Corporate Training & Workshops
Hands-on training programs for engineering teams, product leaders, and executives navigating AI adoption. Built on real-world experience deploying AI in regulated financial environments, not recycled slide decks.
Programs
AI for the Enterprise
A foundational program for teams beginning their AI journey. Covers the practical landscape of large language models, prompt engineering, RAG architectures, and AI integration patterns. Designed for engineering and product teams that need to move beyond experimentation and start building.
What’s covered
LLM Fundamentals
How models work, token economics, model selection criteria, and when to use which approach (API, fine-tuning, RAG, agents).
Prompt Engineering & RAG
Production-grade prompt design, retrieval-augmented generation patterns, embedding strategies, and context window management.
AI Integration Architecture
Patterns for integrating LLMs into existing systems. API design, error handling, fallback strategies, and cost optimization.
Evaluation & Governance
How to measure AI output quality, build evaluation pipelines, and establish governance frameworks for production deployments.
Agentic AI & Multi-Agent Systems
Advanced training for teams building autonomous AI systems. Covers agent architectures, tool use, multi-agent coordination, and the operational challenges of deploying agents that take real actions in production environments.
What’s covered
Agent Architecture Patterns
ReAct, plan-and-execute, reflection loops, and when each pattern is appropriate. Building agents that are reliable, not just impressive in demos.
Tool Use & Function Calling
Designing tool interfaces, managing tool permissions, error recovery, and building agents that interact safely with external systems.
Multi-Agent Coordination
Orchestration patterns, shared state management, agent-to-agent communication, and avoiding cascading failures in agent networks.
Production Operations
Monitoring, observability, human-in-the-loop controls, audit trails, and the operational discipline required for autonomous systems.
AI-Augmented Software Development
A practical program for engineering organizations integrating AI into their software development lifecycle. From code generation and review to testing, documentation, and deployment. Focused on measurable productivity gains without sacrificing code quality or security.
What’s covered
AI-Assisted Development
Effective use of coding assistants, context management, prompt patterns for code generation, and integrating AI into existing IDE workflows.
Automated Testing & QA
AI-driven test generation, coverage analysis, mutation testing, and building quality gates that leverage LLMs without creating false confidence.
Code Review & Security
AI-augmented code review processes, vulnerability detection, dependency analysis, and maintaining security standards with AI-generated code.
SDLC Transformation
Measuring developer productivity gains, reorganizing workflows around AI capabilities, and building an AI-native engineering culture.
Format & Delivery
- Led by a practitioner, not a trainer. Every session is delivered by someone who has built and shipped these systems at scale.
- Customized to your stack and domain. Programs are tailored to your technology environment, regulatory context, and team maturity level.
- Hands-on, not lecture-based. Participants build working prototypes during the workshop using their own tools and infrastructure.
- Available on-site or remote. Half-day, full-day, and multi-day formats. Programs can be combined or run as a series.
Bring a workshop to your team
Tell us about your team, technology environment, and what you’re trying to accomplish. We’ll design a program that fits.
Request a Workshop