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Sample project (fictional test): Small Node.js bug fix. A tiny app had a failing answer function. In an isolated sandbox, I installed its locked dependency, reproduced the failure, changed one file, and reran three tests successfully. The sample delivery includes a clean ZIP, the diff, test output, and an install log. This was a Raven Money capability test, not paid client work.
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This project focused on building and testing a practical AI security assessment lab for evaluating LLM defenses against prompt injection and jailbreak attacks.
I integrated Spikee by Reversec with a locally hosted cybersecurity model running through LM Studio, then added NVIDIA NeMo Guardrails to compare model behavior under three conditions: no guardrails, input filtering, and combined input/output protection.
The work included configuring the local model environment, building a custom FastAPI gateway, integrating NeMo Guardrails, troubleshooting model latency and timeout issues, creating a reusable Spikee target, and analyzing attack results using Spikee’s built-in reporting tools.
The project also explored different adversarial testing approaches, including prompt injection datasets, obfuscation, encoded attacks, Best-of-N testing, synthetic canary leakage tests, and structured benchmark comparisons.
The objective was to measure how much the guardrails reduced successful attacks while keeping the model, dataset, and testing conditions consistent.
Tools used: Spikee, NVIDIA NeMo Guardrails, LM Studio, Python, FastAPI, PowerShell, Parrot OS, local LLMs, JSONL datasets, and custom security testing scripts.
This project demonstrates a hands-on approach to LLM red teaming, AI safety testing, prompt-injection assessment, and guardrail validation for organizations deploying generative AI systems.
pretty cool tbh. testing the same attacks with different guardrail setups makes the results way more interesting.
The problem
AI tools changed how fast good work gets made, but hiring still looks like 2015: long specs, hourly guesses, and no clear line between a prompt and a finished product. Clients want the result. Skilled people who build with AI want to be paid for outcomes, not hours.
What we built
VibeBay is a two-sided marketplace for finished AI work. A client posts what they need in plain words. Matched talent reply with a price, a delivery date and real samples. The client picks one, pays into escrow, and the money is released when they approve the work, or 7 days after delivery.
Inside the product:
Explore and search across six kinds of work, with talent profiles, portfolios, levels and reviews
Task posting, proposals with milestones, and checkout with escrow through Stripe
Real-time messaging between clients and talent
An AI assistant that helps clients describe the work and find the right person
Skill tests graded by AI, and profile import that turns an existing portfolio into a VibeBay profile
A full admin panel: approvals, moderation, support, orders and live campaign numbers
A pre-launch system with founding seats per country, referral codes and a countdown to opening day
How it's built
Next.js on Netlify, Supabase for the database, sign-in and file storage, Stripe for payments and escrow, Claude for the AI features, and Resend for email. Every page is checked automatically on each change at four screen sizes, from a small phone to a wide desktop, for accessibility and for broken buttons and links.
Where it is now
Founding seats are opening country by country, and the full marketplace opens on 31 October 2026.
Designed and built by Dreamec Studios.:
Just shipped KnowYuu 🎉
I recently finished building KnowYuu, a couples game app designed to help partners learn more about each other through fun questions, guesses, challenges, and deeper conversations.
One of the biggest milestones: KnowYuu was approved by Apple on our very first App Store review submission 🚀
From building the app and refining the experience to preparing the store listing and handling the release process, it’s been exciting taking KnowYuu from an idea to a real product available on the App Store.
Built with React Native + TypeScript.
Really proud to finally have this one out in the world. ❤️
apps.apple.com
KnowYuu App - App Store
Download KnowYuu by MOSES OLAOLUWA ADEBAYO on the App Store. See screenshots, ratings and reviews, user tips, and more apps like KnowYuu.
the couples game idea is so fun