Engineering & technology advisory
AI Strategy & Agentic Engineering
Adopt coding agents around engineering work where they can help, and create the conditions for them to contribute reliably. Agentic engineering changes workflows as well as tools: repository context, task boundaries, evaluation, secure access and human review all matter.
Who it helps
For CTOs, engineering leaders and teams assessing coding agents, moving beyond individual experimentation, or deciding how AI should fit into software delivery and engineering standards.
The challenges
Tool trials can be difficult to evaluate, codebases may lack the context agents need, and teams may not know which work is suitable for delegation. Weak task boundaries, missing checks or broad tool permissions can make generated changes hard to trust and review.
How we can help
Identify valuable engineering use cases and assess codebase and workflow readiness. Shape repository guidance, task design, secure tool access, evaluation and review practices. Where useful, run practical workshops or help implement a focused workflow so the team can learn from real use and decide what to scale.
What changes
Create a grounded adoption strategy, choose use cases based on engineering value, and give teams practices for checking agent contributions. Keep engineers accountable for direction, architecture and quality while making routine work and complex problem-solving more effective.
Ways to work together
An AI and engineering workflow assessment, leadership strategy session, hands-on team workshop, or a scoped implementation of an agent-assisted workflow with evaluation and review practices.
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