Armagan Amcalar

Q&A: Building Real-World Apps With GenAI

Founder of Coyotiv. Fractional CTO. 20+ years building tech teams and platforms.

Get your questions answered on things like contextual prompting, debugging, code co-creation, and output evaluation.

Get an overview of building apps with GenAI

Let's talk about what it *really* takes to launch an app in just four weeks.

What does it take to launch an app?

We'll get into solving real problems for real people + understanding how you can evaluate the usefulness of your ideas.

And what does it take to make something people care about?

We’re living through one of the most transformative periods in the history of computing — and Generative AI is at the heart of it. From content creation and personalized customer support to autonomous decision-making and intelligent search, GenAI is rapidly redefining how businesses operate, how knowledge is accessed, and how software is built. You've likely experienced this firsthand: vendors promising AI solutions that will transform your business overnight, countless products with overlapping capabilities, and the nagging question: "Which of these actually solves our unique problems?" Our startup has worked with organizations across fintech, supply chain, consulting, and manufacturing sectors, and we've consistently encountered the same challenge: businesses know AI matters, but struggle to identify concrete use cases that deliver measurable ROI. This course addresses precisely that gap—helping you cut through the noise to identify, build, and deploy GenAI applications that create actual business value. Building GenAI Agents for Enterprise Use is designed to give you a laser-focused and in-depth view of real-world GenAI applications. Designed for Business Leaders, Not DevelopersWhat sets this course apart is our relentless focus on the "what" rather than just the "how." While many courses dive directly into technical implementation, we prioritize use case identification, business value assessment, and strategic deployment considerations that matter to non-technical leaders. You don't need a programming background to succeed here. For business professionals who want to understand the capabilities without getting lost in the code, we've designed an experience that emphasizes concepts, applications, and outcomes. This course is one of the top-rated Gen AI Course on Maven, with over 1000 professionals trained from companies across tech, finance, government, and healthcare. It has been successfully offered at Stanford Continuing Studies and the UCLA Anderson School of Management for their Master’s in Business Analytics programs. Designed for Executive leaders, Data Scientists, Machine learning engineers, and Product Managers, the course demystifies the Gen AI landscape by blending deep technical concepts with practical enterprise deployment strategies. This is not another LangChain how-to or framework tour. Instead, this course teaches you to build modern GenAI systems from first principles, grounded in real-world constraints like scale, guardrails, multi-agent workflows, and domain-specific adaptation. 👤 Who This Course is For This course is designed for: - Product Managers looking to integrate GenAI into their roadmaps with clarity and confidence - Technical Leaders and Architects who want to build scalable and safe GenAI systems - Startup Founders &amp; Innovation Teams aiming to create competitive GenAI-powered products - Data Scientists &amp; ML Engineers who want to go beyond notebooks and deploy impactful GenAI apps ﻿- Consultants &amp; Enterprise Strategists exploring GenAI adoption and implementation strategies for clientsAnyone who wants to learn how Gen AI can be used 📚 Course ModulesModule 1: The World of Generative AI — Why Leaders Must Understand ItUnderstand the GenAI revolution and what it means for industries, infrastructure, teams, and the future of software. We break down the LLM ecosystem, the commoditization of models, and the real moats: data and architecture. Module 2: Building Blocks for Intelligent Information RetrievalWhy do most enterprise search solutions disappoint users? Discover the fundamental components that transform basic document search into contextual intelligence systems. Get hands-on with embeddings, chunking strategies, and the architecture of RAG systems that actually return relevant information. Module 3: Enterprise RAG with Guardrails—Moving Beyond PrototypesWhy do systems that work in demos fail in production? Learn how to transform proof-of-concepts into enterprise-grade solutions with semantic caching, optimized inference, and essential safety controls. Implement trustworthy systems that match your organization's risk tolerance and compliance requirements. Module 4: Agents and Their Ecosystem — Vertical AI AgentsWhat are agents really? Go beyond CrewAI and Autogen to build your own agent orchestration framework using AgentPro. Focus on vertical agents like Data Analyst Bots, Research Assistants, and more. Module 5: Teaching LLMs Your Organization's Language Through Fine-TuningWhy do generalist models struggle with your industry's terminology? Learn practical approaches to adapting models to your domain's vocabulary, processes, and knowledge structures. Implement LoRA fine-tuning and knowledge graph integration techniques that ground AI in your organizational context. Module 6: Capstone Discussion WeekWorkshop your final project ideas, get peer and instructor feedback, and finalize your architecture and approach for your custom RAG or Agent system. Module 7: Demo DayPresent your fully built, working system to the cohort. From agent demos to enterprise RAG deployments — this is where theory meets execution. Why This Course Is Different?The GenAI landscape is cluttered with tools, frameworks, and platforms—each promising to be the silver bullet. Our approach isn't about teaching you specific tools that will be outdated in six months. Instead, we focus on the enduring principles of identifying high-value use cases and building solutions that address actual business needs. Our startup has guided organizations through the process of moving from AI curiosity to deployment, and we've distilled those lessons into this course. You'll learn to look beyond the marketing hype to determine which problems in your organization are genuinely suited for Gen AI solutions. This Course Delivers Results Where Others Don'tUnlike theoretical courses that leave you wondering how to apply concepts, or technical deep-dives that ignore business realities, this program bridges the gap between possibility and practicality.We've designed every session to answer the question: "How do I use this to create actual value in my organization?" Whether you're looking to enhance customer experiences, streamline operations, or unlock insights from unstructured data, you'll complete this course with concrete tools to transform GenAI from a buzzword into a business advantage. ✅ What You'll Get (Outcomes, Action-Oriented) By the end of this course, you’ll be able to: 🧠 Understand the GenAI Landscape: Cut through the noise and get a clear grasp of how LLMs, RAG, and Agents fit into real-world enterprise workflows. 🛠️ Build Production-Ready AI Agents: Learn how to design and deploy AI Agents that go beyond simple Python scripts — handling reasoning, memory, retrieval, and tool use. 💼 Deliver Business Impact: Map Agent use-cases to measurable ROI — from automating internal knowledge retrieval to customer service, market analysis, and more. 🧪 Customize &amp; Scale Your Solutions: Fine-tune domain-specific models, design feedback loops, and deploy with guardrails. 🚀 Capstone + Demo Day: Work on a real-world Agent project and showcase it to a private network of peers, builders, and mentors.

