CT Academy

Hosted by Siosi Samuels

Guidance Beyond Language: Wisdom, Embeddings & LLMs

Edward Kennedy

Pioneering Human Centric AI

Utilizing Diffusion Side Context Injection and Resonant Embedding Guidance to gain control over AI model aesthetics

Embedding guidance technology

Real-time video generation and dynamic web content to enable models to act with the depth rather than static personas

Scaling embedding technology applications

Bridging technical AI startups with spiritual practices to help maintain philosophical awareness while navigating tech

Ties to the Conscious Technologist movement

Arming senior leadership teams with the AI literacy, practical skills and strategic acumen needed to guide their companies into the AI era.

September 2026 Cohort

AI Strategist // Trainer // Futurist

Mark Laurence

Founder and lead consultant at generative AI consultancy Ten Past Tomorrow.

NZTE Private August 2026 Cohort

October 2026 Cohort

“We're going to get to AI systems that are better than almost all humans at almost all tasks... That's the thing I think we're quite likely to get in the next two or three years." - Dario Amodei (CEO, Anthropic. However… ”Only 8% of employees reported they feel GenAI is already transforming their organisation.” - Deloitte - State of Generative AI in the Enterprise report, Q4 2025. Quite frankly, the gap between AI advancement and AI adoption that those two stats speak to is just too large. It’s no longer just a gap. It’s a chasm. And add to that… “In organisations where AI is openly embraced, the chance of developing 'AI Experts' and 'AI Practitioners' is halved when direct managers discourage its use, either directly or indirectly.” - Section School - The AI Proficiency Report. Merging those three storylines and you get a headline that says that senior leadership is the bridge that connects AI aspirations to organisational reality, and ultimately the trajectory of its integration at every level. In other words; true organisation-wide AI adoption doesn’t begin with technology or tools. It begins with leadership. AI literate and AI skilled senior leadership.

Close the AI capability gap: Exec-level training for senior leadership teams

Master AI prompting fundamentals

Evaluate and select AI tools strategically

Discover how to truly scale AI usage throughout your business

Develop a 5-step AI transformation roadmap

Lead AI change management

Implement AI governance and privacy practices

Senior leadership teams wanting to collectively, confidently, knowledgeably, skilfully and ethically lead an AI-forward company.

SLT teams who sense AI is far more than a technical challenge, that it demands leaders step forward to lead comprehensive strategic change.

Leadership teams excited by making a genuine commitment to fundamentally reshape their people, processes and businesses.

Build the core systems yourself. Diagnose failures, make tradeoffs, and develop engineering judgment that outlasts today’s frameworks.

Author of the Common-Sense Guide Series

Jay Wengrow

Author of A Common-Sense Guide to AI Engineering, Software Engineer and Educator

Cohort 2

Cohort 3

It's easy to build an impressive LLM demo.It's much harder to understand why it works, why it sometimes fails, and what to change when it does.That's the problem with learning AI engineering primarily through frameworks and tutorials. You can get something running quickly without developing a clear picture of what's happening underneath.In AI engineering, that missing intuition matters.Become the kind of software engineer who can look at any LLM-powered system and reason about it: What should the model handle? What context does it need? Why is it hallucinating? How should we evaluate it? When does it need tools? Should this even be an agent? How do we trade off quality, latency, and cost?We'll start with a simple LLM call and progressively construct the systems around it. You'll see every important piece come together in real code while developing a practical mental model for how LLM applications behave.Taught by Jay Wengrow, software engineer, educator, and author of A Common-Sense Guide to AI Engineering and the Common-Sense Guide to Data Structures and Algorithms series.By the end, you won't just know how to build an AI application.You'll understand what you're building.

Stop learning AI frameworks. Learn how AI engineering actually works.

Build LLM systems you can reason about

Steer LLM behavior with context, not prompt guesswork

Build RAG by understanding retrieval from the inside out

Use evals to replace vibes with evidence

Build agents by assembling the loop yourself

Make tradeoffs like an AI engineer

This course is designed for current software engineers who will use Python  to build LLM-powered apps. We won't teach basic coding here.

Software Engineering

We'll be using Python, but we'll keep it simple in case you're more familiar with other coding languages.

Note about Python

This course is designed primarily for software engineers who can already code but are new to AI engineering.

Our Leadership, Strategy, and Innovation approaches are no longer working!

Future of Work Researcher | TEDx Speaker

Dr Mansoor Soomro

Future of Work- Researcher | Thought Leader | Speaker | Writer | Futurist

Cohort 8

Cohort 9

I must admit that AI-powered tools have fundamentally transformed the way we work- and should Lead, Strategize and Innovate (LSI).Traditional frameworks and approaches to leadership, strategy, and innovation are no longer sufficient. The rise of AI demands a rethink, a redefinition of how we lead teams, craft strategies, and drive innovation in a rapidly evolving business landscape.This power-packed 1-day course is designed to guide busy executives through this transformational shift. You’ll explore how AI reshapes leaders' decision-making, strategy design, and innovation processes while learning how to align these changes with your organization’s goals.This course is thoughtfully designed into 4 modules, delivered through 4 live sessions.The course ends with a hands-on implementation project (AI-driven Leadership, Strategy and Innovation Plan) giving you a chance to apply your learnings immediately.

