cleopatra douglas

Build Fintech AI Systems That Actually Ship

Goldman Sachs

Flutterwave

GUARANTY Trust Bank

Cleopatra Douglas

CEO & Co-Founder, Recital Finance | ex @ Goldman Sachs, Flutterwave (YC Unicorn)

Identify the 3 architectural mistakes that kill fintech AI projects, and the decision patterns that prevent them.

Why fintech AI projects fail before production

You'll see a real reconciliation agent in action and understand how to structure autonomous workflows around messy data

How to design an agentic workflow for financial data

Leave with a checklist covering observability, ML lifecycle, and the guardrails that separate demos from shipped systems

The production checklist nobody teaches you

Ship production features 2x faster by using coding agents across research, planning, implementation, testing, and review workflows

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Creator of Stanford's AI Coding Course

Amazon

Stanford University

Y Combinator

Mihail Eric

Created Stanford's first AI coding class. Former YC founder and Amazon AI lead. 

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Today many developers use AI, but few are maximally productive with it. I created Stanford's first AI software development class, and after building a YC-backed coding company and leading AI at Amazon, I've seen how top engineers integrate AI into production workflows. My techniques have been used to train 200+ Stanford engineers and industry professionals.My goal is simple: make you dramatically more productive writing software with AI than without it.In this course, you'll learn practical, end-to-end workflows for using AI in real-world development, not toy examples.We'll cover:<ul><li>Building production features with AI agents using the research → plan → implement → test workflow</li><li>Configuring an optimal AI native dev environment for your specific tech stack (IDE, code review, tool integrations, and beyond)</li><li>Setting up review and CI processes that catch AI errors, hallucinations, and slop before production</li><li>Enabling multiple agents to work together on the same codebase without conflict, accelerating software delivery and throughput</li></ul>If you're ready to write better code, ship to production faster, and stay in control of your coding agents, let's get started.

Increase developer productivity with AI-first, production-ready workflows

Configure optimal AI-first developer environments to improve your coding output

Learn how to navigate the ecosystem of cutting-edge AI developer tools 

Exercise effective strategies for prompting and building with coding agents

Reduce hallucinations, software errors, and AI slop all while shipping faster

Become a manager of coding agents so you can keep many agents productive 

Develop a deep intuition for how AI coding platforms work under-the-hood

Engineers who want to increase their productivity with AI-generated code while making it actually production grade.

Engineering managers who want to ensure their teams aren't being left behind when it comes to the new way of developing software.

Those confused about how to develop with AI the right way (how to maintain context and manage multiple agents without compromising code)

Build autonomous AI agents that use tools, manage payments, and run independently—turning you into a product-builder, not just an AI user.

Founder & AI Instructor at School of AI

Vivian Aranha

AI architect with 2.2M+ learners, building enterprise-grade agentic systems

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This course is completely asynchronous and available to view at your own convenience. There will be no Live sessions.Most AI professionals today can build demos — but very few can turn AI into something that operates, earns, and scales on its own. That gap is becoming a career ceiling.As companies move from copilots to autonomous agents, the real challenge is no longer prompting models — it’s designing AI systems that can use tools, remember context, make decisions, handle money, and operate safely without constant human input. This is where most engineers, founders, and product leaders feel stuck.You’ll learn how to go beyond chatbots and scripts and instead build AI agents that behave like digital workers or businesses — agents that can take tasks end-to-end, charge for their work, log decisions, manage risk, and explain why they acted. These are the skills now being demanded in AI engineering roles, startups, and internal innovation teams.If you’ve ever wondered how to turn AI into a real product, a real service, or a real revenue stream — not just a prototype — this course gives you a clear, structured path from zero to a deployable, monetizable autonomous agent.

Where AI Agents Become Revenue-Generating Digital Businesses

Design an AI-Native Business Model

Build Tool-Using Autonomous Agents

Implement Memory & Multi-Step Planning

Enable Payments & Revenue Simulation

Add Governance, Risk & Auditability

Launch a Production-Ready Capstone

AI Engineers &amp; Developers Builders who can prototype with LLMs but want to create autonomous, revenue-generating AI systems.

