Sean Thielen-Esparza is a creative technologist at Complex, where he builds AI-powered tools that reshape how stories are created and shared. His work bridges product, design, and engineering — exploring how emerging technology like generative AI can be made more useful for creative people. Previously, Sean was a venture-backed startup founder and ML product manager. Outside of work, Sean runs a patronage syndicate, giving no-strings-attached grants, studio space, and exhibition opportunities to artists around the world.
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I've spent 15+ years at the intersection of AI, software, and hardware:
Here's what I learned:
You don't need a PhD to build software anymore. You don't need to be trapped by Bubble or Zapier limits. You just need the right System Prompt. In this Lightning Lesson, I'll show you Pattern #1—the exact \"Agentic AI Workflow\" behind all 16 products. My mission: Help working professionals become AI Builders without quitting their job or hiring a CTO. For founders and enterprise leaders, I also maintain a private Inner Circle for 1:1 implementation, but this Lightning Lesson is the exact starting point I recommend for everyone.
Why trust me?
I've been on every side of AI:
Beyond AI coding, I’m using these same agentic coding patterns to build a memory-first personal AI agent OS – a system that turns daily data into long-term, reusable intelligence.
This Lightning Lesson gives you the core workflow behind both: how to drive Cursor like a Senior Engineer, even if you've never written React before. You’ll be able to plug this workflow into your own idea immediately.
I'll show you the shortcut. See you in the session.
Important Notes
🚀 Serious about shipping?
This 30-minute session is a high-speed overview. If you are already looking for a structured 3-week build sprint or private implementation help, check the Go Deeper Link to secure a seat in the next cohort before the price jump.
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Eleanor Berger is an AI expert and technology leader with a track record of advising, building and leading high-performing AI engineering teams at Microsoft, Google and several start-ups.
At Microsoft and Google, Eleanor enabled top cloud customers, including startups, software vendors, and enterprises, to deliver impactful AI-first solutions. She has served in key advisory roles with a focus on applied AI and is recognised as a leading voice in the industry.
Today, Eleanor advises companies and empowers catalysts — leaders who drive AI innovation — by pairing deep technical expertise with hard-won managerial insight. Eleanor helps organisations build robust AI capability, integrate advanced AI and deliver powerful solutions that drive business value and strategic advantage.
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If you're ready to write better code, ship to production faster, and stay in control of your coding agents, let's get started.
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Have Built Requirements Practices for dozens of organizations
Co-Author of Futureproof: Amplifying Agility with AI and Insightful Analysis (Book about AI and BA)
Lead Author Team on IIBA BABOK v3
LinkedIn Learning Instructor
AI risk often comes from poor assumptions about what AI can and cannot do. It also comes from poor analysis and organizational dynamics of leaders asking for solutions and pressuring teams to deliver solutions rather than solving real problems.
Analysis professionals have a huge role in this dynamic that can change everything!
Analysts are increasingly expected to participate in AI decisions, yet most training focuses on tools or stays abstract. This course fills the gap in understanding AI capabilities: Not from a technical point of view, rather a capability point of view; business uses and patterns of functional usage.
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🎯 Identifying the right AI use cases for specific business scenarios
🎯 Distinguishing between deterministic and probabilistic systems and deciding where each should be applied in a workflow
🎯 Questioning and communicating AI use case fit and risks—and defining clear hypotheses for AI solutions
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For as long as I can remember, product designers have been pushed away from code. Most designers settled this question for themselves long ago—code is not for me. Now is a great time to reconsider that decision. You can have a relationship with what feels like real work without spending years mastering syntactical minutiae.
Working on a design with code is an act of shaping: you’re shaping something out of the raw materials yourself. And as you shape it, you can actually interact with it, get the feel of it. This means you can work on a user interface the way it really works.
As designers, we enjoy making things. Working with code is a fantastic opportunity to feel connected to the thing you’re making.
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Every professional has access to ChatGPT, Claude, Gemini. But access isn't advantage.
The professionals who will thrive operate AI as a system. They build tools that compound. They create digital extensions of themselves that work continuously, not just when prompted.
Right now, a small group of practitioners has made this shift. They're working with AI systems that remember, maintain context, and automate entire workflows. While others type prompts into ChatGPT, they've built personal AI operations that multiply their output.
This course closes that gap in two sessions.
You won't learn prompting techniques. You'll build a working AI system, trained in your voice, solving your actual workflows during the live sessions. Not someday. Now.
By the end of this course, you'll wonder how you ever worked without it.
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