The Ascent of Engineering

From Foundational Code to the Agentic Enterprise: A Maturity Model

👶CRAWL

Mastering the Fundamentals

This is the non-negotiable foundation. Before speed, there must be stability. The crawl stage is about building a robust, automated pipeline that enforces quality, security, and consistency for every line of code committed.

Essential Engineering Hygiene Pipeline

Code & Branch Policy
PR & Code Review
CI & Unit Tests
Quality Gates (Code Coverage, Vuln Scan)
Build Artifact
Automated Tests
Deploy

This diagram illustrates the mandatory, sequential flow of the CI/CD pipeline, where each step ensures the integrity of the software before it progresses, culminating in a safe, automated deployment.

🚶WALK

Accelerating with AI Assistance

With a solid foundation, we can now focus on velocity. The walk stage introduces AI-powered tools that act as copilots for developers, automating repetitive tasks and accelerating core activities across the SDLC, from coding to test creation.

AI-Driven Productivity Gains

This chart compares the estimated efficiency boost from AI assistants in various development phases. The greatest impact is seen in code generation and test automation, significantly reducing manual effort.

🏃RUN

Automating with Agentic Platforms

The focus shifts from assistive tools to autonomous platforms. The run stage establishes an Internal Developer Portal (IDP) as a central, self-service hub. Here, AI agents execute complex operational tasks on behalf of developers, from provisioning infrastructure to managing cloud costs.

The Self-Service Agentic Hub

Agentic IaC
AI-Assisted Pipelines
Infrastructure Monitoring
Autonomous FinOps
Cloud Operations
Self-Service Portals

This organized grid represents capabilities managed by an IDP. It provides developers with a self-service interface where AI agents handle the underlying complexity of DevOps and CloudOps tasks.

🚀FLY

Orchestrating the Agentic Enterprise

This is the ultimate state of maturity. Engineering transcends software creation to enable intelligent business automation. By exposing enterprise APIs as tools for AI via the Model Context Protocol (MCP), agents can now directly orchestrate complex business workflows, driving unprecedented operational efficiency.

Enterprise API Ecosystem Flow

Agentic AI(MCP Client)
→
MCP Auth & Gateway(Secure Tooling Layer)
→
Enterprise Business Capabilities(APIs as Tools)

This diagram shows the relationship where Agentic AIs securely access and utilize core enterprise data and functions (like inventory or finance) through a specialized MCP gateway, transforming APIs into actionable tools for intelligent automation.