AI DEVELOPMENT / 003
AI-NATIVE
DEVELOPMENT.
3+ YEARS / GPT-BASED DELIVERY
3+ years of continuous GPT-based software delivery. I use AI as an implementation layer inside a structured development process: requirements → implementation → manual validation → regression analysis → corrective specification → new iteration → deployment → release acceptance.
I have been working with GPT-based development workflows since 2023, progressively integrating new generations of AI systems into increasingly complex product delivery. My workflow is specification-driven rather than one-shot generation. Each major change begins with a defined functional outcome, constraints and acceptance criteria. Programming implementation is executed through AI-assisted development cycles, followed by hands-on functional validation, regression testing and iterative refinement. Complex functionality routinely moves through multiple implementation and verification rounds before acceptance.
Business logic, workflow, priority and expected outcome.
Detailed implementation briefs, edge cases, constraints and acceptance criteria.
Context preparation, implementation tasks, patch iteration, debugging and controlled refinement.
Information hierarchy, workflows, interface behavior and acceptance of visual result.
Personal hands-on testing of every significant feature and patch.
Verification that new changes preserve existing behavior.
Installation, environment checks, rollback readiness and final acceptance.
Vibe coding · Prompt engineer enthusiast · No-code developer · “ChatGPT built everything” · Pet project / hobby project · AI generated app in a few prompts
Release standard: I do not hand off an unvalidated release. Before delivery: functional QA, edge cases, regression, acceptance-criteria checks, and deployment / rollback readiness.