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Unlocking the Next Frontier of AI: How Agentic Generative AI Empowers Michigan’s Entrepreneurs

First and foremost, I want to extend a heartfelt thank you to everyone who attended our recent presentation, “๐— ๐—ผ๐˜ƒ๐—ถ๐—ป๐—ด ๐—•๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ ๐—–๐—ผ๐—ฝ๐—ถ๐—น๐—ผ๐˜ ๐—ฎ๐—ป๐—ฑ ๐—–๐—ต๐—ฎ๐˜๐—š๐—ฃ๐—ง: ๐—š๐—ฒ๐˜ ๐— ๐—ผ๐—ฟ๐—ฒ ๐—ฉ๐—ฎ๐—น๐˜‚๐—ฒ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—”๐—œ ๐˜„๐—ถ๐˜๐—ต ๐—–๐˜‚๐˜€๐˜๐—ผ๐—บ ๐—”๐—œ ๐—ฃ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—ง๐—ฒ๐—ฎ๐—บ๐˜€ ๐—ผ๐—ณ ๐—”๐—œ ๐—”๐—ด๐—ฒ๐—ป๐˜๐˜€,” hosted by Startup Nation in Birmingham, MI. It was an honor to share the stage with R.J. King, Editor of DBusiness Magazine, and esteemed guest speakers Hilary Doe, Chief Growth Officer for the State of Michigan, and entrepreneur Hajj Flemings.

The event that took place was a vibrant discussion about the future of AI and its transformative potential for businesses in Michigan. Hajj Flemings highlighted a particularly inspiring vision: enabling smaller businesses to compete on a global scale, empowering entrepreneurs to create billion-dollar companies with only a small team. This aligns perfectly with our mission at Proactive Technology Management to democratize access to advanced AI capabilities.

For those who couldn’t make it, I’d like to share some key takeaways from our presentation and explore how ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—”๐—œ is set to revolutionize the way we do business, especially for solopreneurs and startups.

๐—ง๐—ต๐—ฒ ๐—–๐—ต๐—ฎ๐—ป๐—ด๐—ถ๐—ป๐—ด ๐—”๐—œ ๐—Ÿ๐—ฎ๐—ป๐—ฑ๐˜€๐—ฐ๐—ฎ๐—ฝ๐—ฒ: ๐—•๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ ๐—•๐—ฎ๐˜€๐—ถ๐—ฐ ๐—–๐—ต๐—ฎ๐˜๐—ฏ๐—ผ๐˜๐˜€

The advent of tools like ๐—–๐—ต๐—ฎ๐˜๐—š๐—ฃ๐—ง and ๐—–๐—ผ๐—ฝ๐—ถ๐—น๐—ผ๐˜ has undoubtedly kickstarted a generative AI revolution. However, as enterprises grapple with data privacy concerns, output quality control, and high operational costs, it’s clear that we need to move beyond basic chatbots.

Businesses don’t wantโ€”and shouldn’t needโ€”to turn their employees into prompt engineers. That’s not the most effective use of their time or talents. As Satya Nadella, CEO of Microsoft, aptly put it:

