AI-Driven Development
Accelerate your software delivery by 3-5x with Claude Code integration
What We Help With
Practice Assessment
A clear-eyed review of how your team ships today. We map workflow, tooling, and review process, then identify where AI assistance produces measurable gains and where it does not.
Tooling Strategy
Which assistants, agents, and MCP integrations fit your stack. Recommendations come from daily production use, not vendor briefings.
Team Enablement
Hands-on training and pairing. Prompting patterns, repository conventions, and review workflows your developers keep using after the engagement ends.
Guardrails & Governance
Policies that let teams move fast safely: review gates, security scanning, data-handling rules, and explicit boundaries for what AI tooling can touch.
Proof From Our Own Delivery
Engagement Path
Assess
We work inside your actual workflow: repositories, tickets, review process, deployment pipeline. The output is a written assessment of where AI assistance will help, where it will not, and what to try first.
Pilot
One team, one real project, measured. Baseline metrics are set before the pilot starts, so the results are defensible: cycle time, review time, defect rate.
Enable
Training, pairing sessions, and playbooks. What works gets codified into repository conventions and prompt patterns your team owns and maintains.
Scale
Roll out across teams with guardrails in place. Periodic reviews keep the practice current as tools change.
We Use This Practice Daily
This is not theoretical advisory. Refined Element builds with AI as the default workflow. This website and Sentinel (our open-source health scanner for Xperience by Kentico) were both delivered AI-first with Claude Code and KentiCopilot.
The delivery-acceleration numbers above come from that work. When we advise on tooling, guardrails, or team workflow, the recommendations have already survived contact with production.
What That Looks Like
A Kentico Xperience 13 widget ported to Xperience by Kentico: KentiCopilot's migration tooling drafts the conversion, Claude Code adapts it to the repository's conventions, and a developer reviews and ships it.
Hours instead of days, with the same review gate every other change passes through.
AI Consulting FAQ
Which AI tools do you recommend?
It depends on your stack and constraints. We work daily with Claude Code, KentiCopilot, and MCP-based integrations, and we evaluate candidates against your codebase rather than recommending from a list. The pilot phase exists to test the shortlist on your real work.
Will AI-generated code meet our review standards?
Yes, if the workflow enforces it. AI-assisted code goes through the same tests, reviews, and quality gates as any other code. We help you set those gates up so quality is a property of the process, not of trust in a tool.
How do you handle security and IP concerns?
Data-handling boundaries are defined before any tool touches your code: enterprise agreements, retention settings, and explicit rules for what may leave your environment. For regulated teams, we scope tooling to what your compliance requirements allow.
Where do teams usually see gains first?
Migrations, test coverage, boilerplate, and documentation. These are high-volume, well-specified tasks where AI assistance is reliably strong. Complex domain logic improves later, once conventions and guardrails are established.
Is this a one-time engagement or ongoing?
Either. Assessments and pilots are fixed-scope. Most clients continue with an enablement retainer while the practice beds in, then taper to periodic reviews.
Ready to Build an AI Development Practice?
Start with an assessment of how your team ships today and where AI assistance will produce measurable gains.
Schedule a Consultation