I’m a Full-Stack and AI developer currently open to long-term collaborations. If you’re looking for a reliable partner, feel free to reach out anytime. I’m ready to provide dedicated support and help move your projects forward.

✨ The AI Quirk: You give AI a clear instruction at the start of a prompt… but the response seems to ignore it completely. Even stranger, if you repeat the instruction later in the prompt, suddenly the AI follows it perfectly. ✨ What’s Going On: - Large language models weigh instructions "based on proximity and clarity" within the prompt. - Instructions buried early in a long message can lose influence once the model begins predicting the response. - The model often prioritizes "the most recent instruction signals" it sees. - If a prompt contains mixed signals (examples, context, and instructions together), the model may treat the first instruction as "background instead of a rule". Example: You start with: 1) Write this in bullet points. 2) Then provide a long paragraph of context. The model may treat the context as the main task and default to paragraphs. But if you end the prompt with: “Use bullet points for the final answer”, the output suddenly follows the rule. ✨ What To Do If You See It: - Place "critical instructions at the end of the prompt". - Separate instructions from context using spacing or labels. - Repeat important constraints when precision matters. Try this prompt: “Using the context above, produce the final answer in bullet points only.” ✨ Why This Happens: AI isn’t reading instructions like a human would. It’s predicting the next most likely text — and "AI tends to pay the most attention to the instructions it sees last." ✨ AI Bits & Pieces — helping people and businesses adopt AI with confidence.

I’m an AI + Full Stack Engineer focused on LLM systems, autonomous agents, workflow automation, and multimodal AI (text · voice · vision). I build production-grade AI systems, not demos, connecting LLMs, APIs, databases, real business logic, designed for reliability, scale, and real usage. Core Skills • LLM orchestration (DSPy, LangChain, AutoGen, CrewAI, ReAct) • RAG pipelines (vector DBs, hybrid search, custom retrievers) • Multi-agent systems (planning, tool use, reflection loops) • Multimodal AI (Whisper, CLIP, YOLOv8, TTS) • Full-stack & backend (Next.js, React, FastAPI, NestJS) • Automation & integrations (n8n, Zapier, Make, custom APIs) • AI agents for research, ops, and customer support • Knowledge assistants & internal tools (RAG-based) • Workflow automation & AI copilots • Multimodal chat / voice assistants • MVP → production AI system delivery If you need help turning messy workflows into reliable AI systems, happy to connect 🤝