What can Agents do for me?

Course syllabus

If you haven't written code before, no worries at all. We will provide you with everything you need to get started.

Just be willing to learn, we will take of the rest

We will go through each module during this class

Wednesday: Module Teaching

Students will spend time building projects with their team members or individually

Weekly projects

Course schedule

Product Managers looking to integrate GenAI into their roadmaps with clarity and confidenceYou want to cut through the jargons and actually

Technical Leaders and Architects who want to build scalable and safe GenAI systems

Startup Founders &amp; Innovation Teams aiming to create competitive GenAI-powered products

Data Scientists &amp; ML Engineers who want to go beyond notebooks and deploy impactful GenAI apps

Who is this course for

Actionable Business Value, Not Just Technical Knowledge Outcome

Develop a structured approach to evaluate which business problems in your organization are genuinely suited for GenAI solutions. Stop wasting resources on use cases that look good in demos but fail to deliver ROI.

A Framework for AI Use Case Identification

Create actual, functioning GenAI applications using our provided code templates and step-by-step guidance. You'll build and deploy real systems—not just learn concepts.

Practical Experience Building Working Systems

Connect with professionals facing similar challenges across diverse sectors. Previous cohorts have formed lasting relationships that continue to provide value long after the course ends.

A Network of Cross-Industry Peers

Develop the ability to assess AI vendor claims and capabilities objectively. Learn which questions to ask and what metrics actually matter when evaluating solutions.

Vendor-Neutral Evaluation Skills

Build a clear, phased approach to GenAI implementation for your organization that aligns with business objectives and accounts for technical constraints.

