Unapproved tools become shadow engineering infrastructure
Teams adopt coding agents independently, creating inconsistent source-code handling, access, and audit exposure.
Agentic Software Engineering
Adopt AI coding agents as a governed engineering capability.
Help engineering organizations adopt AI coding agents securely — from readiness and tool evaluation through secure pilots, enterprise rollout, MCP integration, DevSecOps transformation, and developer AI governance.
Readiness & tool evaluationSecure pilotsRepository intelligenceMCP & DevSecOpsDeveloper AI governance
Practice coverage for GitHub Copilot, OpenAI Codex, Claude Code, and Cursor.
Why teams engage
The adoption risks that appear before enterprise scale
Coding agents create value quickly, but unmanaged tools, weak repository context, and unclear execution boundaries prevent safe expansion.
Pilots stall without repository context or evidence
Promising demos do not become repeatable delivery when instructions, approved repositories, and success measures are missing.
Agent and MCP access outpaces the operating model
Tool integrations expand before authentication, authorization, human review, and exception ownership are agreed.
Engagements
Start with the decision your engineering organization needs to make
Core engagements establish readiness and pilot direction. Specialist extensions add repository intelligence, MCP integration, DevSecOps workflows, or governance depth.
Core engagementsAssessment → pilot → rollout
AI Coding Readiness Assessment
Engineering maturity, repository classification, data-handling review, security posture, use-case prioritization, tool shortlist, and an adoption roadmap with an initial value model.
Book readiness assessmentAI Coding Tool Evaluation
Structured comparison of GitHub Copilot, OpenAI Codex, Claude Code, and Cursor across codebase understanding, security, administration, integration, cost, and auditability.
Request tool evaluationSecure Engineering Pilot
One or two teams, approved repositories and workflows, repository instructions, security controls, training, baseline metrics, and a pilot report leadership can act on.
Plan a secure pilotEnterprise Rollout
Identity and access, team configuration, approved models, repository onboarding, MCP controls, security policies, champions, analytics, and a durable operating model.
Design enterprise rolloutSpecialist extensionsContext · MCP · DevSecOps · governance
Repository Intelligence
AGENTS.md, CLAUDE.md, Copilot instructions, Cursor rules, architecture guidance, security rules, and pull-request standards that make agents reliable on your codebases.
Improve repository intelligenceMCP Integration Factory
Use-case discovery, MCP server design, schemas, authZ, audit, approval workflows, client integration, testing, documentation, and support for production MCP tooling.
Build MCP integrationsAgentic DevSecOps
Agent-assisted issue analysis, test generation, PR creation, code and security review, dependency updates, CI failure analysis, vulnerability triage, and runbook generation.
Transform DevSecOpsDeveloper AI Governance
Approved tool and model matrices, repository classification, source-code handling, MCP and command-execution policy, human-review rules, audit requirements, and incident handling.
Establish governanceAI coding platforms
Select by engineering fit and control requirements
Platform pages cover product-specific capabilities and security considerations; this practice provides the cross-platform operating model.
GitHub · Microsoft Ecosystem
GitHub Copilot
Adopt GitHub Copilot across engineering teams with enterprise controls — content exclusions, identity-aligned access, repository instructions, and adoption measurement that security and leadership can stand behind.
View platform guidanceOpenAI · Agentic CodingOpenAI Codex
Bring OpenAI Codex into enterprise engineering with clear repository context, secure automation boundaries, MCP controls, and team workflows that improve delivery without sacrificing auditability.
View platform guidanceAnthropic · Terminal AgentsClaude Code
Operationalize Claude Code for enterprise engineering teams — repository instructions, MCP servers, permission models, and secure agentic workflows that fit existing DevSecOps practices.
View platform guidanceCursor · AI-Native IDECursor
Roll out Cursor as an enterprise AI-native development environment — project rules, agent permissions, MCP controls, and measured adoption that fits security and platform standards.
View platform guidanceDelivery lifecycle
Move from readiness to governed scale with explicit outputs
Each phase resolves a different enterprise decision and leaves an artifact the next phase can use.
Assess readiness and tool fit
Evaluate engineering maturity, repository risk, data handling, and platform fit.
Readiness scorecardDesign pilot boundaries
Define approved repositories, agent permissions, MCP boundaries, review gates, and success measures.
Pilot charterEnable teams and repositories
Run the pilot with repository guidance, applied training, office hours, and measurement.
Operating playbookScale and govern
Expand through policy, champions, analytics, control ownership, and an optimization cadence.
Scale roadmapLearning pathways
Programs that support the engineering operating model
Start here
Shape a governed agentic software engineering program
Share your coding-tool landscape, repository constraints, security posture, and rollout goals. We’ll help determine the right assessment, pilot, or governance path.
Tool evaluation
Secure pilot design
MCP and governance