“๐˜ˆ๐˜ด ๐˜ˆ๐˜ ๐˜ด๐˜บ๐˜ด๐˜ต๐˜ฆ๐˜ฎ๐˜ด ๐˜ญ๐˜ช๐˜ฌ๐˜ฆ ๐˜ต๐˜ฉ๐˜ฆ๐˜ด๐˜ฆ ๐˜ฃ๐˜ฆ๐˜ค๐˜ฐ๐˜ฎ๐˜ฆ ๐˜ช๐˜ฏ๐˜ค๐˜ณ๐˜ฆ๐˜ข๐˜ด๐˜ช๐˜ฏ๐˜จ๐˜ญ๐˜บ ๐˜ค๐˜ข๐˜ฑ๐˜ข๐˜ฃ๐˜ญ๐˜ฆ, ๐˜ฎ๐˜ฐ๐˜ฅ๐˜ฆ๐˜ญ๐˜ด ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ๐˜ด๐˜ฆ๐˜ญ๐˜ท๐˜ฆ๐˜ด ๐˜ฃ๐˜ฆ๐˜ค๐˜ฐ๐˜ฎ๐˜ฆ ๐˜ฎ๐˜ฐ๐˜ณ๐˜ฆ ๐˜ฐ๐˜ง ๐˜ข ๐˜ค๐˜ฐ๐˜ฎ๐˜ฎ๐˜ฐ๐˜ฅ๐˜ช๐˜ต๐˜บ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ข๐˜ญ๐˜ญ ๐˜ท๐˜ข๐˜ญ๐˜ถ๐˜ฆ ๐˜จ๐˜ฆ๐˜ต๐˜ด ๐˜ค๐˜ณ๐˜ฆ๐˜ข๐˜ต๐˜ฆ๐˜ฅ ๐˜ฃ๐˜บ ๐˜ฉ๐˜ฐ๐˜ธ ๐˜บ๐˜ฐ๐˜ถ ๐˜จ๐˜ณ๐˜ฐ๐˜ถ๐˜ฏ๐˜ฅ, ๐˜ด๐˜ต๐˜ฆ๐˜ฆ๐˜ณ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ง๐˜ช๐˜ฏ๐˜ฆ-๐˜ต๐˜ถ๐˜ฏ๐˜ฆ ๐˜ต๐˜ฉ๐˜ฆ๐˜ด๐˜ฆ ๐˜ฎ๐˜ฐ๐˜ฅ๐˜ฆ๐˜ญ๐˜ด ๐˜ธ๐˜ช๐˜ต๐˜ฉ ๐˜บ๐˜ฐ๐˜ถ๐˜ณ ๐˜ฃ๐˜ถ๐˜ด๐˜ช๐˜ฏ๐˜ฆ๐˜ด๐˜ด ๐˜ฅ๐˜ข๐˜ต๐˜ข ๐˜ข๐˜ฏ๐˜ฅ ๐˜ธ๐˜ฐ๐˜ณ๐˜ฌ๐˜ง๐˜ญ๐˜ฐ๐˜ธ.”

This sentiment captures the essence of our approach: leveraging AI in a way that is deeply integrated with your specific business needs.

๐—˜๐—บ๐—ฝ๐—ผ๐˜„๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—ง๐—ต๐—ฟ๐—ผ๐˜‚๐—ด๐—ต ๐—”๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—š๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—”๐—œ

So, how do we get more value from AI? The answer lies in ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—”๐—œโ€”teams of AI agents working together semi-autonomously to accomplish specific business workflows and subtasks. This approach empowers and democratizes access to business-relevant skills and capabilities, creating a wealth of opportunities for solopreneurs and startups in Michigan.

Imagine being able to delegate tasks to AI agents just as you would to a capable employee. Every entrepreneur who has hired staff already knows how to do this. The metaphor of prompt engineering as delegation makes AI more accessible and less intimidating. You’re not wrestling with complex prompts; you’re giving clear instructions to specialized agents.

๐—”๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—”๐—œ ๐˜€๐˜†๐˜€๐˜๐—ฒ๐—บ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ผ๐˜‚๐—ป๐—ฑ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜ ๐—ฝ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€ enable the best-engineered prompts to be captured and reused repeatedly. This not only increases efficiency but also ๐—ฟ๐—ฒ๐—น๐—ถ๐—ฒ๐˜ƒ๐—ฒ๐˜€ ๐—ฒ๐—บ๐—ฝ๐—น๐—ผ๐˜†๐—ฒ๐—ฒ๐˜€ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ฏ๐˜‚๐—ฟ๐—ฑ๐—ฒ๐—ป ๐—ผ๐—ณ ๐—ฏ๐—ฒ๐—ฐ๐—ผ๐—บ๐—ถ๐—ป๐—ด ๐—ฝ๐—ฟ๐—ผ๐—บ๐—ฝ๐˜ ๐—ฒ๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—”๐—œ ๐—ฒ๐˜…๐—ฝ๐—ฒ๐—ฟ๐˜๐˜€ ๐˜๐—ต๐—ฒ๐—บ๐˜€๐—ฒ๐—น๐˜ƒ๐—ฒ๐˜€.

๐—ง๐—ต๐—ฒ ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ผ๐—ณ ๐——๐—ถ๐˜ƒ๐—ถ๐˜€๐—ถ๐—ผ๐—ป ๐—ผ๐—ณ ๐—Ÿ๐—ฎ๐—ฏ๐—ผ๐—ฟ: ๐—–๐—ผ๐—บ๐—ฝ๐—ผ๐˜‚๐—ป๐—ฑ ๐—”๐—ด๐—ฒ๐—ป๐˜ ๐—ฃ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€

๐——๐—ถ๐˜ƒ๐—ถ๐˜€๐—ถ๐—ผ๐—ป ๐—ผ๐—ณ ๐—น๐—ฎ๐—ฏ๐—ผ๐—ฟ isn’t just a principle for human teams; it applies to AI as well. The most effective use of AI involves pipelines and coordinated teams of specialized agents, each hyper-focused on individual business-relevant tasks. Each agent has its own custom-tailored knowledge base and access to external tools, making them highly efficient at what they do.

