Jake Dawson outlined a practical step-by-step roadmap for learning AI from scratch in 2025, focusing on real-world business automation.
The discussion covered essential concepts, recommended AI tools (ChatGPT, DeepSeek, GenSpark), and detailed strategies for prompt engineering and workflow automation.
Key emphasis was on mastering tools companies need, building reusable automations, and continuously optimizing AI processes for efficiency.
Attendees are encouraged to stay up to date, document their wins, engage with the community, and treat AI as an evolving business partner.
Action Items
Start immediately – All listeners: Create accounts on ChatGPT, DeepSeek, and GenSpark; organize chats by use case.
Start immediately – All listeners: Begin documenting a prompt library in a Google Sheet (task, prompt, best tool).
Weekly ongoing – All listeners: Schedule time to explore new features/tools and update prompts.
Ongoing – All listeners: Document before/after results to track automation improvements.
As desired – All listeners: Join Jake Dawson's AI community and participate.
Foundational Concepts & Tools Overview
Understand the basics of AI, JSON, APIs, and prompt engineering to avoid common pitfalls when automating business tasks.
Learn the difference between system and user messages and how to control AI creativity using settings like temperature.
Recognize the importance of output formatting instructions for clarity and integration with other tools.
Recommended core AI tools: ChatGPT for general use, DeepSeek for complex/structured work and large context, and GenSpark for building multi-step, no-code automations.
Identifying & Selecting Automation Opportunities
Prioritize automating simple, repetitive tasks that save at least 30 minutes weekly and can be clearly explained in steps.
Evaluate if a task is a good automation candidate using a four-question filter: clear input/output, consistency, simplicity, and time savings.
Examples include email processing, generating reply templates, and repurposing content for multiple channels.
Setting Up AI Workspaces and Building Basic Automations
Use dedicated chats per use case to streamline retrieval and maintain organization.
Create prompt templates and a prompt library to improve efficiency and output quality.
Start with simple automations (e.g., auto-reply systems for FAQs) and document each step for future troubleshooting and scaling.
Understand integration points between tools such as Google Forms, Make.com, ChatGPT, and Gmail.
Advanced Prompting & Workflow Design
Employ advanced prompt engineering techniques like chain-of-thought prompting for analytical tasks.
Use zero-shot and few-shot prompting as needed, saving strong prompts as reusable templates.
Implement quality checkpoints and AI self-checks before final outputs are delivered to clients or stakeholders.
Connecting and Scaling Automations
Use platforms like Make.com, Zapier, or IFTTT to connect multiple tools into multi-step workflows.
Test each integration thoroughly to handle imperfect real-world data and implement error handling.
Combine multiple AI tools in a workflow to leverage their individual strengths (e.g., research, summarization, presentation creation).
Build full automation pipelines for tasks like lead management or content production.
Continuous Improvement and Community Engagement
Regularly update automations, prompts, and workflows to adapt to the fast-changing AI landscape.
Subscribe to high-quality AI newsletters and set aside time for exploration and learning.
Document progress and create a portfolio of before/after snapshots and workflow demos.
Engage with the community for feedback, new ideas, and shared templates to accelerate learning.
Decisions
Focus on practical, in-demand AI skills and business automation — Rationale: Avoid wasted effort on outdated or non-transferable skills; align learning directly with current and future business needs.
Open Questions / Follow-Ups
None explicitly stated; ongoing commitment to learning and updating processes is emphasized.