Train Your Team to Build with AI
The Right Way
We teach engineering teams how to use AI coding tools effectively in production environments. Our training is built on spec-driven development, hands-on Claude Code mastery, and the same practices we use daily to build platforms at scale.
AI Tools Are Everywhere. Best Practices Aren't.
Your team is using AI to write code. But without shared standards, the output is unpredictable, unreviewable, and unscalable.
Inconsistent AI Output
Most teams adopt AI coding tools individually. One developer uses it for tests, another for boilerplate, a third ignores it entirely. The result: inconsistent code quality, unpredictable outputs, and no shared standards for how AI fits into your development process.
No Production Standards
AI-generated code that works in a demo can break in production. Without deterministic workflows, validation frameworks, and spec-driven guardrails, AI becomes a liability rather than a multiplier. Especially at scale.
Isolated Learning
Developers are learning AI tools in isolation, watching tutorials and experimenting in side projects. But enterprise development isn't a solo activity. Teams need shared conventions, shared commands, and shared understanding of when and how AI accelerates their specific workflows.
Spec-Driven AI Development for Production Teams
A structured methodology that turns AI from a novelty into a reliable part of your development lifecycle.
Spec-Driven Development
Specs as the source of truth. Intent before implementation. We teach the methodology that GitHub, JetBrains, and Red Hat are converging on: structured specifications that make AI output predictable and reviewable.
Claude Code Mastery in VS Code
CLAUDE.md configuration, shared command libraries, prompt engineering for code generation, and parallel development workflows. Hands-on, in-editor training. Not slides.
Deterministic Workflows & Change Tracking
Predictable, reproducible AI outputs. Validation frameworks, Git-integrated change tracking, and specs that create accountability for every line of AI-generated code.
Scaling Across Distributed Teams
Standardize AI practices when your team spans time zones, repos, and tech stacks. CLAUDE.md as team conventions. Shared commands. Review processes for AI-generated PRs.
A Training Program That Sticks
Assessment
We evaluate your team's current AI tool usage, codebase patterns, and development workflows to customize the training to your actual environment.
Foundation
Core methodology training: spec-driven development principles, Claude Code setup and configuration, CLAUDE.md conventions, and the fundamentals of deterministic AI workflows.
Hands-On Workshops
Your team works in their actual codebase using Claude Code in VS Code. Real feature development. Real code reviews. Real problems.
Integration
We help embed these practices into your existing processes, including CI/CD pipelines, Git workflows, code review checklists, and team conventions documentation.
Ongoing Support
Post-training review cycles, updated best practices as tools evolve, and availability for follow-up sessions as your team scales its AI-assisted development.
Built for Teams That Build at Scale
Engineering Teams
Development teams of any size adopting AI coding tools and looking for a structured, production-ready approach instead of ad hoc experimentation.
Technical Leadership
CTOs, VPs of Engineering, and Engineering Managers who need to standardize AI development practices across their organization with governance and consistency.
Distributed Organizations
Companies with remote or distributed engineering organizations that need shared AI workflows, conventions, and quality standards across time zones and teams.
What Your Team Will Learn
Our curriculum covers everything your engineering team needs to adopt AI coding tools with confidence, from foundational methodology to advanced team workflows.
Schedule a ConsultationTopics Covered
- Writing effective AI specifications
- CLAUDE.md configuration and team conventions
- Shared command libraries for common workflows
- Deterministic code generation and validation
- Change tracking with Git integration
- Code review practices for AI-generated code
- Scaling AI workflows across teams and repositories
- When to use AI coding tools (and when not to)
Tools We Train On
Frequently Asked Questions
Our training focuses on Claude Code integrated with VS Code. We teach spec-driven development methodology and deterministic workflows that apply broadly, but our hands-on instruction centers on the Claude Code toolchain.
No. We design the program around your team's current skill level, from teams that haven't used AI tools yet to teams that have been experimenting individually and need structure.
We're practitioners who build platform-level software using these practices daily. Our training is hands-on, customized to your codebase and workflows, and designed for team adoption rather than individual learning.
Yes. Our training methodology is specifically designed for distributed teams. We teach shared conventions, async-compatible workflows, and the tooling configuration needed for consistent AI-assisted development across time zones.
Ready to Transform How Your Team Builds?
Let's talk about how spec-driven development and AI-assisted workflows can level up your engineering team. No commitment required. Just a conversation about what's possible.
Schedule a Consultation