Strategic Implementation Roadmap

Master the what, why, and how of Generative AI by building Enterprise-Grade Agents that go beyond the basics and actually move the needle

Hamza Farooq

Founder | Ex-Google |
Instructor Stanford Continuing Studies & Adjunct UCLA

Self-paced cohort

2025-01

🚨🚨Note: This course is an independent offering and is not affiliated with, endorsed by, or related to the instructors' current or past employers. ⛳ The only prerequisite: you should have coded at least once in your life. The course includes low-code assignments, and even folks who hadn’t touched code in over 15 years have found it approachable and rewarding. That said, a basic understanding of coding really helps you get the most out of it — and of course, there’s AI to assist you along the way. The course is built for everyone, whether you’re a Product Manager, Architect, Director, C-suite leader, or someone seriously exploring agentic AI. Agentic AI or AI systems capable of operating with some degree of autonomy, is transforming how we interact with technology. In the coming years, most software systems will integrate AI agents to enhance their capabilities. This shift will drive a growing demand for professionals who can move beyond surface-level understanding and apply AI effectively to solve real business challenges while navigating practical constraints. This course focuses on practical AI agent development, covering key usage paradigms such as workflow agents, integrating RAG/retrieval components, autonomous agents, and fine-tuning—all with a strong emphasis on real-world applications. Instead of just explaining "what" these techniques are, we’ll explore "when" and "how" to use them, equipping you to make informed, business-driven AI decisions. ⛳ What Makes This Course Unique Solving Real Enterprise Challenges, Not Just ConceptsWhile most courses stop at teaching tools and frameworks, this course goes further by focusing on solving real-world business problems. You’ll tackle practical constraints like cost, scalability, latency, and performance, learning to design AI solutions tailored to real use cases that deliver value. Participate in Weekly Enterprise Use-Case Workshops with Peers All sessions are recorded and available to watch anytime. Through the week, we host four 60-min office hours where you can bring in real-world business use cases you want to explore, and discuss possible design ideas with peers and instructors. Hands-On Product DevelopmentYou’ll build a real-world agentic product from scratch (low code options available). Our tutorials will guide you through creating your own Perplexity (Agentic search system), giving you practical experience with application techniques. Collaborative Team WorkshopsExperience what it’s like to solve a business problem in a real-world setting. In a collaborative workshop, you’ll work with others to design and develop solutions, simulating how teams take AI projects from 0 to 1.&nbsp; Capstone ProjectLearn how to connect cutting-edge research with real-world applications. For the capstone, you’ll use our curated list of the latest research papers to design and implement solutions for practical business use cases. ☕ Weekly Chai &amp; AI Sessions with Our Problem-First CommunityJoin optional weekly sessions during the course where we discuss the latest AI developments, their impact on enterprises, and what they mean in practice. We bring in guest speakers, including AI practitioners, industry leaders, founders, and VCs for AMA sessions, along with deep dives into research and hands-on workshops to bridge theory with real-world applications. Guest Lectures from Industry ExpertsWe believe in learning from practitioners who have built and deployed real AI solutions in the enterprise—not just talkers, but doers. Our past cohort guest lectures have featured leaders who drive AI adoption at scale, including:Aman Khan – Director of Product, LLM @ Arize AIDoneyli De Jesus – Principal AI Architect @ SnowflakeJayeeta Patatunda – Director, AI CoE @ Fitch RatingsWe aim to bring many more industry leaders in future cohorts, ensuring you learn from the best in the field. 🫨🫨🫨The Biggest Advantage! (Lifetime access to future cohort material)AI moves fast, and staying ahead means continuous learning. That’s why all students get lifetime access to the latest AI material from all future cohorts—no extra fees, no outdated content. You’ll always have access to latest cohorts lecture recordings and reading materials, incorporating the latest model updates (like reasoning models currently), emerging techniques, industry shifts, and best practices. This is your one-stop learning hub—no need to keep signing up for new AI courses. New Concepts Coming to the May 2025 Cohort:Reasoning Models – A full module on when, how, and why to use themMCP &amp; Agentic Apps – Building agentic applications using MCPAgent Evaluations – Methods and best practices for assessing agentsAgent Architecture Breakdown – Deep dive into popular agents like NotebookLM, Deep Research, and potential architectures 🙌 Plus, top students get lifetime access to our Chai &amp; AI community sessions and in-person meetups, where they can dive into deep discussions, network with top industry professionals, and gain exclusive insights straight from the frontlines of AI. ❌ Who This Course Is Not For For Those Who Have Already Deployed Gen AI in Enterprise: This course is designed as an applied foundations course for enterprise AI with only basic Python as a prerequisite and no ML background required. If you’re already familiar with deploying AI systems, you won’t gain much from the core content. However, if you're looking to network and refine best practices, you're welcome to join. Those Seeking Heavy Theoretical Knowledge: This course emphasizes applied learning and practical problem-solving, not deep dives into theoretical topics like transformer architecture, pre/post-training optimization, inference techniques, or alignment. Those Who Have Never Coded Before: While we provide low-code options, this course assumes you have some coding experience. It’s not suitable for those who have never written or worked with even basic code. Individuals Expecting Deep AI Research Focus: While we’ll cover cutting-edge techniques, this course is centered on applying AI to business problems, not research-heavy exploration. Scaling and Ops Enthusiasts: This course does not focus heavily on scaling or operational aspects (i.e., LLMOps). Deployment will be covered at a high level, but not in-depth.