By creating ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ผ๐˜‚๐—ป๐—ฑ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜ ๐—ฝ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€, we harness the power of specialization. These pipelines allow agents to pass information through a controlled system, validating results at every step. This approach leverages each agent’s specialized skills, creating an end-to-end solution for even the most complex business processes.

๐—˜๐—ป๐˜€๐˜‚๐—ฟ๐—ถ๐—ป๐—ด ๐—ค๐˜‚๐—ฎ๐—น๐—ถ๐˜๐˜† ๐˜„๐—ถ๐˜๐—ต ๐—”๐—ด๐—ฒ๐—ป๐˜-๐—˜๐˜ƒ๐—ฎ๐—น๐˜‚๐—ฎ๐˜๐—ผ๐—ฟ ๐—ฃ๐—ฎ๐—ถ๐—ฟ๐˜€

One of the challenges with AI-generated content is ensuring its accuracy and reliability. This is where the important role of ๐—ฎ๐—ด๐—ฒ๐—ป๐˜-๐—ฒ๐˜ƒ๐—ฎ๐—น๐˜‚๐—ฎ๐˜๐—ผ๐—ฟ ๐—ฝ๐—ฎ๐—ถ๐—ฟ๐˜€ comes into play in compound agentic AI architectures.

By pairing an agent with an evaluator, we cut down on hallucinations and apply a quality ratchet to agent outputs. Incorporating ๐—ฟ๐—ฒ๐—ถ๐—ป๐—ณ๐—ผ๐—ฟ๐—ฐ๐—ฒ๐—บ๐—ฒ๐—ป๐˜ ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐˜„๐—ถ๐˜๐—ต ๐—ต๐˜‚๐—บ๐—ฎ๐—ป ๐—ณ๐—ฒ๐—ฒ๐—ฑ๐—ฏ๐—ฎ๐—ฐ๐—ธ, low-quality responses are rejected and revised. High-quality responses and human-corrected responses are added to memory, improving future outputs.

This continuous improvement loop ensures that the AI becomes more accurate and aligned with your business objectives over time.

๐—›๐—ฎ๐—ป๐—ฑ๐˜€-๐—ข๐—ป ๐—˜๐˜…๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐˜๐—ถ๐—ผ๐—ป: ๐—ง๐—ฒ๐˜€๐˜๐—ถ๐—ป๐—ด ๐—ฃ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€ ๐—ฌ๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐—น๐—ณ

Business owners and executives don’t have to take our word for it; you can ๐—ฒ๐˜…๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—บ๐—ฒ๐—ป๐˜ ๐˜„๐—ถ๐˜๐—ต ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—”๐—œ ๐—ฝ๐—ถ๐—ฝ๐—ฒ๐—น๐—ถ๐—ป๐—ฒ๐˜€ yourself. Start by sketching out the pipeline on paper. Identify the tasks you want to automate and the specialized agents required for each subtask.

You can implement each sub-agent as a custom prompt in its own ChatGPT window. By shuttling the outputs between windows, you can test out the pipeline approach. Apply your own evaluation to each sub-agent’s output before passing it on. This hands-on experimentation can provide valuable insights into how agentic AI can be integrated into your business processes.

๐—ฅ๐—ฒ๐—ฎ๐—น-๐—ช๐—ผ๐—ฟ๐—น๐—ฑ ๐—”๐—ฝ๐—ฝ๐—น๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€: ๐—™๐—ฟ๐—ผ๐—บ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜ ๐˜๐—ผ ๐—˜๐˜…๐—ฒ๐—ฐ๐˜‚๐˜๐—ถ๐—ผ๐—ป

During our presentation, we showcased how businesses can deploy ๐—ฐ๐˜‚๐˜€๐˜๐—ผ๐—บ ๐—”๐—œ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€ that specialize in specific tasks, each grounded in the company’s internal data and processes. These agents don’t just answer queriesโ€”they collaborate within predefined workflows to deliver highly accurate results tailored to your business needs.

We demonstrated multi-agent systems managing everything from customer service interactions to data extraction from unstructured documents, all while ensuring compliance and security within enterprise environments.

