Day 1 - Agentic Engineering/VIbe Coding an AI App from Zero To Production | 🔴 Live

2026-05-03 · Source: Venelin Valkov · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Robotics & Autonomous Systems · Depth: Intermediate, extended

Summary

This content introduces a new series focused on building and deploying an AI application, "Arit," an AI-powered pet habit and goal tracker. The application features an AI pet that changes mood based on user performance, offers encouragement or "judgy" feedback, and remembers user goals and habits. The initial planning phase utilizes a modified "Interview Me" skill within the Codex tool, inspired by the Q*ME method, to generate a product requirements document (PRD). This interview process, conducted using GPT 5.5 high, explores core features like a Sunday email progress report, MVP scope focusing on planning value, day-one onboarding, logging mechanisms, AI inference boundaries, pet mood representation, species differentiation, AI speaking rules, goal models, and accessory unlocking. The session successfully produced a detailed PRD, consuming only 3% of the usage limit on a $20 plan.

Key takeaway

For AI Product Managers defining new applications, consider integrating AI-powered interview tools like the modified "Interview Me" skill into your planning workflow. This approach can rapidly generate detailed product requirements and specifications, ensuring a comprehensive understanding of features, user experience, and technical boundaries from the outset, while optimizing resource usage for large language models.

Key insights

AI-driven interview skills can efficiently flesh out complex application specifications and product requirements.

Principles

• Prioritize essential utility over gamification for initial user engagement.
• AI should infer operational patterns, not user identity or emotional states.
• Pet evolution should reflect relationship maturity, not just performance metrics.

Method

Utilize a custom "Interview Me" skill in Codex, based on Q*ME, to iteratively define application features and scope through a structured question-and-answer session, generating a PRD with AI assistance.

In practice

• Implement a weekly email review for users to renegotiate goals.
• Focus MVP on converting vague goals into concrete, actionable plans.
• Design pet accessories as cosmetic souvenirs of user patterns, not gameplay elements.

Topics

• Agentic Engineering
• AI Application Development
• Arit Pet Tracker
• Codex AI Platform
• LLM-driven Product Planning

Best for: AI Engineer, AI Product Manager, Director of AI/ML

Related on AIssential

• Day 5 - Agentic Engineering/VIbe Coding an AI App from Zero To Production | 🔴 Live — AI agents can achieve high test coverage and implement features in complex applications.
• The rise of the professional vibe coder (a new AI-era job) | Lazar Jovanovic (Professional Vibe Coder) — Effective AI-driven development prioritizes clarity, planning, and design judgment over traditional coding skills.
• You NEED to know these vibe coding secrets — Structured agent configuration, reusable skills, and continuous loops automate advanced AI coding workflows.
• Presentation: Directing a Swarm of Agents for Fun and Profit — Orchestrating AI agent swarms enables rapid, cost-effective, and lower-carbon software development, shifting focus to platform engineering.
• Beyond Spec-Driven Development: The Agentic Engineering Playbook That’s Replacing How We Build… — Agentic engineering integrates AI agents into software development with structured human oversight for intent definition and output verification.
• Day 2 - Agentic Engineering/VIbe Coding an AI App from Zero To Production | 🔴 Live — AI agents can rapidly generate functional prototypes and manage project workflows from high-level requirements.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Venelin Valkov.