Everyday AI

AI Landscape

Shawn Boehm

CEO & Founder: Everyday - AI

Understand the major AI companies, their flagship models, and which platforms serve different needs.

Navigate the Complex AI Ecosystem with Confidence

Discover the critical decisions you need to make before adopting AI: data privacy consideration &  AI capabilities

Make Informed Choices About AI Tools for Your Needs

Learn how AI models (like GPT-4, Claude, Llama) relate to productivity platforms (like Perplexity, Venice.ai, ChatGPT).

Understand the AI Model Hierarchy and Platform Layers

The Problem: Scaling organizational expertise with generative AI&nbsp;captures the basics but misses the distinctive thinking patterns and cultural fingerprint that differentiate your organization. The Solution: Capture, automate and reimagine your distinctive methodology with agentic systems using frameworks emerging from years of strategic consulting and building AI tools for Fortune 500 companies and think tanks. We provide the strategic insight and hands-on capabilities to integrate generative AI strategically—in a way that preserves your competitive advantage while unlocking new dimensions of interactivity and personalization. Effective AI integration requires new collaboration frameworks between domain experts and technical teams — we teach you how to bridge this gap so expert knowledge translates into reliable, personalized AI outputs. You will master the frameworks we have been applying for half a decade for global consultancies and companies, walking away with a repeatable blueprint for scaling generative AI across the enterprise. Atop the theoretical bedrock, we bring heavy focus on hands-on practice doing unglamorous but essential work for mastering generative tool deployment: data plumbing, iterative evaluation and stress-testing, collaborative prompt design and de-risking roll-outs through phased deployment. This is not just a course. This is a commitment of experts with a decade of combined experience to transform your workflows and multiply your organization's output.- Unlimited one-on-one consultation opportunities during the course- Proprietary chatbots trained on the learning content- A resource hub 3 years in the making- Takeaway: The extent of your learning is bordered only by the time you are willing to commit.

Transform Your Organization's Expertise Into AI-Powered Competitive Advantage

Course syllabus

Synchronous zoom lecture on Tuesday, focusing on the conceptual backbone of AI agent functionality and applications. Recordings of class will be available soon after its completion.

Tuesday

An async walkthrough will guide you in building functional prototypes of AI Agents. You will get to shape the project deliverable. Lecturers will be available by email, during office hours and via one-on-one sessions throughout the week for questions and support.

Weekly projects (async)

Optional office hours where you can ask questions and receive personal guidance on developing your AI applications.

Tuesday & Thursday

Schedule 1:1 coaching time with instructors for individualized help with your hands-on projects, privately thinking through a use-case, or whatever else you need.

1:1 Coaching

Course schedule

Executive Leaders who need to scale organizational capabilities with AI while preserving competitive differentiation

Project/Product Managers leading cross-functional AI integration initiatives bridging domain expertise with technical implementation

Domain Specialists who want to enhance their analytical workflow through custom AI applications without having to code

Who is this course for

What you’ll get out of this course

Master the end-to-end methodology from initial requirements to production launch, including risk assessment, phased implementation, and organizational adoption strategies that minimize disruption while maximizing competitive advantage

Strategic AI Integration Frameworks

Transform unstructured institutional knowledge like meeting transcripts, reports, and backlogs into agentic systems that prevent your expertise from walking out the door with the next turnover

Culture Capture From Unstructured Data

Design and implement human-in-the-loop evaluation systems and testing methodologies that ensure trust, relevance, and reliability

Quality Assurance and Evaluation Frameworks

Navigate technical tradeoffs across compliance, latency, and cost vectors while managing non-technical stakeholders through AI development cycles and scope definition

Strategic Decision-Making and Project Management

Update your awareness with strategic foresight and thorough ecosystem analysis of AI affordances in specific industries, domains and modalities, enabling informed investment decisions and long-term positioning

AI Ecosystem Intelligence and Future Planning

Automate and amplify institutional knowledge through AI agents that embody your cultural DNA

