Trackman

Implemented Home Screen for all the tenants: Lufthansa, Swiss, Brussels, Austria which uses millions of users. Winner of 'Battle of the Airline Apps’ 2024. Decreased app size 40% by optimizing modularization, linking, file format. Developed a Server Driven UI (SDUI) new way to update and manage the user interface on iOS apps for Lufthansa, Austrian, Brussels, and Swiss airlines using SwiftUI. Worked on changing a Python machine learning model (Stable Diffusion) to be used with CoreML. Wrote an article about how I did it: https://shorturl.at/hxJ02." Explored how to predict what users might do next using CoreML. Shared

Fine-Tuned Model. Built for prompts. Only prompts. Sapa does not use a general-purpose LLM. The model was fine-tuned on prompt engineering patterns, security anti-patterns, and token efficiency techniques. It understands what makes a prompt good or dangerous in ways generic models miss. Token Optimizer. Same result. Fewer tokens. Lower cost. The model restructures your prompt - removes redundancy, clarifies intent, improves context layout - so the receiving LLM needs fewer tokens. Average reduction is 38%. 100% Private. Your data never leaves your machine. Sapa runs a fine-tuned model entirely inside your Mac memory. Your prompts are processed locally and discarded immediately - never sent to any server. Security Scan. Catch what you almost sent. Before you hit send, Sapa detects credential leaks, PII exposure, API keys, connection strings, and injection patterns. Plain-English explanations tell you the risk, not just that one exists.

Deterministisk kodebase analyseværktøj