๐—ฆ๐—ฐ๐—ฎ๐—น๐—ถ๐—ป๐—ด ๐—จ๐—ฝ: ๐—˜๐—ป๐˜๐—ฒ๐—ฟ๐—ฝ๐—ฟ๐—ถ๐˜€๐—ฒ-๐—š๐—ฟ๐—ฎ๐—ฑ๐—ฒ ๐—”๐—œ ๐—œ๐—ป๐˜๐—ฒ๐—ด๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป

For larger organizations, integrating compound agentic AI systems with enterprise-grade CRMs like ๐— ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ผ๐—ณ๐˜ ๐——๐˜†๐—ป๐—ฎ๐—บ๐—ถ๐—ฐ๐˜€, ๐—ฆ๐—ฎ๐—น๐—ฒ๐˜€๐—ณ๐—ผ๐—ฟ๐—ฐ๐—ฒ, or ๐—›๐˜‚๐—ฏ๐—ฆ๐—ฝ๐—ผ๐˜ is a game-changer. We discussed two architectural approaches:

1. ๐—™๐—ฟ๐—ฒ๐—ฒ๐˜€๐˜๐—ฎ๐—ป๐—ฑ๐—ถ๐—ป๐—ด “๐—ช๐—ผ๐—ฟ๐—ธ ๐—ค๐˜‚๐—ฒ๐˜‚๐—ฒ” ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ณ๐—ฎ๐—ฐ๐—ฒ: This involves a separate interface that preprocesses raw or unstructured data. AI extracts structured data and relevant action items, which are then reviewed by humans before being inserted into the CRM. This allows for human oversight while automating data processing.

2. ๐—˜๐˜ƒ๐—ฒ๐—ป๐˜-๐——๐—ฟ๐—ถ๐˜ƒ๐—ฒ๐—ป ๐—œ๐—ป๐˜๐—ฒ๐—ด๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป: In this approach, the AI acts on records in the CRM as they are created or modified. AI-generated recommendations update the CRM’s status fields, and humans review and approve the content, ensuring control while largely automating tasks and business processes within the CRM system.

๐—ง๐—ต๐—ฒ ๐—™๐˜‚๐˜๐˜‚๐—ฟ๐—ฒ ๐—ผ๐—ณ ๐—”๐—œ: ๐—”๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—•๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ

The next phase in AI’s evolution is ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—”๐—œ, where agents not only respond to prompts but also make autonomous decisions, orchestrating multiple agents for tasks like long-term strategic planning. While this future is exciting, it requires careful planning to ensure systems remain aligned with business objectives.

๐—–๐—ผ๐—บ๐—ฝ๐—ผ๐˜‚๐—ป๐—ฑ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜ ๐—ผ๐—ฟ๐—ฐ๐—ต๐—ฒ๐˜€๐˜๐—ฟ๐—ฎ๐˜๐—ฒ๐—ฑ ๐˜๐—ฒ๐—ฎ๐—บ๐˜€ and architectures like the “๐—ง๐—ฟ๐—ฒ๐—ฒ ๐—ผ๐—ณ ๐—ง๐—ต๐—ผ๐˜‚๐—ด๐—ต๐˜” allow AI to think through problems step by step, effectively brainstorming with themselves. This level of complexity can be appropriate for certain research use cases and goal-oriented brainstorming but may not be necessary for all business processes.

๐—™๐—ถ๐—ป๐—ฎ๐—น ๐—ง๐—ต๐—ผ๐˜‚๐—ด๐—ต๐˜๐˜€

We were thrilled by the engagement and the insightful questions that led to a lively discussion afterward. The enthusiasm in the room confirmed what we believe: ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—ด๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—”๐—œ ๐—ต๐—ผ๐—น๐—ฑ๐˜€ ๐—ถ๐—บ๐—บ๐—ฒ๐—ป๐˜€๐—ฒ ๐—ฝ๐—ผ๐˜๐—ฒ๐—ป๐˜๐—ถ๐—ฎ๐—น ๐—ณ๐—ผ๐—ฟ ๐—ฏ๐˜‚๐˜€๐—ถ๐—ป๐—ฒ๐˜€๐˜€๐—ฒ๐˜€ ๐—ผ๐—ณ ๐—ฎ๐—น๐—น ๐˜€๐—ถ๐˜‡๐—ฒ๐˜€, particularly solopreneurs and startups looking to level the playing field.

For those who couldn’t attend or who missed the QR code during our talk, you can access the full presentation slides here:

๐Ÿ”— https://www.beautiful.ai/player/-O7jj3_BXAKujuNeF4D5/1

Once again, thank you for your continued support. Our Fusion Development Team looks forward to helping you unlock the full potential of AI in your business. If you have any further questions or would like to discuss how we can assist in your AI journey, please don’t hesitate to reach out by scheduling a free consultation using the link below.

๐Ÿ”— https://calendly.com/mweinberger-proactive