AI is like steroids. It can speed up the process, but you still have to go to the gym and practice the fundamentals. You have to suffer. (c) In this talk, I will explore the art and science of writing actionable, high-context prompts that transform AI from a "hallucinating assistant" into a productive teammate, without skipping the basics. We will start with a brief historical overview, comparing today’s Prompt-Driven Development (PDD) to the Readme-Driven Development (RDD) practices of the past. I will present practical techniques for maximizing the quality of AI-generated code by carefully tuning context, specificity, and scope, all demonstrated with concrete and relatable examples. I will also describe the concept of AI wrappers, the essential middleware behind tools like Cursor and Windsurf. Wrappers automatically gather context from the codebase, tailor prompts for optimal results, refine AI output, and embed changes directly inside editors like VS Code. This section will clarify why prompt engineering is a critical modern skill. I will also show my personal prompt collection in action. Then we will break down what makes an effective prompt and what does not, comparing and iterating live. I will illustrate why different scenarios require different types of prompts and explain why this matters for developers at all levels, not just juniors. To wrap up, I will outline key principles for AI-assisted development, including requirements analysis, collaborative habits, validation practices, and robust documentation. Attendees will leave with actionable guidance for integrating prompt-driven practices into their daily workflow. Slides What is PDD The Evolution: From RDD to PDD Prompting Matters: Context, Specificity, Scope My Prompt Collection Why We Need Different Prompts Why Prompting Is Important (not only for juniors) The Golden Rules of Vibe Coding

Platform Engineer | OSS Contributor Vlad is a seasoned full-stack developer with over a decade of experience building and maintaining scalable B2B platforms, as well as a dedicated open-source contributor. He currently works at Cybergizer in a hybrid SWE/CRE/SRE role, focusing on production reliability, systems design, and cross-functional engineering using languages like Ruby, Elixir, and Rust. He is a member of the Diesel.rs contributor team and the creator of opencryptolist.xyz, a platform dedicated to fostering open-source contributions in the blockchain industry. Vlad is also the author of getIDL.xyz – a tool to get IDL and source code info from closed-source Solana programs, using AI-based reverse engineering. He has open-sourced, maintained, and contributed to several libraries in the Ruby and Rust ecosystems (including pkcs12cracker, solscan-mcp, and visual-cryptography). He is also a writer for EffectiveProgrammer, AI Advances, IT Next, and Level Up Coding, and a three-time hackathon winner.