Development Framework

What this site is

This is the single source of truth for how EmeSoft delivers software in 2026. It is written for two audiences at once:

• Stakeholders & clients who want the big picture - how we work, what to expect, and where they plug in.
• The delivery team (PM, BA, Architect/Dev Lead, Developers, Cloud Engineers, Quality Engineers, Data Engineers) who need the concrete, day-to-day detail of their role, their inputs and outputs, and the AI tools they use.

Every role page follows the same structure so you always know where to look: Mission → Responsibilities → Inputs → Outputs → AI tools & how we use them → Collaboration → Pitfalls.

Three principles for AI at EmeSoft

Everything in this site is grounded in EmeSoft’s AI Applications Manifesto. Three principles matter most for how the delivery team works day to day:

Secure and Transparent by Default

AI tools are used through approved accounts only, with activity logs always on. Every AI-generated output clearly shows its source so teams can understand how it was created.

AI Assists, Humans Approve

AI helps us work faster, but people make the final decisions - especially for important code, system changes, and data work. Human oversight stays at the center.

Feedback Helps AI Improve

Everyone shares regular feedback on what works and what doesn’t. These insights help us refine tools, prompts, and workflows so AI becomes more useful over time.

These three are part of the eight principles published in our manifesto, and they recur throughout the AI Toolchain and Integration & Governance sections.

EmeSoft AI Center - our public hub

We share how we actually use AI publicly at emesoft.ai, the EmeSoft AI Center. It’s grounded in our AI Usage Statistics of 80+ practitioners across Dev, QC, Data, and Cloud teams, and brings four things together:

• AI Manifesto - the eight principles that keep our AI practices accountable.
• Technology Radar - the tools and techniques we Adopt, Trial, Assess, or Hold, with maturity rings.
• Metrics - survey-backed KPIs: adoption, productivity lift, AI-assisted PRs, and decision confidence.
• Role-based playbooks - how each role applies AI daily, including the Developer, Quality, Data, and Cloud Engineer deep dives.

This internal site is the detailed how-we-deliver companion to that public how-we-think hub.

The shape of the process

flowchart LR

PO["👤 Stakeholders"]
BA["👤 Business Analyst<br/>🤖 AI Copilot"]
AR["👤 Architect / Dev Lead<br/>🤖 AI Copilot"]
DEV["👤 Developers<br/>🤖 Coding Agent"]
QA["👤 QA Engineer<br/>🤖 Test Agent"]
REL["🚀 Validated Release"]

PO -->|Vision & Feedback| BA
BA -->|Requirements| AR
AR -->|Design & Tasks| DEV
DEV -->|Working Increment| QA
QA --> REL

KB[("Shared Knowledge Base<br/>BRD • Code • Standards • MCP")]

BA -.-> KB
AR -.-> KB
DEV -.-> KB
QA -.-> KB

This diagram shows how EmeSoft integrates Agentic AI into the software development lifecycle. AI agents assist each engineering role by automating repetitive tasks, generating high-quality artifacts, and leveraging a shared organizational knowledge base. Human experts remain responsible for decision-making, validation, and collaboration, while AI governance ensures secure, compliant, and effective use of AI throughout the delivery process.

Where to start

If you are new here, read the Process Overview, then the Scrum/Agile Foundation. If you want your own role, go straight to Roles at a Glance.