AMA Answer: What's the relationship between context engineering and prompt engineering?
22 Mar 2026
In this moment:
Simon Tomes
Rahul Parwal
AI is stateless.
It doesn't know or remember anything about you. The state has to be managed externally.
You share your context with it via "prompts".
For a normal AI chatbot (eg, ChatGPT), you can communicate with it via its messaging text area. Prompts are a good starting point to begin your interactions with AI. You can certainly improve / tailor / fine-tune / optimize / engineer / strategize this discussion via prompt engineering. We also talk more about all that as part of our Prompting for Testers | Ministry of Testing course.
Now, as the AI systems evolve (tools, memory, RAG, system prompts, etc). New failure modes appear. There are risks of the overall context getting "poisoned", "distracted", or "noisy".
If you notice AI syndromes like "Forgetfulness" or "Incorrectness" or "Omitting Information" that you supplied with your "prompts", you are actually getting hit by the "contextual" limits of the AI systems. So, now good prompts alone are not enough; you will have to engineer the "context" too. As a thumb rule, it's good to only carry the context relevant to the task at hand.
Context engineering is about controlling what the model sees, retains, and ignores across interactions.
TL;DR:
It doesn't know or remember anything about you. The state has to be managed externally.
You share your context with it via "prompts".
For a normal AI chatbot (eg, ChatGPT), you can communicate with it via its messaging text area. Prompts are a good starting point to begin your interactions with AI. You can certainly improve / tailor / fine-tune / optimize / engineer / strategize this discussion via prompt engineering. We also talk more about all that as part of our Prompting for Testers | Ministry of Testing course.
Now, as the AI systems evolve (tools, memory, RAG, system prompts, etc). New failure modes appear. There are risks of the overall context getting "poisoned", "distracted", or "noisy".
If you notice AI syndromes like "Forgetfulness" or "Incorrectness" or "Omitting Information" that you supplied with your "prompts", you are actually getting hit by the "contextual" limits of the AI systems. So, now good prompts alone are not enough; you will have to engineer the "context" too. As a thumb rule, it's good to only carry the context relevant to the task at hand.
Context engineering is about controlling what the model sees, retains, and ignores across interactions.
TL;DR:
Prompt engineering = what and how you phrase instructions Context engineering = what information the model has access to
When to use which:
- If the model misunderstands your instruction → fix the prompt (use prompt engineering)
- If the model lacks, ignores, or mixes up information → fix the context (use context engineering)
Rahul Parwal
Test Specialist
Rahul Parwal is a Test Specialist with expertise in testing, automation, and AI in testing. He’s an award-winning tester, and international speaker.
Want to know more, Check out testingtitbits.com
Simon Tomes
This is epic. Thanks for explaining, Rahul. 🤩
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