Learn what progress
requires.

Practical learning for people who need artificial intelligence to work beyond the demo. Build stronger judgment, repeatable methods, and systems your organization can trust.

Explore classes
Short courses Applied practice Team sessions

Learn · Apply · Build

Short Course

Repeatability + Reliability

Turn promising AI work into an operating capability. This short course focuses on the methods, evidence, and controls that help teams produce useful outcomes consistently.

Class commitment: 1.5 hours

Learning catalog

Capability grows through practice.

Each class combines clear frameworks, guided exercises, and usable takeaways. Select a class to review its description, agenda, and registration area.

An orange singularity representing accountable agentic systems

AI governance · On-demand

Governing Agentic Workflows

Learn at your pace while setting authority boundaries, escalation paths, and evidence standards for AI that can act.

The AI Moment graphic connecting intelligence, singularity, and audacity

Data practice · Foundations

Data Foundations for AI

Clarify ownership, quality, lineage, and access before weak data becomes an AI risk.

Designed for transfer

Leave with a method, not just notes.

  1. 01

    Frame

    Connect the learning objective to a consequential business decision.

  2. 02

    Practice

    Work through realistic scenarios with feedback and structured reflection.

  3. 03

    Build/Acquire

    Engineer and implement the tested concepts in your real-world context with guidance and support.

  4. 04

    Transfer

    Take away templates, agentic flows, libraries and next steps that fit your operating context.

For teams

Bring the classroom closer to the work.

Private cohorts can be shaped around your systems, operating model, and decisions.

Short course · 1.5 hours

Repeatability + Reliability

Explore how to specify outcomes, repeat tests, and review behavior before trusting AI with consequential work.

Specify, Generate, Review: a four-step cycle of specifying outcomes, generating repeated runs, reviewing against the standard, and stress testing operating conditions.
Critical outcome testing: repeat until reliable.
Customer Refund Reply: Repeated Test Plan. Five scenarios cover a repeated baseline, missing data, ambiguous requests, an unavailable tool, and a critical outcome gate.
A customer refund reply: repeated tests and failure conditions.

Who Should Join

For people moving AI into everyday work.

This course is for leaders, builders, and practitioners who have tried AI and now need a repeatable way to put it to work. Bring one workflow you want to improve and a willingness to test what happens when the inputs or operating conditions change.

  • Business and team leaders deciding where AI can help and what evidence they need before trusting it.
  • Product, operations, and data practitioners turning promising experiments into dependable workflows.
  • AI builders and technical teams setting project files, evaluation criteria, and boundaries for agentic work.

Class details

Class title

Agenda

    Speaking request

    Schedule Odiambo to speak.

    Share your organization, audience, and event details. We will review your request and follow up using your business email.

    Executive briefing

    Executive Engagement

    Request a focused engagement for organizational leaders, elected or administrative public leaders, or a board. Topics may include governance, cybersecurity and risk management, and AI project design and implementation.

    Meeting format

    Engagement inquiry

    Interested in solving your problems with Odiambo solutions?