Design and build impactful agentic AI systems to solve business problems.

We offer generous office hours to support you throughout the course, along with 24-hour help on Slack. Typical weekly schedule:<ul><li>Wednesdays at 10 am PT and Saturdays at 9 am PT: Assignment Support</li><li>Thursdays at 5 pm PT and Saturdays at 8 am PT: Content/Use-case discussions</li></ul>

Live Office Hours

Our weekly community discussion channel covers the latest trends in AI, industry updates, and all the unfiltered tea, open, casual, and freeform.

Chai & AI Sessions

We bring in industry experts to share proven insights and discuss real enterprise challenges

Guest Lectures

Software/AI Engineers, Strategists, Data Professionals, Solution Architects and Consultants who want to master AI system design

Business Leaders and Product Managers seeking to gain the technical understanding needed to make informed decisions &amp; lead AI initiatives

Entrepreneurs looking to understand common generative AI use cases and learn how to develop and implement AI-powered solutions

What you’ll get out of this course

Learn applied generative AI techniques like prompt engineering, RAG, agents, and fine-tuning, with a focus on applying them effectively to real-world business scenarios. Understand how to navigate constraints like cost, latency, and performance constraints in AI systems.

Master Applied Agentic AI Concepts
 

While learning applied AI concepts, we’ll put them into action by building a Perplexity-like AI-powered search system through detailed, hands-on tutorials that demonstrate their practical application (Low code options will be provided)

Apply Concepts to Build an Agentic Search System

Participate in brainstorming sessions and team huddles to approach hypothetical business problems. Learn to identify the right AI solutions for specific use cases, leveraging low-code options where applicable.

Tackle Business Use-Cases with AI

Gain a deep understanding of key challenges in building AI systems, including handling hallucinations, adversarial attacks, security, privacy issues etc., and learn best practices to evaluate AI solutions comprehensively

Understand Challenges and Effective Evaluation
 

You’ll design and demo a solution for a hypothetical business problem, integrating insights from relevant research papers in my curated list, hand-picked for enterprise relevance. This project will also involve addressing challenges and evaluation methods.

Final Capstone Project
 

The course includes guest lectures from industry experts, AMA sessions, and our Chai &amp; AI discussions, culminating in a final in-person meetup in the Bay Area. You'll have plenty of opportunities to network and become part of our community.

