AI training for teams who want to ship, not just watch slides
Practical training with exercises, examples, and the messy parts included. Built so teams can actually build after.
Training Tracks by Role
Different roles need different knowledge. Each track is designed for what that audience actually needs to do.
For Engineers
Build production AI systems
LLM Basics & Failure Modes
How these things actually work and where they break
Prompting Patterns
Techniques that hold up in production, not just demos
Retrieval Done Right
RAG, embeddings, chunking, and search quality
Tool Calling & Agents
Reliable function calling and agent orchestration
Evals & Monitoring
Measuring quality and catching regressions
Cost Control
Token economics, caching, and optimization
For Product & Ops
Spec and ship AI features
Use Case Selection
Picking AI projects that will actually succeed
Workflow Mapping
Designing AI-augmented processes
Quality Expectations
Setting realistic targets and review processes
Policy Basics
What product needs to know about AI governance
Rollout Planning
Launching AI features without disasters
For Leaders
Guide AI strategy and investments
AI Strategy Foundations
How to think about AI investments
Team & Skills
What to hire vs train vs outsource
Budgeting AI Work
Realistic cost expectations and ROI
Governance Overview
Risk, compliance, and responsible AI
How Training Works
Live sessions
Interactive instruction with Q&A and discussion
Hands-on labs
Exercises using real tools and your context
Homework (optional)
Extended practice between sessions
Office hours
Follow-up sessions to unblock and answer questions
What People Can Do After
- Write a decent AI feature spec
- Build a small working prototype
- Set up basic quality evaluations
- Talk to security and legal without panic
- Review and improve prompts systematically
- Evaluate build vs buy decisions
This is for you if...
Perfect fit
- Your team needs to level up on AI fundamentals quickly
- You want consistent knowledge across the organization
- You need engineers to build, not just understand
- You want product people who can spec AI features properly
- You value practical skills over theoretical knowledge
- You want training tailored to your tech stack and use cases
Not the best fit
- You need a one-time inspirational talk (see Speaking)
- You want hands-on project help (see Consulting)
Concrete Outcomes
No vague promises. Here's what actually changes.
Capable Team
People who can actually build, spec, and evaluate AI systems, not just talk about them.
Projects started, prototypes built, specs written post-training
Shared Language
Everyone uses the same vocabulary and mental models when discussing AI work.
Meeting efficiency, reduced miscommunication, faster decisions
Reusable Materials
Documentation, templates, and references your team keeps using after training ends.
Material usage, onboarding time for new hires
Ways to Work Together
Choose the engagement model that fits your needs and timeline.
1-Day Intensive
- Single track deep dive
- Hands-on exercises
- Reference materials
- Certificate of completion
3-Session Series
- Full track coverage
- Homework and practice
- Office hours access
- Team materials license
Custom Track
- Custom curriculum design
- Your tech stack focus
- Internal use case examples
- Ongoing support option
Want the real lessons from production AI?
No spam. Unsubscribe anytime. Your email stays private.
Build with people who actually ship
Join a community of practitioners who are building real AI systems, not just talking about them.