CT Academy

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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.

NZTE Private August 2026 Cohort

September 2026 Cohort

AI Strategist // Trainer // Futurist

Mark Laurence

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

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.

You will walk into any AI conversation able to read the proposal, ask the questions that matter, and shape the decision in your own voice.

AI Transformation Leader & Educator

Deloitte

University of Exeter

Lloyds Bank

Deidré Luzmore

Founder of Your AI Journey

Cohort 1

LIMITED SEATS! (Use code: earlybird for $500 off ) ♾️ A free seat in every future cohort, for life🏫 AI Leadership community included.📚 24 lessons across 8 modules. 16 hours live with Deidré.🧰 3 artefacts you build on your own AI proposal and take to work✉️ Private team training available: info [@] youraijourney.comYou are sitting in another meeting about AI. A vendor is presenting, a technical colleague is nodding, and someone says the word agentic. You have twenty years of experience in your field, and right now none of it feels like it counts.What you have to contribute still counts. You are not behind. Yours is the missing voice in the room. This course is for the leader who has to live with AI decisions made by other people. It teaches you to spot weak AI thinking before it becomes weak AI rollout, ask the questions others miss, and shape the decision from your own seat without being labelled obstructionist.Over eight weeks you build a framework for thinking, practise it on a realistic case study, then apply it to a real AI proposal in your own organisation. You leave able to shape the decisions you used to absorb.

The non-technical leader is the missing voice in nearly every AI decision.

Speak the language of AI without bluffing

Read any AI proposal and form a defensible position

Choose the right intervention with the Five Routes framework

Ask the questions that stop weak AI rollouts

Define where humans stay in the loop, and design safe pilots

Lead the adoption conversation on your home turf

<pre><code class="language-markdown">The People &amp; Culture leader- You lead HR, People or Internal Communications. You have been asked to represent the workforce in AI decisions.</code></pre>

<pre><code class="language-markdown">The Finance, Risk or Legal leader signing off the exposure- You lead Finance, Risk, Compliance, Legal or Internal Audit.</code></pre>

<pre><code class="language-markdown">The Operations, Marketing or CX leader living with the AI tools you never asked for- You lead Operations, Marketing or Customer Experience.</code></pre>

Your team adopted AI. Why hasn’t delivery improved?

Staff Software Engineer

Luis Vieira

Staff engineer

Agentic Engineering 1

<blockquote>AI coding tools make implementation faster. But typing code is only one part of getting software safely from idea to production.Teams still need to turn ambiguous requests into clear plans, understand how changes affect an existing system, verify that they are safe, and make sound decisions about what reaches production.When code becomes cheap to produce, context, judgment, and verification become the limiting factors.This is why faster coding does not automatically mean faster delivery. Improving one part of the workflow has limited impact when the rest of the system continues to create bottlenecks.This workshop gives you a practical method for improving delivery with agents. You’ll learn to find the constraints slowing down your SDLC, design agents that can safely take on bounded work, and improve them over time using proof of work, feedback, and evals.</blockquote>

Learn how to find delivery constraints, design trustworthy agent workflows, and improve them through evidence, feedback, and evals.

Understand the AI coding plateau

Find agent opportunities across the SDLC

Design a trustworthy agent harness

Improve agent workflows over time

Software engineers using AI coding tools looking to improve their team SDLC

Tech leads and engineering managers who want to understand how to increase engineering output using AI

Engineering leaders who adopted AI tools but aren't seeing it in delivery speed or business outcomes and want to understand why and fix it

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

Wells Fargo

Evan Benjamin

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

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

Go-to-Market

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

Fundraising

Everyone

Operators

Data Scientists

Business Analysts

User Researchers

Customer Success

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.

Guidance Beyond Language: Wisdom, Embeddings & LLMs

What you'll learn

Why this topic matters

You'll learn from

CT Academy

Edward Kennedy