Access to the Problem-First AI Community

Learn to make decisions tailored to business constraints, understand when & how to apply AI effectively & build an application from scratch

May 2025 Cohort

Aishwarya Naresh Reganti

Tech Lead | Lecturer | Advisor | Researcher | Speaker | Investor

Kiriti Badam

Member of Technical Staff @ OpenAI | AI Advisor | Ex-Google

March 2025 Cohort

July 2025 Cohort

The pace of GenAI is relentless. Are you finding it challenging to:- Move beyond basic prompts to engineer reliable AI solutions?- Effectively integrate GenAI into your complex workflows?- Stay ahead of the curve with the constant stream of new research and tools?- Cut through the hype and identify genuine opportunities? Feeling overwhelmed is normal. GenAI isn't just another tool; it's a paradigm shift. Simply using it isn't enough to secure your future. There are no textbooks to read, no buttons to click, no "best practices" or even "the best model". Everything is changing. To truly thrive, you need to become a builder. This Course Transforms You From User to BuilderWe believe the key to mastering GenAI lies in learning through creating. This course is built from the ground up to do more than just teach you techniques – it's designed to fundamentally shift your mindset and empower you to build. We combine hands-on projects with deep dives into the underlying research. Why? Because practical skills without research knowledge become quickly outdated, and research knowledge without practical application remains theoretical. You need both to innovate. "This course not only teaches me many best practices and techniques of Generative AI but also, more importantly, conveys mindsets that can be leveraged in both work and life." – Software Engineer at Zuora, Cohort 1"What I love this course, is that it does not only teaches you practical skills, but also training your mind and establish a builder's mindset... learn how to learn, learn how to unlearn, will be surely one of those skills." – Sr. Principal Technical Program Manager at Oracle, Cohort 8 What You Will Achieve:- Master Practical GenAI Building: Go from idea to prototype. Learn advanced prompt crafting, robust GenAI integration, and essential tooling through hands-on projects relevant to your work. Get personalized feedback to ensure success.- Gain Deep Research Intuition: Develop a solid foundation in LLMs. Understand the 'why' behind the techniques, navigate new developments confidently, and identify valuable opportunities others miss.- Revolutionize Your Daily Workflow: Learn to automate complex tasks, significantly enhance your efficiency, and maintain your competitive edge by strategically applying GenAI. Overcome hurdles with our "guided mistakes" approach.- Develop Critical AI Thinking: Learn to see beyond the clickbait. Put GenAI into the context of technological history, challenge assumptions, and predict future impacts with clarity.- Unlock the Builder's Mindset: Move beyond passive consumption. Cultivate the confidence, framework, and iterative approach needed to continuously learn and create valuable AI applications. "I was looking for guidance in integrating GenAI into my day-to-day job and this course provided exactly that... I highly appreciate the instructor's focus on the technical best practices and the intuitive explanation of the 'why' behind them. I feel prepared." – Senior Research Scientist at SLB, Cohort 2"The course is well designed with very insightful high level contents on mindset... and very specific and tangible practical examples... Highly recommend for people who are a bit hesitant to start building... or people who want to see how they can build better genAI applications but lack a framework to do so." – Principal Data Scientist at DIRECTV, Cohort 4 How You'll Learn:Our curriculum centers around building practical prototypes. After each build, we dive into the relevant research, connecting theory directly to application. You'll learn prompt engineering, debugging strategies, and how to optimize GenAI solutions for your specific needs, culminating in a class project tailored to you. "I really appreciated how Yan presented the demo and technical details with clear examples, while Yuzheng provided valuable insights into LLMs and practical guidance on their usage." – Software Engineer at Google, Cohort 7"Despite I was working on AI tools day-to-day, I find myself learning something new and in a deeper level, and be able to more effectively leverage AI to build solutions..." – UX Manager at Google, Cohort 7 We Created A LIfelong Community with over 5,000 AI BuildersYour enrollment includes lifetime access to our exclusive community: https://www.superlinear.academy/c/share-your-work/Connect with fellow innovators, share cutting-edge developments, find inspiration, and get support on your GenAI journey and career advancement. Ready to Build?We highly recommend the immersive experience of our cohort-based course. However, we also offer a self-paced version if your schedule requires flexibility: https://www.superlinear.academy/c/ai/All cohort students receive complimentary lifetime access to the self-paced course materials and community.

