Context Engineering, Not Prompt Engineering

📰 Medium · Machine Learning

Learn how context engineering can improve AI model performance by analyzing 1.3 billion tokens and 45 AI models, and discover the importance of understanding the context in which AI models operate

advanced Published 14 Apr 2026
Action Steps
  1. Analyze large datasets of AI model interactions to identify patterns and trends
  2. Use tools like TokenPulse to track and visualize AI model performance and token usage
  3. Experiment with different AI models and fine-tune them for specific tasks and contexts
  4. Evaluate the cache hit rate and optimize AI model performance by minimizing recomputation
  5. Apply context engineering principles to improve the accuracy and efficiency of AI models in real-world applications
Who Needs to Know This

Data scientists and AI engineers can benefit from understanding the concept of context engineering and how it can be applied to improve AI model performance, leading to more efficient and effective use of AI models in various applications

Key Insight

💡 Context engineering is crucial for optimizing AI model performance, as it allows for a deeper understanding of the context in which AI models operate and makes them more efficient and effective

Share This
🤖 Context engineering can boost AI model performance! Analyze 1.3B tokens and 45 models to learn how 📊

Key Takeaways

Learn how context engineering can improve AI model performance by analyzing 1.3 billion tokens and 45 AI models, and discover the importance of understanding the context in which AI models operate

Full Article

Title: Context Engineering, Not Prompt Engineering

URL Source: https://medium.com/@sanchaygumber686/context-engineering-not-prompt-engineering-cbb8d9f38543?source=rss------machine_learning-5

Published Time: 2026-04-14T03:10:15Z

Markdown Content:
# Context Engineering, Not Prompt Engineering | by Sanchay Gumber | Apr, 2026 | Medium

[Sitemap](https://medium.com/sitemap/sitemap.xml)

[Open in app](https://play.google.com/store/apps/details?id=com.medium.reader&referrer=utm_source%3DmobileNavBar&source=post_page---top_nav_layout_nav-----------------------------------------)

Sign up

[Sign in](https://medium.com/m/signin?operation=login&redirect=https%3A%2F%2Fmedium.com%2F%40sanchaygumber686%2Fcontext-engineering-not-prompt-engineering-cbb8d9f38543&source=post_page---top_nav_layout_nav-----------------------global_nav------------------)

[](https://medium.com/?source=post_page---top_nav_layout_nav-----------------------------------------)

Get app

[Write](https://medium.com/m/signin?operation=register&redirect=https%3A%2F%2Fmedium.com%2Fnew-story&source=---top_nav_layout_nav-----------------------new_post_topnav------------------)

[Search](https://medium.com/search?source=post_page---top_nav_layout_nav-----------------------------------------)

Sign up

[Sign in](https://medium.com/m/signin?operation=login&redirect=https%3A%2F%2Fmedium.com%2F%40sanchaygumber686%2Fcontext-engineering-not-prompt-engineering-cbb8d9f38543&source=post_page---top_nav_layout_nav-----------------------global_nav------------------)

![Image 1](https://miro.medium.com/v2/resize:fill:32:32/1*dmbNkD5D-u45r44go_cf0g.png)

# Context Engineering, Not Prompt Engineering

[![Image 2: Sanchay Gumber](https://miro.medium.com/v2/resize:fill:32:32/1*BDNGgxWW12sbZuQm1P1mRQ.jpeg)](https://medium.com/@sanchaygumber686?source=post_page---byline--cbb8d9f38543---------------------------------------)

[Sanchay Gumber](https://medium.com/@sanchaygumber686?source=post_page---byline--cbb8d9f38543---------------------------------------)

Follow

9 min read

·

Just now

[](https://medium.com/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2F_%2Fvote%2Fp%2Fcbb8d9f38543&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40sanchaygumber686%2Fcontext-engineering-not-prompt-engineering-cbb8d9f38543&user=Sanchay+Gumber&userId=a12080a85ba2&source=---header_actions--cbb8d9f38543---------------------clap_footer------------------)

[](https://medium.com/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2F_%2Fbookmark%2Fp%2Fcbb8d9f38543&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40sanchaygumber686%2Fcontext-engineering-not-prompt-engineering-cbb8d9f38543&source=---header_actions--cbb8d9f38543---------------------bookmark_footer------------------)

[Listen](https://medium.com/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2Fplans%3Fdimension%3Dpost_audio_button%26postId%3Dcbb8d9f38543&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40sanchaygumber686%2Fcontext-engineering-not-prompt-engineering-cbb8d9f38543&source=---header_actions--cbb8d9f38543---------------------post_audio_button------------------)

Share

## What 45 AI Models and 1.3 Billion Tokens Taught Me

## The Numbers First

Let me show you the scoreboard before I tell you the lesson.

Over the last 14 months, I tracked every AI coding session through Cursor’s token export and built a personal analytics dashboard I called TokenPulse. Here is what the data shows, from Cursor only, verifiable from my own export:

* **1.302 billion tokens** consumed across 9,104 sessions
* **45 distinct AI models** used: Claude, GPT-5, Gemini, o3, Grok, DeepSeek, and more
* **$849.36 total estimated platform cost** ($302.74 paid out of pocket; the rest absorbed by Cursor’s included tier)
* **89.8% cache hit rate**, meaning nearly 9 out of every 10 tokens my sessions read were served from cache, not recomputed fresh

Press enter or click to view image in full size

![Image 3](https://miro.medium.com/v2/resize:fit:700/1*MR24F
Read full article → ← Back to Reads