Lev Gorelov

Jeremy Kirshbaum

Cohort 15

Cohort 16

Your team wants direction, leadership wants you to deliver more with less (and AI) - all while the AI tech stack changes every week. When you're not-technical and don't have the time to become technical, this becomes an insane challenge to overcome.&nbsp; It's also the challenge that I had to solve for myself. At Accenture, I went from being a non-technical leader to securing $2M in funding for AI initiatives (which ended up generating $300M in value). Then I helped build the AI strategies that drove productivity improvements for over 14,000 consultants. Today, I advise both tech startups and Fortune 1000 companies on becoming AI-native organizations. What you need is the time and space to learn by doing. I'll show you how to pick the right problems to solve with AI (and that will get you kudos from your bosses) and we will collectively build AI solutions together, live. Plus you'll walk away with frameworks and cheat sheets so that you can do it again and again -- and teach your team how to do it. Walk away not just with a working AI experiment, but with the skills and frameworks to become the go-to AI leader in your org. This cohort isn’t “AI 101.” It’s applied enterprise-grade learning for leaders who want to be ahead of the curve, not catching up to it. Unlike broad "AI for Leaders" courses that just cover definitions, this live lunch-time cohort is hands-on -- you'll pick your top use cases, calculate ROI, decide on the tech stack, and try your hand at automating some of your own workload. WHAT TO EXPECT:Format: four live, lunch-time sessions across two weeksSupport: two optional interactive office hours for hands-on helpPrep: bite-sized, zero fluff—show up, apply, move onOutcome: identify high-impact AI use-cases, craft an executable plan, and become the AI-native voice in your org (or for your clients) WHAT WE'LL COVER:- Pinpoint problems that are truly AI-solvable (we’ll choose them live)- Scope projects that become career-making case studies, not budget sinkholes- Speak “just-technical-enough” about GenAI, agents, ML, and automation- Make smart Build • Buy • Vibe-Code calls to save cash and time- See case studies from companies seeing 70%-300% improvements in productivity, marketing, engineering, and product management- Select platforms for low-code / no-code AI automations- Set realistic expectations with leadership and clients- Overcome resistance and build cross-functional buy-in- Avoid the costliest implementation traps- Keep your strategy relevant as the tech leaps forward YOUR REPEATABLE AI PLAYBOOKGain proven frameworks, vendor matrices, and checklists to de-risk projects and win buy-in:1. Build, Buy, Vibe-Code AI Solution Decision Matrix2. AI Vendor Assessment Checklist3. “Why We’re Going AI-Native” Narrative Template4. 7-Point Checklist to Avoid AI Project Failure5. Handpicked list of my personal AI tech stack (the coolest AI products in the market right now) to explore The goal isn't to make you a technical expert - it's to give you the confidence to lead AI initiatives successfully. WHO WILL BENEFIT MOST FROM THIS COURSE: - You're responsible for AI projects but don't have a technical background- You need to make strategic decisions about AI investment- You're leading consulting engagements and clients want coaching on AI- You're bridging the gap between technical teams and business objectives- You want to position yourself as a forward-thinking leader WHO THIS IS NOT FOR: - Developers or AI engineers seeking technical implementation skills- Those expecting to become AI experts overnight- People looking for general "this is what ChatGPT is" courses If you're still not convinced, consider this: The price of this course is a fraction of the cost of a single failed AI project (so you should ask if your company will pay for this). And even if they won't, this is a small investment towards making your career future-proof.

Expectations have never been higher...

Use your lunch hour for the most impactful activity you could have on your plate -- future-proofing your career.

Wednesdays & Fridays Live Sessions

Open Office Hours for any questions and deep dives.

Thursday AMA Office Hours

Team leads, directors, and department heads who have been "volun-told" to implement AI and need to show a plan, quickly.

AI consultants who need structured frameworks to help clients decide on AI use cases, execution, and ROI.

Execs, founders, and business owners who need to set the AI strategy for their org and can't afford to make costly mistakes

Who should take this course

Companies are already seeing huge results...HubSpot improved email performance by 70%, Gumroad increased feature releases by 300%. Don't reinvent the wheel. Learn directly from real, behind-the-scenes case studies - and leave with a tangible plan for your team.

Leapfrog to picking 2-3 of the most impactful AI use cases based on what top AI leaders are doing

Decision fatigue is real -- and not all use cases need to be custom-built (and who has engineering resources for that, anyway). You'll be able to confidently decide how you should implement each use case to maximize speed to value. We'll apply this framework together in real time

Steal my framework for quickly deciding whether to Build, Buy, or "Vibe Code" AI solutions

Learn how to prompt AI agents like a boss, pick the right platform (Zapier, Make, ChatGPT, N8N), and start to automate your own work so you can deliver 10x more value.

Vibe code your AI "quick wins" live

74% of companies are struggling to see value beyond an AI proof of concept. We'll cover what makes a good AI deployment (to AI agent or not to AI agent) so your efforts stay relevant and scale over time. We'll analyze real situations from within the cohort.

