This is the Everyday AI episode we probably shoulda done a while ago.... 👇
Because as different as ChatGPT, Gemini, Claude and others actually are under the hood, they have really started to copycat each other over the past 6 months.
Which means we finally have a set of concrete best practices to get the best outputs from any LLM.
Join us as we boil thousands of hours of experience into a 30-ish minute crash course that you can't afford to skip out on.
2026 LLM Cheat Code: 10 Essential Steps To Get the Most out of Any AI Chatbot -- An Everyday AI Chat with Jordan Wilson (Start Here Series Vol 26)
Newsletter: Sign up for our free daily newsletter
More on this Episode: Episode Page
Today's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.
Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show:
[email protected]Connect with Jordan on LinkedIn
Topics Covered in This Episode:
LLM Landscape: Cookie Cutter Model Trends
10 Essential Steps for AI Chatbots
Choosing the Right AI Operating System
Selecting Optimal AI Chatbot Surfaces
Importance of Paid AI Chatbot Plans
Understanding LLM Context Window Layers
Context Engineering and Prompt Best Practices
Integrating Files, Apps, and Company Data
AI Chatbot Privacy, Permissions, Governance
Transparency, Observability, and Reasoning Artifacts
Verification, Iteration, and Workflow Automation
Timestamps:
00:00 Keeping up with AI changes
03:55 Introduction to AI chatbots essentials
09:05 Rapid innovation in AI models
13:01 Understanding early AI models
14:37 Choosing an AI operating system
17:08 Discussing desktop app benefits
21:14 Understanding the context layer
23:55 Challenges without web search integration
28:55 Advancements in CRM connectors
32:35 Challenges with AI governance
35:13 Importance of observability in workflows
37:36 Developing universal AI skills
Keywords:
large language model, LLM, AI chatbot, AI operating system, ChatGPT, Claude, Gemini, Copilot, Perplexity, Grok, open models, cheat code for LLM, AI best practices, prompt engineering, context engineering, context window, context layer, reasoning models, generative AI, deterministic vs generative, web search in AI, model selection, paid AI model, free AI model risks, AI surface, desktop AI app, agentic capabilities, AI connectors, app integrations, business data privacy, permissions and governance, shadow IT, enterprise AI, observability, transparency, reasoning artifacts, workflow automation, verification loop, iteration in AI outputs, skill creation, plugin, automated workflow, agentic orchestration, company data security, expert driven loop, AI scheduling, context carry, modular AI, AI-powered work automation, personalized context, role-based access control, SaaS application integration, economic value of AI, knowledge work automation, prime prompt polish, refine queue, five five five framework, human-in-the-loop AI, knowledge cutoff, model versioning.
Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)
Start Here ▶️
Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com
Also, here's a link to the entire series on a Spotify playlist.