How we taught eight cohorts to get ahead and stay ahead in AI:


Walkthrough building prototypes together. Learn their implications through LLM research and our technical insights.

Live Sessions

Content similar to the live sessions without the need for interactions. Fit your busy schedule and learn on your own pace.

Offline/Async Courses


Build your own GenAI solution for your particular use case. Apply the tools and mindsets learned in class

Get feedback and coaching on your class project. Learn what other students have built.

Office hours

You know basic Python.

You want to apply AI to your daily work and boost productivity

You seek to understand AI.

You want to capture the opportunties in AI

Acquire hands-on skills by building useful GenAI prototypes. Master prompt crafting, AI integration, and essential tools for immediate application in your daily tasks. Receive personalized feedback to ensure your project's relevance and success.

Master Practical AI Building

Build a solid foundation in LLMs to confidently navigate GenAI developments. Learn to spot and seize opportunities by understanding the evolving landscape of AI technology from the inside out.

Gain Deep Research Intuition

Learn to automate complex tasks, significantly enhance efficiency, and maintain your competitive edge by strategically integrating GenAI. Overcome common challenges effectively through our unique "guided mistakes" approach.

Transform Your Daily Workflow

Cut through the clickbait. Get challenged to think critically, place GenAI developments in historical perspective, and predict future impacts with clarity.

Develop Critical AI Foresight

Get lifetime access to an exclusive, member-only community that we specially built. Connect with fellow builders for inspiration, sharing cutting-edge developments, and ongoing support in AI and career advancement.

Join a Lifelong Community of Builders (over 5,000 members)

Leapfrog the AI curve by joining 5,000+ fellows, mastering the only skill that never expires: building.



Yuzheng Sun, PhD

Statsig.com Data Scientist | Ex Tencent Director | Ex Meta/Amazon/BCG | Tech channel with 200k+ subscribers and 5k+ paid members

Yan Wang, PhD

Applied Scientist @ Samsara | Olympic Torchbearer | Ex Pinterest/Microsoft | Ex Tech blogger with 100k+ subscribers

Cohort 8

Cohort 9

If you’re a software engineer or data scientist, chances are you’ve built or seen a proof of concept (POC) for a generative AI app. It’s exciting at first—an impressive demo that showcases the potential of large language models. But here’s the problem: that’s where it usually stops. These POCs often fail to scale into reliable, production-ready applications. The result? Endless iteration cycles, unreliable outputs, and frustration as teams struggle in what we call “POC purgatory.” It doesn’t have to be this way. With the right principles, processes, and workflows, you can build LLM applications that work in production – without overcomplicating pipelines or chasing trends. This course focuses on the iterative development, evaluation, and debugging practices that make AI systems production-ready. We’ll explore tools like RAG, embeddings, and agents, but the emphasis is on building scalable, robust systems – ensuring you leave with the mindset and skills to adapt as the technology evolves. You’ll not only learn how to design, test, and deploy generative AI applications, but also how to iterate and improve rapidly. This isn’t just about building something cool – it’s about creating AI systems that solve real problems, deliver real value, and scale with confidence. What to ExpectThis is a highly interactive course designed to get you results. Across live workshops, discussions, and hands-on projects, you’ll build your skills while solving real-world challenges. •	Live coding sessions to design and refine LLM applications.•	Iteration exercises to explore how small changes can dramatically improve reliability.•	Discussions on user-centric development and integrating feedback loops.•	Expert-led Q&amp;As to help you tackle your toughest challenges. What You’ll Learn •	How to transform POC demos into production-grade applications.•	Strategies for managing non-determinism and optimizing outputs through prompt engineering.•	How to monitor, log, and debug AI systems to ensure reliability and performance.•	Best practices for handling structured outputs and integrating function calling into your applications.•	Building workflows for iterative development and experimentation.•	Practical skills through hands-on app development, including creating a Generative AI app to query PDFs. Bonus Perks All students will receive -&nbsp;$500 in Modal credits&nbsp;for cloud compute – giving you resources to power real AI applications.- $300 in Google Cloud and Gemini credits for the first 100 registrants.- More credits to be announced soon! Guest lectures Learn directly from leading practitioners solving real AI problems in production. These sessions focus on practical workflows, debugging strategies, and building scalable systems – not just theoretical research or cutting-edge multi-agent architectures. Enrolling will also give you access to all recorded guest lectures from previous cohorts of this course: - Hamel Husain (Ex-Airbnb, GitHub) – Basic Data Literacy for Debugging and Evaluating LLMs&nbsp;- Swyx (Latent Space podcast, smol.ai, ai.engineer): Engineering AI Agents in 2025- Sander Schulhoff (CEO, LearnPrompting.org) – Prompt Engineering in the LLM SDLC&nbsp;- Charles Frye (Developer Advocate, Modal) – Hardware for LLM Developers- Ravin Kumar (DeepMind) – End-to-End LLM Product Development This Course Is For •	Data scientists and machine learning engineers who are sick of unreliable POCs and want to ship reliable LLM applications.•	Software engineers who want to learn how to build generative AI systems and master the LLM software development lifecycle. This Course Is Not For Those •	Looking for an introductory course in AI—some programming knowledge is required.•	Expecting ready-made solutions for AI problems without active participation.•&nbsp;Expecting deep dives into advanced evals, multi-agent systems, or large-scale RAG pipelines. This course emphasizes building and iterating on practical, production-ready systems.•	Unable to commit to hands-on projects, live discussions, and iterative development exercises. Why Take This Course By the end of this course, you’ll: •	Understand the first principles of generative AI development.•	Gain hands-on experience building robust, scalable applications.•	Learn how to troubleshoot, monitor, and optimize AI systems for production.•	Develop workflows to iterate and refine AI applications effectively.•	Leave with the confidence to deploy reliable AI systems at scale.