Deconstruct the best practices and top mistakes companies make when deploying AI internally

AI tech isn't even the hardest part -- AI leaders are putting 80% of their effort into aligning people and processes. You'll leave with a clear, actionable roadmap to transform your team into an AI-Native powerhouse.

Create your own "Why We're Going AI Native" narrative to gain buy-in from your team

Walk away with a working AI experiment built on your own business problem — and the skills to become the go-to AI leader in your org.

Lauren Vriens

Cohort 1

Cohort 2

Build clarity, alignment, and the strategic direction needed to enable enterprise AI.AI is reshaping how businesses operate. Decision-making is becoming more data-driven. Automation is changing how work gets done. Cloud costs and value tracking are now leadership priorities. Security and compliance risks are evolving. To compete, organizations need to move beyond experimentation and establish clear, actionable AI strategies. If your teams are navigating these shifts without a cohesive plan, you are not alone. Many organizations have strong capabilities but lack a structured approach to AI readiness. This course gives you that path. Built on the proven 10 Dimensions of Enterprise AI Readiness, this program helps leaders assess where their organization stands, align teams around the right priorities, and develop a practical strategy for enabling enterprise AI. What You’ll Get From This Course ⦿&nbsp;A clear understanding of how AI is reshaping Business ITLearn how AI, automation, cloud, security, and data are driving change across operations, strategy, and leadership expectations. ⦿&nbsp;An actionable AI readiness assessment frameworkUse the 10 Dimensions of Enterprise AI Readiness to assess strengths, gaps, and opportunities across the organization. ⦿&nbsp;Alignment on strategic prioritiesFacilitate conversations that help leadership teams identify the right focus areas and build consensus on where to invest in AI enablement. ⦿&nbsp;A practical path from AI trends to business outcomesTranslate current AI trends into initiatives that drive measurable value and support business goals. ⦿&nbsp;Cross-functional collaboration and leadershipStrengthen alignment between IT, data, finance, security, and business leaders to support enterprise-wide readiness and strategy execution. Learn with a Supportive Community This is not lecture-based learning. It is hands-on, discussion-driven, and outcome-focused. You will work alongside peers from across industries who are also leading AI readiness efforts, sharing insights, building alignment skills, and shaping strategic action. By the end of this course, you will be equipped to assess your organization's AI readiness, align leadership around strategic priorities, and build a clear, actionable path to enable enterprise AI.

Future-Proof Your Organization with AI Readiness for Organizations


Join interactive, instructor-led sessions where we break down key concepts, discuss real-world applications, and work through challenges together. Expect a mix of guided learning, open Q&amp;A, and hands-on exercises to help you apply what you’ve learned.

Instructor-Led Live Sessions


Drop in for live office hours to get personalized guidance, ask questions, and connect with peers.

Open Office Hours


Apply what you learn through hands-on projects, case studies, and skill-building exercises designed to help you gain confidence and real-world experience.

Weekly projects

Get lifetime access to all future course material updates, including workshop templates and slides. Stay current, even as Business continues to evolve in the years to come.

Updated Course Materials


Join the class Discord server for continued access to instructors and community members, even after the class has ended.

Join the Community


Business and IT leaders seeking to align teams and drive a clear, actionable AI strategy that delivers results

Internal consultants and change agents working to assess organizational AI readiness and guide strategic priorities

Cross-functional leaders in roles spanning IT, data, finance, security, or operations who are shaping enterprise AI initiatives

Gain clear, practical insights into how these forces are impacting operations, decision-making, and competitive positioning across the business.

Understand how AI, automation, cloud, security, and data are reshaping Business IT

Learn to run structured readiness assessments that reveal strengths, gaps, and opportunities across teams, systems, and practices.

Assess organizational readiness using the 10 Dimensions of Enterprise AI Readiness

Use proven facilitation approaches to help leaders and teams build consensus on where to focus and how to sequence AI enablement efforts.

Align leadership and teams around clear priorities

Apply real-world examples and case studies to identify where AI can drive measurable business value, efficiency, and innovation.

Translate AI trends into actionable business outcomes

Strengthen coordination between IT, finance, security, data, and business functions to support enterprise-wide AI readiness and strategy execution.

Build cross-functional alignment and collaboration

AI Readiness for Organizations helps leaders align teams, set priorities, and build a clear, actionable strategy for enabling enterprise AI.


September Start

John Tanner

Founder & Chief Strategist @ C4G Enterprises Inc.

