Most engineering teams of 5–20 already use AI coding tools. The problem is not adoption. It is consistency.

When every engineer prompts differently, output varies engineer to engineer. PRs look different. Reviewers cannot tell what to scrutinize. Senior engineers absorb the extra review load. The benefits stay siloed with whoever prompts best.

We help small engineering teams build structured AI-assisted development workflows so the gains become team-wide and code review, tests, and commit standards stay intact.

Our founder has 14+ years building production systems in Python and developer tooling. The structured method we use in sprints is documented publicly in three open-source repos: agent-context-base, agent-cloud-context-base, and language-atlas.

The entry offer is a five-business-day Proof Sprint. One real target in your repo, built alongside your team, through your existing review process. By Day 5 you have working software, a documented workflow, a PR review checklist grounded in your conventions, and an honest rollout recommendation. Adopt it now, trial it for one quarter, or walk away. No upsell pressure.

For teams that want to extend the workflow across the codebase, we offer a 2–4 week System Setup. For teams that want ongoing guidance as their AI usage evolves, we offer monthly Advisory.

We work with CTOs, founders, VPs of Engineering, engineering managers, technical leads, and agency owners at 5–50 person companies already using Claude, Codex, Copilot, Cursor, or similar tools.

This is structured AI-assisted development. Humans write and review code with AI tools, inside your existing process. No autonomous systems in production.

Kenjyco LLC

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Kenjyco LLC

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