Tech Founders &amp; Product Leaders Entrepreneurs exploring AI-native business models and agent-based products beyond SaaS.

Automation &amp; Innovation Professionals Operators looking to replace workflows with autonomous agents that execute and monetize tasks.

Future-proof your finance career by mastering AI tools, predictive modeling, and autonomous agents that handle real finance workflows.

Professor & AI Expert (510K+ Students)

General Motors

Samsung

HSBC

Barclays

Stellantis

Dr. Ryan Ahmed

Professor, AI expert, & YouTuber who has taught 500,000+ learners worldwide.

AI Agents are rapidly transforming how business and finance teams operate. 6 months ago, building a DCF financial model took a junior analyst ~1 day. Today, a team of autonomous AI agents builds, audits, reports, and presents it in 10 minutes.Organizations are moving beyond spreadsheets and manual workflows toward AI-native systems, where intelligent agents analyze data, generate reports, and automate complex tasks.The problem: Most professionals still use AI for basic Q&amp;A and drafting emails; they lack the skills to build AI agents that execute real business and finance tasks autonomously.The solution: This bootcamp teaches you to build intelligent agents that reason, use tools, access data, and complete multi-step workflows automatically using Claude Code, Claude Cowork, and Copilot agents.What makes this bootcamp unique?<ul><li>AI Agent Workflows: Automate research, reporting, and operational tasks</li><li>Build AI Agents: Connect agents to financial data and generate insights, no coding required to start</li><li>Predictive Analytics: Use ML agents for forecasting, classification, and risk scoring</li><li>Autonomous Agent Teams: Deploy teams of agents that collaborate and improve continuously</li></ul>

Build AI Agents That Automate Business & Finance Workflows & Get Certified

Automate Business & Finance Workflows with AI Agents

Build Predictive Financial Models with AI Agents

Connect Agents to Financial Data with MCP

Build & Deploy Autonomous Finance Agent Teams

Master Agent Architectures & Guardrails

Capstone: Deploy an End-to-End Agent System

Finance Professionals &amp; Analysts wanting to automate workflows, build predictive models, and deploy AI agents for reporting and forecasting.

CFOs, Controllers &amp; Finance Managers who want to lead AI adoption and deploy autonomous agents for reconciliation and decision support.

Data-Savvy Accountants &amp; FP&amp;A Teams who want to move from manual spreadsheets to AI-powered workflows that analyze and forecast at scale.

Learn to design, build & deploy real AI systems—become a portfolio-ready AI builder, not just a prompt user.

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Most AI courses teach you prompts. This course teaches you how to build real AI systems.Right now, professionals face a critical challenge: AI is everywhere — but very few people know how to turn it into working, deployable applications. Watching demos isn’t enough. Copy-pasting prompts isn’t enough. Employers and clients want people who can design, build, evaluate, and deploy AI-powered solutions that actually solve problems.If you’ve felt overwhelmed by the noise — new tools every week, agent frameworks, RAG, automation — you’re not alone. The real gap isn’t intelligence. It’s structure.This course matters because it gives you a complete, end-to-end mental model of modern AI systems. In 14 days, you move from understanding how AI works to deploying your own AI-powered application with memory, tools, automation, and evaluation.By the end, you won’t just “know AI.” You’ll have built and shipped a real product — and that changes your confidence, credibility, and career trajectory.

Build Real AI Systems & Agents in 14 Days — Not Just Prompts

Build End-to-End AI Systems

Work Confidently with LLM APIs

Engineer Reliable Prompts & Outputs

Implement RAG & AI Memory

Build Task-Executing AI Agents

Deploy & Present Portfolio Projects

Aspiring AI builders who want real projects, not just prompt tricks, and need a structured path to ship their first AI app.

Developers or engineers curious about AI who want to add LLMs, agents, and automation to their existing skill set.

Product managers &amp; tech professionals who want to understand AI systems deeply enough to build, deploy, and lead AI initiatives.