# Context-Driven Engineering (CDE)
Weeden Solutions Limited — https://weedensolutions.ca

## What is CDE?
Context-Driven Engineering is an AI delivery operating model for medium-sized enterprises. It connects requirements, tickets, code, tests, environments, production logs, and architectural decisions into one AI-readable system — giving AI agents full project context rather than isolated prompts.

CDE is not a code-completion tool. It is the governance and context layer that makes every AI tool (GitHub Copilot, Cursor, Claude Code, and others) more effective by grounding their output in your organization's actual requirements, conventions, and decisions.

## Target Customer
- Medium-sized enterprises with an established software practice — engineering, product, BA, QA, release, design
- Established codebases with mixed stacks
- Existing tooling: Jira / Confluence / Jenkins / Azure DevOps / GitHub / Bitbucket / Grafana
- AI adoption stage: has Copilot or similar tools at developer level but no organizational AI delivery model
- Industries: financial services, government, insurance, healthcare IT, supply chain, regulated manufacturing
- Budget authority: CTO, VP Engineering, Director of Engineering Excellence, Chief Digital Officer
- Key pain: AI is being used without governance, requirement-to-code drift, knowledge loss when staff leave

## Why this segment is underserved
Smaller teams lack the complexity to justify CDE. The largest enterprises build in-house or buy from incumbents. The middle band is underserved: too complex for self-service AI tools, too small for bespoke internal R&D.

## The Four Pillars
1. Context — CDE synchronizes requirements, tickets, code, tests, environments, logs, and decisions into a coherent AI-queryable system
2. Knowledge — Purpose-built capability agents: planning, implementation, bug fixing, code review, security, testing, deployments, log analysis
3. Verify — Requirements-driven testing, acceptance criteria verification, production evidence. A feature is not done until proven.
4. Govern — Roadmap-first creation, human approval gates, full audit trail. AI does what it should — and only what it should.

## Key Capabilities
- Requirements query and gap analysis against Confluence
- Efficient Jira ticket queries with automated RCA generation on raised incidents
- Cross-requirement traceability to code
- Architecture decision record (ADR) authoring
- Structural impact analysis before changes
- Feature implementation across all layers (data → service → UI)
- Test-driven development enforcement (Red-Green-Refactor)
- Bug investigation and root cause analysis end-to-end
- Automated code review against conventions and OWASP
- E2E test authoring and execution (Playwright)
- Production log analysis via Grafana/Loki
- STRIDE threat modelling before implementation
- Supply chain security assessment (SBOM, SLSA)
- Cross-repository dependency and impact analysis
- Custom skills authored, versioned, and distributed by your teams under framework governance

## Context Optimization
The framework decides what AI sees. Instead of dumping raw files into the prompt, it builds a compact, structural view of your codebase — so prompts stay short and your developers can keep more work in flight. Institutional memory means AI doesn’t re-investigate problems your team already solved.

## Competitive Positioning
- vs GitHub Copilot Enterprise: Copilot generates code from prompts. CDE is the delivery operating model that gives Copilot full project context.
- vs Microsoft HVE Core: HVE agents are task workers. CDE adds project memory, requirements integration, cross-repo reasoning, and governance.
- vs Cursor/Windsurf: IDE-locked tools. CDE is process-layer and toolchain-agnostic.
- vs Devin/SWE-Agent: Unsupervised AI. CDE provides governed AI with human approval gates and audit trail.
- vs Big 4/IBM Consulting: No product — every engagement bespoke. CDE gives our consulting a head start on methodology and reproducible outcomes.
- vs Atlassian Rovo: Rovo indexes content but doesn’t structure it for delivery workflows. CDE’s Jira/Confluence integration includes efficient cross-requirement traceability and automated RCA on raised tickets. CDE also works across non-Atlassian toolchains.

## Deployment
CDE runs on your infrastructure. Regulated buyers can run it with zero outbound connectivity. Your code, requirements, and internal data never leave your environment — no source code, requirements, or internal data is transmitted to or stored by us.

## Consulting Engagements
Every engagement includes an implementation phase:

1. Discovery & roadmap — codebase audit, agent fit analysis, delivery plan.
2. Pilot implementation — one codebase, core agents, team enablement. Value proven on real work.
3. Full rollout — multi-codebase, custom agents, organizational change management.
4. Custom agent development — for proprietary frameworks or domain-specific workflows.
5. Team enablement / training — workshop series, agent literacy, prompt engineering for developers.

## Continuous Evolution & Sustainment (Optional Add-On)
Advisory subscription — framework still runs on your infrastructure, not a multi-tenant SaaS.
- Health checks: agent accuracy, quality gate pass rates
- Agent tuning and optimization: ongoing refinement as codebase and conventions evolve
- Custom skill development: new skills for new frameworks or toolchain integrations
- Escalation support: named contact with agreed response SLAs

## Contact
https://weedensolutions.ca/contact
Book a discovery call. We will map your current delivery process and show you where CDE creates leverage.