August Start

November Start

But most teams are still designing like it’s 2015. AI is transforming industries and changing the very foundation of how products work. Companies are moving fast to integrate large language models, agents, and adaptive systems into their products. But as model complexity grows, the user experience often gets left behind. Powerful algorithms can now predict, generate, and decide but without thoughtful design, they often confuse users, introduce risk, or fail to earn trust. The challenge? Designing for AI isn’t like designing for traditional software. It’s not just about usability or polish anymore. It’s about system behavior, adaptation, and collaboration between humans and machines. If you’ve ever launched an AI feature only to see users abandon it because they didn’t understand what it was doing or if you’ve been asked to “design the AI experience” but weren’t sure where to begin → this course is for you. The Role of the Designer Is ChangingUntil recently, designers focused on interfaces and flows. Today, the frontier is different. OpenAI recently posted a job for a Model Designer, a new kind of design role focused on shaping how models behave. And it signals a broader shift across the industry: Designers aren’t just styling outputs anymore. They’re architecting how intelligent systems learn, adapt, and interact. In AI-powered products, design happens upstream, at the level of:- Data inputs and how users shape them- Model decisions and how they’re surfaced or corrected- Feedback loops that guide learning- System behavior that evolves over time To adapt to this new environment, designers must understand how models work, not to become ML engineers, but to ensure what the system learns, shows, or hides aligns with human expectations and values. Real Challenges This Course Prepares You For You launch an AI-powered feature and maybe it recommends content, summarizes input, or automates a task. But users are confused or drop off quickly. They can’t tell why the AI did what it did, or how to influence it. The model works, technically. The experience doesn’t.→ Learn to design transparency, feedback, and control into intelligent systems before trust is broken. Your CTO asks you to “design the AI experience.” There’s no interface yet, just a prototype from the ML team and a prompt to “make it usable.” You’re left staring at system outputs, unclear where to start, or how much of the system behavior is even within your control.→ Gain the tools and frameworks to work upstream, shaping behavior, not just UI. You’re in a meeting where the team is debating whether to launch a model with 72% accuracy. Product wants speed. ML is confident the model will improve post-launch. But no one’s talking about the UX cost of being wrong nearly 1 in 3 times or how the system will recover from those mistakes.→ Learn how to design for failure, uncertainty, and system correction from day one. A personalization feature goes live. But user feedback is harsh: “This feels random.” You realize the issue wasn’t the model, it was the lack of communication and guidance. There’s no explanation, no context, and no way for users to improve the output.→ Understand how to design model feedback loops and trust-building interactions. You inherit a half-built AI assistant. It occasionally interrupts users at the wrong time, answers inconsistently, and disappears when needed most. The UI looks fine but the behavior feels off. You realize this isn’t a layout problem, it’s a systems design problem.→ Move from UI design to shaping system behavior, flows, and agent logic. You will bring your own real-life project scenarios, and we’ll coach you through how to solve them—using frameworks, feedback, and hands-on critiques.

The AI Tech Revolution Is Redefining Design

Class will meet once a week for live lectures and project discussions.

Weekly Live Sessions

Plan to work on a capstone project to apply your learning to a capstone project

Weekly assignments

Get weekly 1-1 office hours for personalized feedback on your capstone project

1-1 Coaching 

Senior UX &amp; Product Designers: Deepen your systems thinking skills and learn to design around model behavior

Design Leads &amp; Heads of UX: Guide teams, shape AI product strategy, and lead with system-level thinking and trust design.

AI-Aware PMs &amp; Researchers: Collaborate better with design, align model goals with UX, and support ethical, adaptive systems.

Learn how to speak the language of models, data pipelines, and evaluation metrics—so you can contribute meaningfully from early scoping to final delivery. You’ll practice framing use cases, defining handoffs, and aligning design with system capabilities.

Collaborate effectively with ML and Product teams

Instead of just designing around the model, you’ll explore how interaction design can shape what the model learns, retains, or ignores. You’ll build UX patterns that create useful training signals, structured inputs, and adaptive guidance.

Shape model behavior through smart UX architecture

You’ll create flows that help users understand, question, or override the model’s decisions—like confidence indicators, correction mechanisms, and recovery paths for failure scenarios.

Design interactions that support user trust, control, and adaptation

Learn to design feedback loops where user actions (like corrections, inputs, skips, or feedback) help the model adapt. You’ll map those flows and create testable patterns that help close the loop between model performance and user value.

Build systems that improve over time—with users in the loop

Whether you’re dealing with ranking systems, generation models, or multi-step agents—you’ll practice mapping decision logic, designing trust dashboards, and identifying failure points. You’ll learn how to advocate for UX in model evaluation and behavior design conversations.

Lightning Lessons

AI Landscape