AI MDLC Kernel FAQs

Question 1

How does the AI MDLC Kernel work?

Accepted Answer

It uses plain markdown files as an agent-agnostic control plane, guiding a single AI agent through specialized roles (Researcher, Architect, Spec Writer, Engineer, QA, SRE). This structured 'Markdown Development Life Cycle' (MDLC) ensures disciplined execution, from research to a working system.

Question 2

What kind of output can I expect from the AI MDLC Kernel?

Accepted Answer

The kernel delivers a fully functional, production-grade software system. This includes runnable code, passing tests, comprehensive logging, and an integrated traceability layer with audit trails for decisions, changes, reports, compliance, and security.

Question 3

Is the AI MDLC Kernel compatible with any AI agent or model?

Accepted Answer

Yes, the AI MDLC Kernel is designed to be fully agent-agnostic and model-agnostic. It uses plain markdown as its control plane, allowing you to 'bring any AI, any tool.' Larger, more capable models typically yield better performance.

Question 4

What makes AI MDLC Kernel unique compared to other AI coding tools?

Accepted Answer

Its core differentiation is the Markdown Development Life Cycle (MDLC), which provides a structured, document-driven pipeline. This enables unprecedented traceability with audit trails for every decision, agent/model-agnostic control via `.md` files, and built-in self-correction and security invariants, moving beyond ad-hoc prompting.

Question 5

What is the AI MDLC Kernel?

Accepted Answer

The AI MDLC Kernel is an autonomous, self-correcting software development pipeline that transforms structured markdown (`.md` files) into production-grade software. It provides a document-driven approach for highly traceable and disciplined software delivery.

AI MDLC Kernel

AI MDLC Kernel

Key Features

Use Cases

Key Features

Use Cases