You will get better AI prompt results with less mistakes and missing information
Project details
AI often produces confident outputs that are incomplete, inconsistent, or subtly wrong. In most cases, the issue is not the model—it is the prompt structure.
In this project, I redesign your prompt to reduce error risk by design, not by trial and error. I focus on preventing skipped steps, unchecked assumptions, and guessing by introducing clear structure, constraints, and self-checks directly into the prompt.
My background is in software engineering and AI systems design. I am the creator of the S-File, a structured format for guided AI sessions used to produce more reliable, repeatable AI behavior across tools like ChatGPT, Copilot, and Claude. This work applies the same systems thinking—clarity, explicit rules, and validation—to a single prompt.
You receive a cleaner, more controlled prompt, with built-in error-reduction rules and a short usage guide. This is not prompt “polishing.” It is prompt design aimed at reliability.
In this project, I redesign your prompt to reduce error risk by design, not by trial and error. I focus on preventing skipped steps, unchecked assumptions, and guessing by introducing clear structure, constraints, and self-checks directly into the prompt.
My background is in software engineering and AI systems design. I am the creator of the S-File, a structured format for guided AI sessions used to produce more reliable, repeatable AI behavior across tools like ChatGPT, Copilot, and Claude. This work applies the same systems thinking—clarity, explicit rules, and validation—to a single prompt.
You receive a cleaner, more controlled prompt, with built-in error-reduction rules and a short usage guide. This is not prompt “polishing.” It is prompt design aimed at reliability.
AI Algorithms
Large Language ModelAI Applications
AI Chatbot, Conversational AIAI Models
ChatGPTWhat's included
| Service Tiers |
Starter
$79
|
Standard
$139
|
Advanced
$189
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 4 days |
Number of Revisions | 2 | 4 | 6 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
About Novi
AI Interactions Designer | Software Engineer
London, United Kingdom - 7:04 am local time
My current specialization is AI systems design: structuring AI interactions so they behave reliably, consistently, and usefully in real work, not just demos or experiments. I approach AI as a system to be engineered, not a collection of clever prompts.
I am the creator of the S-File, a structured format for guided AI sessions that applies software engineering principles—explicit inputs, clear constraints, validation steps, and repeatable execution—to AI interactions. The goal is to turn AI from a “chatty tool” into a dependable component of professional workflows.
Before focusing on AI systems, I spent more than a decade as a full-stack web developer, primarily working with PHP and JavaScript. I have designed and maintained production systems with long lifespans, real users, and real operational constraints.
My background includes the following areas of work:
- Custom web applications using PHP and Laravel
- WordPress and Moodle platforms
- API design and third-party integrations
- Linux and cloud-hosted environments
- Performance, security, and maintainability of live systems
In parallel, I have significant experience in software and data integration, particularly in environments where systems must stay in sync over time.
This includes work with:
- CRM and nonprofit platforms such as Blackbaud CRM
- Data synchronization tools such as Brightvine Data Link
- Automation and iPaaS tools including Zapier and Power Automate
- Custom API-based integrations between web applications and external systems
This integration experience strongly informs how I design both AI and web systems. I focus on data flow, failure modes, validation, and long-term reliability, not just getting something to work once.
As a result, I often work in advisory, coordination, and systems-design roles. Typical engagements include:
- Technical project discovery and requirements definition
- Web architecture and stack advisory (PHP-centric)
- Technical coordination and delivery oversight
- Legacy web system and integration assessments
- Data integration and automation planning
- AI integration planning for web applications using APIs
Across all of this work, my approach is consistent: clarity over cleverness, structure over guesswork, and outcomes over hype. I help teams reduce risk by defining scope, making trade-offs explicit, and designing systems that behave predictably under real-world conditions.
I typically work with founders, teams, and organizations who need technical clarity before building or scaling, are integrating multiple systems and data sources, want AI embedded into real workflows rather than prototypes, and value predictable delivery with well-defined responsibilities.
If your goal is to make AI, integrations, and web systems practical, predictable, and productive in real operations, I can help you design and deliver systems you can rely on.
Steps for completing your project
After purchasing the project, send requirements so Novi can start the project.
Delivery time starts when Novi receives requirements from you.
Novi works on your project following the steps below.
Revisions may occur after the delivery date.
Prompt Intake & Context Review
I review your original prompt, the intended outcome, and any examples of errors or missing information to understand how and where the prompt currently fails.
Failure Point Identification
I identify structural weaknesses such as ambiguity, missing constraints, skipped reasoning steps, unclear roles, or instructions that encourage guessing.