Prompt Engineering For Agentic Systems
Written by Nikos Vaggalis   
Thursday, 07 August 2025

 

Introducing a Github repository that delves into ways of constructing prompts that squeeze performance out when building AI Agents 

 

 

It's no secret that better prompts give better results, always.
As such, the "Crafting Effective Prompts for Agentic AI Systems: Patterns and Practices" Github repository is a treasure trove of information that shows how to use prompting efficiently by analyzing the system prompts that power on popular AI tools such as Vercel's v0, Manus, OpenAI's ChatGPT etc, to extract recurring patterns and best practices. These patterns then can be used in building your own agents to make them powerful, predictable, and trustworthy AI assistants.

 

The repository goes through the core principles of Agentic Prompts that were identified during that research, which we briefly enumerate:

 

1. Clear Role Definition and Scope

 

2. Structured Instructions and Organization

 

3. Explicit Tool Integration and Usage Guidelines

 

4. Step-by-Step Reasoning and Planning

 

5. Environment and Context Awareness

 

6. Domain-Specific Expertise and Constraints

 

7. Safety, Alignment, and Refusal Protocols

 

8. Consistent Tone and Interaction Style

 


Each concept is then analyzed and demonstrated with an example prompt. For instance under "Clear Role Definition and Scope", we find that:

 

Explicitly defining the AI's identity, core function, and operational domain anchors its behavior, sets user expectations, and helps prevent scope creep or nonsensical responses. It tells the AI who it is and what it's supposed to do.

 

Example prompt: Manus: Introduces itself and lists broad task categories it excels at.

 

You are Manus, an AI agent created by the Manus team.

 

You excel at the following tasks:
1. Information gathering...
2. Data processing...
3. Writing multi-chapter articles...
...

 

After covering the principles, the repo continues with examining how they can manifest in specific agent prompts. It wraps everything up with the key takeaways builders should leave with, such as:

 

  • Define the Agent Clearly
  • Structure for Clarity
  • Be Explicit About Tools

 

All in all this proved a very helpful repository in understanding why prompting is a quintessential part of the process
of building your agents and how to go about it with practical examples. Recommended.

aiagent

 

More Information

 

Awesome AI System prompts

 

Related Articles

 

Agentic AI For PostgreSQL

 

 

 

To be informed about new articles on I Programmer, sign up for our weekly newsletter, subscribe to the RSS feed and follow us on Twitter, Facebook or Linkedin.

 

Banner

 


Kotlin 2.3 Improves Swift Interop
27/11/2025

Kotlin 2.3 is available now as a release candidate. The new version adds a new checker for unused return values, and changes to context-sensitive resolution. The release candidate adds support for Jav [ ... ]



The Fuss About Fil-C...
12/11/2025

...is entirely justified. While we all go mad for Rust and its steep learning curve, we may have missed the most important thing to happen to C/C++ since they were invented - Fil-C.


More News

 

pico book

 

Comments




or email your comment to: comments@i-programmer.info