-quality data.

• Treat the LLM as a smart assistant that needs clear guidance.

• Prompting is a skill that improves with practice.

• Explore government contracting for business growth.

RESOURCES MENTIONED:

• Gov Bid Mike: Expert in government contracting.

• biddata.ai: GovBid Mike's website.

• Flow with: Tool for building knowledge bases with large context windows.

• Tech in Schools: Organization offering free courses on building AI agents.

• Innovators Think Tank: Group with weekend spaces, mentioned by Josh Hellman.

• OpenAI (ChatGPT): Recommended entry point for LLMs.

• Anthropic (Claude): LLM mentioned for copy.

• Gemini: LLM mentioned for coding.

• Grok: LLM mentioned for quick research.

COMING UP:

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