Remote or On-site1 DayNew York, USA

AI Engineering for Dev Teams in New York

Your team in New York is already using AI tools — but there's no consistent workflow. This 1-day workshop closes that gap. From setting up AI dev environments with Cursor and Claude Code to shipping with AI-integrated code review and CI pipelines, on your actual codebase.

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Why Take This Workshop in New York?

New York's tech scene rivals Silicon Valley, with major engineering teams in fintech, media, and enterprise SaaS. The city's dev community is among the largest and most diverse in the world. Our AI engineering workshop in New York helps dev teams go from ad-hoc AI usage to a structured, production-grade AI workflow — in one day.

Workshop at a Glance

Duration

1 Day

Format

Remote or On-site

Participants

Up to 15 participants

Price

€4,500/team

What Your Team Will Learn

This workshop is for dev teams already shipping code with AI tools — or about to start. By the end of the day, every engineer has a configured environment, a shared review process, and a playbook they actually follow.

A fully configured AI-native dev environment for every engineer
A shared code review process designed for AI-assisted development
Clear rules for when to trust, edit, or reject AI-generated code
An AI-integrated CI/CD pipeline with security and quality gates
A written AI engineering playbook your team actually follows

Workshop Curriculum

From AI-native dev environments to production CI pipelines — your team works through real scenarios: writing features with AI, reviewing AI-generated code, catching bugs before they ship, debugging in production, and defining ownership when AI writes most of the code.

AI-native dev workflows — from setup to shipping

What an AI-native engineering workflow looks like in 2026
Cursor and Claude Code in practice: agent mode vs. completion mode
Context management: .cursorrules, architecture docs, README hygiene
Hands-on: set up your AI environment and ship a feature on a real codebase
AI in the PR and review cycle: CodeRabbit and alternatives
AI-powered static analysis in CI: tests, security, and quality gates
AI-assisted debugging: logs, traces, errors → root cause
The handoff problem: code ownership when AI writes 80% of a feature
Debrief: build your team's AI engineering playbook

Tools & Focus Areas

IDE

Cursor & Claude Code

AI-assisted coding in practice. Context management, agent mode, and building a workflow that scales across a team.

Review

CodeRabbit & PR Review

AI as a first pass in your review cycle. Integrating automated review into PRs without replacing human judgment.

CI/CD

Snyk, Semgrep & CI

AI-powered static analysis, security scanning, and quality gates in your CI pipeline for AI-generated code.

Your Instructor

Davy Engone

Founder & Software Mentor @ Hackages

Davy has trained 5,000+ engineers and built AI agents in production. This workshop is what he wishes every dev team had — practical, hands-on, and designed to change how your team works with AI starting the next day.