Navigating the Complexities of AI-Prompt Management: Insights from SIKE

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In the rapidly evolving world of AI-driven tools, understanding the mechanics behind AI interactions, particularly in custom models, is crucial for businesses aiming to leverage these technologies effectively. A recent video on YouTube (see below) delves into the complexities and challenges faced by users of popular AI platforms like ChatGPT, specifically addressing the issue of prompt management and its impact on AI output quality.

The Problem: Layered Prompts in AI Platforms

The video highlights a key issue in many AI platforms: the layering of pre-prompts or system prompts that can dilute or misdirect the user’s original query. This issue often leads to suboptimal outputs, requiring users to continuously regenerate responses or adjust their prompts to achieve the desired results. In platforms like ChatGPT, where multiple layers of prompts precede the user’s input, the AI model may struggle to prioritize and effectively respond to the actual query. Here’s an image showing the pre-instructions that sit on top of your queries depending on whether you’re using ChatGPT to browse, create images or do other functions.

NotCentralised Chat GPT Instructions

It’s all useful to help guide behaviour and absolutely necessary in some cases, but the issue for user shows itself when users don’t get the results they want from the prompts or need to keep reworking it to get it right.

The video from WestGPT above highlights how accessing OpenAI Playground could be useful and for some users it can be, but for others, they’ll need a tool that gives them those options and that’s where SIKE steps in.

SIKE’s Approach: Streamlined and User-Centric

At SIKE, we’ve acknowledged these challenges and have developed a system that not only addresses them but also enhances the overall user experience. Here’s how SIKE stands out:

Persona-Based Prompt Structure

We utilise ‘personas’ in SIKE to provide structured guidance to AI outputs. Each persona comes with specific pre-prompts that are crafted to direct the AI in generating a certain type or style of response. This structured system ensures that the output is consistent and relevant, aligning with the user’s expectations.

NotCentralised Sike Personas
Direct API Integration

Unlike platforms with layers of system prompts that can act as ‘bloatware’, SIKE operates directly on top of OpenAIs API. This approach eliminates unnecessary intermediaries, ensuring a streamlined and efficient process, free from external prompt-related complexities.

Raw Persona for Unfiltered Responses

Unlike platforms with layers of system prompts that can act as ‘bloatware’, SIKE operates directly on top of OpenAIs API. This approach eliminates unnecessary intermediaries, ensuring a streamlined and efficient process, free from external prompt-related complexities.

Focused Document-Specific Guidance

Some personas like “Documents” in SIKE are tailored to respond based on information from specific documents, enabling business users to get answers grounded in particular datasets or document collections. This focused approach is especially beneficial for industries that rely on precise and document-specific information.

Prompt Assembler: A Game-Changer

Our innovative Prompt Assembler feature allows users to efficiently compile and edit segments from conversation threads or AI outputs into new prompts. This tool revolutionises the workflow of using AI tools, particularly for business users, by saving time and offering greater control over AI interactions.

Conclusion: Empowering Businesses with SIKE

The insights from the video underscore the need for a more refined and user-friendly approach to AI prompt management. SIKE’s methodologies and features are designed to meet these needs, offering businesses a sophisticated, flexible, and efficient way to harness AI for their specific requirements. By prioritising user input and minimising complexities, SIKE stands as a beacon of innovation in the AI landscape, paving the way for more effective and seamless AI-driven business solutions.

If you want to try it out for your business, get in touch with us on email here or check out more details on SIKE.

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Mark drives innovation with his deep understanding of AI, blockchain, and data technologies. His experience spans over 15 years of contributions to finance, technology, and operational strategy across Australia, Europe, and North America.

In 2021, he transitioned from Head of Data and Technology at a leading Australian accounting firm to startups. Prior to this, he worked in equity and macroeconomic research in the capital markets space.

Mark brings a passion for data and insights to NotCentralised. His understanding of AI and blockchain technology is central to the development of workplace productivity and financial system modernisation products, including SIKE and Layer-C. Mark’s dynamic and solutions-focused methods enable the navigation of complex technological landscapes and new market potentials.

Mark holds an Executive Master’s and a Bachelor of Commerce. He led the creation of the Australian DeFi Association and serves on the advisory board for the Data Science and AI Association of Australia. His commitment to such communities demonstrates his enthusiasm for emerging technologies and vision of positive change through technology adoption.


Nick spearheads product strategy and institutional business development, leveraging a rich background spanning 23 years in capital markets and financial services across the UK, the US, and APAC.

In 2020, Nick transitioned into startups, bringing extensive experience in asset management and corporate advisory from roles including Director, Head of Australian Fixed Income at Abrdn and Managing Director, Head of Corporate Credit at Gresham Partners. His expertise extends to client management across the government and private sectors.

With a First Class degree in Law and Criminology and Chartered Financial Analyst experience since 2002, Nick is known for his energetic and creative approach, quickly appraising business models and identifying market opportunities.

Beyond his role at NotCentralised, Nick actively contributes to multiple startups and SMEs, holding various Board and advisory positions and applying his institutional expertise to early-stage ventures. Nick is fascinated by emerging technologies with significant societal impact and loves to immerse himself in nature.


Arturo leads product development and software engineering, applying over two decades of experience in technology, capital markets, and data science. With his years of programming expertise, Arturo smoothly transitioned into blockchain, AI, and machine learning.

Arturo has built and sold technology startups across Europe, following quant derivatives roles in global investment banks. His prior experience includes data projects for the NHS in the UK, Strategic Technology Advisor at Land Insight, and Senior Advisor to OpenInsight, where he built predictive models for vessel usage in commodity markets.

A mathematics and statistics graduate from Stockholm University, Arturo’s early grounding in logic problems and data manipulation techniques is evident in his practical applications. His work building equity derivative pricing models for Merrill Lynch and Royal Bank of Scotland showcased Arturo’s highly specialised skillset.

Arturo relocated from London to Australia in 2020. Beyond NotCentralised, his passion for technology and industry involvement extends to the Australian DeFi Association, which he co-founded, and regular contributions to the Data Science and AI Association.