AI is shaking things up! Our existing approach to leadership, strategy, and innovation might not cut it anymore.

Module 1: AI and its Business Implications

Module 2: Redefining Leadership in the Age of AI

Module 3: Strategic Thinking and Decision-Making in the AI Era

Module 4: Driving Innovation with AI

C-suite Executives and Senior Leaders looking to navigate the opportunities and challenges AI brings to their organizations.

Mid-Level Managers aiming to future-proof their leadership skills and drive impactful strategies in an AI-driven world.

Business Innovators and Strategists eager to leverage AI for breakthrough innovation and competitive advantage.

Your agents are already acting. Govern what they do, who is accountable, and how to prove it when something goes wrong.

AI Governance Advisor | Founder, INTLDA

Pfizer

Accenture

Cornell University

S&P Global

Uvika Sharma

Founder, INTLDA | AI Strategist, Governance Advisor | Educator | Keynote Speaker

AI Governance Auditor | AIGP | ISO 42001

Deloitte

Wells Fargo

Evan Benjamin

AI Governance Advisor, INTLDA | AIGP | ISO 42001 Auditor | Algorithmic Auditor

Cohort 1

Build the governance system your organization needs before your next board meeting, your next regulator, or your next incident.AI agents are not coming. They are already inside your organization, making decisions about customers, vendors, employees, and compliance without a human in the loop.Most leaders know this. What they do not have is a governance system built for it. The frameworks organizations rely on were designed for AI that assists. Agentic AI acts. That is a different problem, and it needs a different answer.This course is that answer.Over four weeks, you will work through GUIDED, INTLDA's proprietary framework for governing agentic AI. Six actions. One governance system. Built by you, for your organization, during the course. You will not leave with a certificate and a folder of notes. You will leave with six governance artifacts you can use the week after each session ends.Learn from trusted advisors Uvika Sharma and Evan Benjamin. Together they teach governance as a practice, not a subject. What you build in this course is the beginning of a real governance program, not a hypothetical.

Your AI agents are already acting. Nobody defined what they are allowed to do.

Know what agents are running right now

Define what each agent can and cannot do

Name who is accountable for agent harm

Build an audit trail regulators can read

Build your 90-day governance roadmap

Executives and senior leaders responsible for AI in their organization who need governance that works, not a policy that sits in a drawer

Chief AI, data, and risk officers building enterprise governance programs who need a framework built for agents, not just AI tools.

GCs and compliance officers who need to know what their agents can do, who owns the risk, and how to prove it to a regulator.

Agentic AI

Coding with AI

AI Workflows

Claude Code

OpenClaw

Vibe Coding

AI Evals

AI Transformation

RAG & Search

AI for PMs

AI for Engineers

AI for Designers

AI for Marketers

AI for Founders

Product Sense

Product Discovery

User Research

Prototyping

Growth

Analytics

Tech Foundations

Strategy

Influence

Leadership

Career Growth

Machine Learning

LLM Ops

Context Eng

Security

System Design

Figma

Design Systems

Visual Design

Design Strategy

Automation

Content Marketing

Demand Gen

Product Marketing

Positioning

Social Media

Brand

B2B Marketing

SEO & AEO

AI for Leaders

AI Governance

Communication

Management

People Operations

Exec Presence

Storytelling

Goal-setting

Personal Brand

AI for GTM

Sales

Customer Success

GTM Engineering

Everyone

Founders

Operators

Data Scientists

Business Analysts

User Researchers

Project Managers

HR Professionals

Sales People

Lawyers

Finance

Investors

Real Estate

Educators

Creators

Introduction to Edward Kennedy and the Talk on Guidance Beyond Language

The Shift Towards Multi-Model Workflows and the Spiritual Body Project

Word Parsing in Image vs Language Models and the Limits of Language

Exploring Latent Space and Emergent Properties in AI Models

DSCI Embeddings: Fine-Tuning, LoRAs, and Textual Inversion in Image Models

Bypassing Vision Language Models for Direct Diffusion Transformer Input

Visual Results of DSCI Embeddings: 80s/90s Airbrush and Abstract Concepts

Autoregressive LLMs, the Rational Mind, and the Concept of Papanca

Diffusion LLMs and Resonant Embedding Guidance (REG) for Creative Writing

The Efficiency and Advantages of Embeddings Over LoRAs

Defining Life, Consciousness, and Self-Guiding AI Models

Real-Time AI Video Generation and Future Applications of Embeddings

Engineers and engineering leaders who build, deploy, and scale software systems.

Data scientists who apply statistical and ML techniques to extract insights from data.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Building, training, and deploying machine learning models — from classical ML to deep learning.

Building retrieval-augmented generation and search systems — vector databases, embeddings, ranking, and retrieval pipelines.