Master the patterns and processes that underpin successful GenAI app development

Tuesdays and Thursdays

To ensure hands-on practical time, there will be project work to complete throughout the course.

Data scientists, machine learning engineers who are sick &amp; tired of seeing and building prototypes &amp; want to ship reliable LLM applications

Software engineers who want to learn how to build Generative AI systems and learn the LLM software development lifecycle.

You’ve seen impressive generative AI demos—but how do you take them to production? In this course, you’ll learn the exact workflows, tools, and engineering practices needed to turn concepts into reliable, scalable applications that deliver real value.

Move beyond POCs and build production-ready AI systems

Struggling with inconsistent outputs? Through interactive exercises, you’ll explore proven techniques for optimizing prompts and ensuring your AI delivers actionable results in production settings.

Master prompt engineering for reliable results

When your AI application breaks, you’ll know exactly how to fix it. We’ll walk you through real-world debugging sessions, monitoring techniques, and tools to ensure your systems stay reliable at scale.

 Learn to debug and monitor AI systems like a pro

Want your AI to produce precise, usable results? You’ll learn how to handle structured outputs and function calls, making your applications smarter and more user-friendly.

Build smarter applications with structured outputs

Stop wasting time in endless iteration cycles. Through guided projects, you’ll discover how to set up workflows that refine your applications faster and with less frustration.

Accelerate your development process with iterative workflows

Tired of theoretical knowledge? You’ll build a fully functional app that uses text and image models to query PDFs, giving you practical experience solving complex real-world problems.

Develop hands-on expertise by building GenAI and LLM apps

Whether you’re looking to lead AI projects, impress stakeholders, or level up your technical expertise, this course gives you the tools to stand out as an AI/ML practitioner.

Advance your career with practical, proven techniques

These aren’t just skills for demos—they’re skills for delivering scalable, production-ready systems that solve real-world business challenges.

Solve Real Problems at Scale

Leave the course with a project you can add to your portfolio, demonstrate to your boss, or use to showcase your ability to deploy reliable AI systems.

Showcase Tangible Results

Build LLM-powered software reliably & from first principles. Learn the GenAI software development lifecycle: agents, evals, iteration & more

Lightning Lessons

Q&A: Building Real-World Apps With GenAI