High-Tech
Your competitors' engineering teams are already choosing an agent.
Product cycles move faster than most companies' budgeting cycles. The question is not whether to use coding agents, but which one fits the task in front of the team.
What is current
What is actually being decided right now.
The technology choices look similar on a feature list. The operating priorities do not.
Coding agents chosen by task, not by company-wide mandate
Finance teams needing a current view of where engineering decisions become cost and revenue
ERP and supply chain systems expected to keep pace with quarterly roadmap changes
The AI layer, for High-Tech
The coding-agent landscape, benchmarked by task.
Options are evaluated against the systems, controls, economics, and ownership model already in place.
IDE-native work
GitHub Copilot for development workflows that stay close to the editor.
Repository-scale engineering
Claude Code and Cursor for broader codebase analysis, planning, editing, and testing.
Well-scoped autonomous work
Devin and comparable tools for bounded tickets, with mandatory human review at every tier.
Industry context changes the answer.
Where this shows up
What disciplined systems work changes for a high-tech company.
Evidence and operating patterns from work in comparable enterprise environments.
ERP modernization
Oracle E-Business Suite modernization across ERP, supply chain, and business intelligence.
Five-month CRM migration
A communications equipment manufacturer moved from legacy on-premise CRM to Salesforce Service Cloud.
Agent choice by task
Engineering workflows matched to the appropriate agent, review gate, and risk profile.
Where to start
The practices behind this work.
Start with the operating outcome. Bring in the practices required to make it production-ready.
Tell us your stack. We will tell you which agent actually fits the task.
Bring us the systems, constraints, and outcome. We will bring an architecture point of view grounded in delivery.