Ep 848: Context Engineering: How to Get Expert-Level Outputs From AI Chatbots (Start Here Series Vol 7)
Ep 848: Context Engineering: How to Get Expert-Level Outputs From AI Chatbots (Start Here Series Vol 7)
Ep 848: Context Engineering: How to Get Expert-Level Outputs From AI Chatbots (Start Here Series Vol 7)
Shownote
Shownote
How did prompt engineering die so quickly? ☠️
And what the heck does context engineering even mean?
One of the trickiest things about LLMs is they're changing daily, yet they're
the engines that drive business results.
But if the engine is constantly changing, then you also have to change how you
drive and the roads you take.
That's why we're tackling context engineering in this installment of our Start
Here Series, the essential beginners guide to understanding AI basics and
growing your skills.
Context Engineering: How to Get Expert-Level Outputs From AI Chatbots -- An
Everyday AI Chat with Jordan Wilson
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Topics Covered in This Episode:
1. Evolution from Prompt to Context Engineering
2. Why Prompt Engineering Is Now Obsolete
3. Defining Context Engineering in AI Chatbots
4. Six-Part Framework for Context Engineering
5. Four Layer System for Structuring AI Context
6. Building Reusable Context Vaults and Skills
7. Connecting Business Data to AI Models
8. Techniques to Achieve Expert-Level AI Outputs
9. Importance of Context Windows in Large Language Models
10. Context Engineering Best Practices and Scalability
Timestamps:
00:00 "Access AI Community & Tools"
03:08 "Mastering Context in AI"
07:23 "Smart Models Require Less Precision"
12:01 "Context Engineering Beats Prompt Engineering"
15:49 "AI Context: Six Key Blocks"
16:47 "Building Context for Better Results"
19:53 "AI: Training, Not Easy Button"
25:17 "Chain of Thought Prompting Decline"
29:11 "Show, Don't Tell Techniques"
32:13 "Context, Reuse, and Scalable Systems"
33:19 "AI Chatbots: Memory and Skills"
Keywords:
context engineering, AI chatbots, expert level outputs, prompt engineering,
large language models, business context, AI models, custom instructions, data
access, context window, prime prompt polish, reusable context vaults, context
vaults, skills file, memory enabled models, ChatGPT, Claude, Google Gemini,
Microsoft Copilot, connectors, apps, searchable index, business data,
personalized AI, context clues, reference material, examples, procedures,
evaluation rubric, chain of thought prompting, generative AI, nondeterministic
behavior, show don’t tell technique, few shot examples, rubric first technique,
grading criteria, output quality, scalable AI systems,
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Highlights
Highlights
This episode explains how effective AI use is moving beyond carefully phrased prompts toward deliberately designed context. It presents a practical way to help AI produce more reliable, expert-level work by giving it the right information, structure, and standards.
Chapters
Chapters
Access AI Community & Tools
00:00Mastering Context in AI
03:08Smart Models Require Less Precision
07:23Context Engineering Beats Prompt Engineering
12:01AI Context: Six Key Blocks
15:49Building Context for Better Results
16:47AI: Training, Not Easy Button
19:53Chain of Thought Prompting Decline
25:17Show, Don't Tell Techniques
29:11Context, Reuse, and Scalable Systems
32:13AI Chatbots: Memory and Skills
33:19Transcript
Transcript
Jordan Wilson: Welcome to the Everyday AI Podcast. My name is Jordan Wilson and for the past three and a half years, we've put out more than 800 episodes. Yet, one of the most common questions I get, I didn't really have an answer for. Where do I start on ...

