Problem-First AI

March 2025 Cohort

May 2025 Cohort

July 2025 Cohort

Self-paced Cohort

Oct 2025 Cohort

Hitachi Cohort

Jan 2026

Download a list of over 50 capstone projects from our course with full end-to-end architecture designs, demo video, iterations, evaluations, guardrails, and more across enterprise verticals like healthcare, finance, education, real estate, retail, and legal.

Capstone Projects Showcase

Access our curated collection of top reading materials, roadmaps, research papers, and more!

Our Curated Generative AI Free-Resource Bundle

Learn to make decisions tailored to business constraints, understand when & how to apply AI effectively & build a multi-agent application

AI Founder & Advisor to F500s | Ex-AWS

Aishwarya Naresh Reganti

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

Applied AI @ OpenAI | Ex-Google

Kiriti Badam

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

Building Agentic AI Applications with a Problem-First Approach

Director of Analytics

Systems Analyst

Product Designer

Product Manager

Group Product Manager

Principal Product Manager

Associate Partner

Head of Business Technology

Senior Product Manager

Finance Director 

Amazon Web Services

University of Oxford

Microsoft

OpenAI

Google

Samsung

Databricks

We teach RAG, evals, agents, MCP, multi-agents, context engineering, and all that jazz. But always as tools to solve a business problem. If you want a checklist of hype items without knowing when or why to use them, please don’t join our course. :) 🚨🚨Notes:<ul><li>We hold a 4.9 rating across 430 +reviews, making us the #1 rated course on Maven at this scale. So why are students raving about out course? Check out our <a target="_blank" rel="noopener noreferrer nofollow" href="https://testimonial.to/building-agentic-ai-applications-with-a-problem-first-approach/all">wall of love</a>!</li><li>Many of our students have No AI experience walking into the course. To estimate what you can achieve at the end of this course check out our student capstones <a target="_blank" rel="noopener noreferrer nofollow" href="https://bit.ly/capstones_pai">here.</a></li><li>We follow a flipped-classroom format. All lectures are pre-recorded so folks can go at their own pace, but we’ll still meet 3 times a week for office hours and live sessions. Check schedule below for more details</li><li>For questions or bulk requests, reach out to: problemfirst.ai@gmail.com</li><li>Check out the FAQs section for current promotions and offers</li></ul>This course is an independent offering and is not affiliated with, endorsed by, or related to the instructors' current or past employers.

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

Develop a Problem-First AI Intuition For Enterprise Use Cases

Build an Evals Driven Mindset & Iterative Design

Master Practical Prompt and Context Engineering

Build and Optimize Agentic Pipelines

Apply Everything in a Real-World Capstone

You should have coded at least once in your life. The course includes no-code assignments but some knowledge of code helps!

The only prerequisite

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

State of Applied AI in 2025 Report

AI Founder & Advisor to F500 Leaders

Member of Technical Staff @ OpenAI | AI Advisor

How the applied AI stack evolved, what was hyped and what teams actually adopted

2025 Hype vs. Enterprise Trends

How evals, memory, multimodal reasoning, and better context engineering will shape next year’s systems

What to prepare for in 2026

Sharing some best practices from working on several enterprise ai implementations

5 rules for building robust agents in the wild

#2 Designing Agentic AI Systems for Enterprise Use-Cases

Aishwarya Reganti

AI Advisor, Founder, Ex-AWS

Applied AI Engineer @ OpenAI, Ex-Google

Understand how to take an enterprise use-case, scope it and build solutions with state-of-the-art techniques

Watch 20+ Agentic AI Application Solutions

Use-cases include verticals like finance, real-estate, manufacturing, retail and more!

See Live Solutions For a Wide Range of Enterprise Verticals

What sets a good AI practitioner apart is their ability to work within business constraints. Watch it in real time!

Learn About Our Problem-First Framework

A 25% off coupon will be shared during the session and will be valid only until the session ends.

Get An Exclusive Discount On Our Next Cohort

Sign up for #1: https://maven.com/p/f9951a/1-designing-agentic-ai-systems-for-enterprise-use-cases

🔔 Note: Projects are spread across 2 sessions

#1 Designing Agentic AI Systems for Enterprise Use-Cases

Sign up for #2: https://maven.com/p/22d0f6/2-designing-agentic-ai-systems-for-enterprise-use-cases

Applied AI Engineer, OpenAI, Ex-Google

Watch 15+ Agentic AI Application Solutions

A 15% off coupon will be shared during the session and will be valid only until the session ends.

Sign up for #1: https://maven.com/p/545da1/1-designing-agentic-ai-systems-for-enterprise-use-cases

Sign up for #2: https://maven.com/p/69f3e6/2-designing-agentic-ai-systems-for-enterprise-use-cases?utm_medium=ll_share_l

Don't Build AI Products Like Traditional Software

Founder @ LevelUp Labs | AI Advisor | Ex-AWS

Applied AI @ OpenAI | AI Advisor | Ex-Google

Traditional software behaves predictably. AI doesn’t. Learn how to build around the non-determinism

AI Products & Non-Determinism

Most enterprise teams rush into building autonomous agents, and fail. Learn how to think through the tradeoffs first.

Understanding the Agency/Control Tradeoff

CI/CD doesn't quite make the cut for AI products, learn about our new CC/CD framework!

CI/CD for AI Products

#3 Single vs. Multi-Agent AI Systems

AI Tech Lead | Advisor

We’ll break down what qualifies as multi-agent, common misconceptions, and the core coordination patterns they use.

What Multi-Agent Systems Are (And Aren’t)

Understand when multi-agent systems are helpful and when they can lead to unnecessary debugging overhead

When to Use One Agent vs Many

We’ll cover the real-world challenges: context sharing, memory, handoffs, failure handling etc.

Hidden Complexities in Multi-Agent Setups

#2 AI Protocols 101: What You Should Know About MCP, A2A etc

Tech Lead | AI Advisor

Get a clear picture of the protocol ecosystem (MCP, A2A, and others) and how they fit into the agentic AI stack.

The AI Protocol Landscape Today

See how enterprises are using these protocols today, and what to keep in mind around security, modularity & more

What Practitioners Need to Watch For

Know about current gaps that exist in the space and best enterprise practices while building

Best Practices w/ AI Protocols

#1 Building Agentic AI Applications 2025 (Q2 Updates)

Understand how the agentic AI landscape evolved this quarter across both cutting-edge research and real enterprise use.

2025 Q1 → Q2: What Shifted in Research and Enterprise

Get a quick overview of agent protocols, reasoning models, and self-improvement methods worth paying attention to.

New Trends to Watch

Get a forward-looking view of where agentic AI is headed next and what matters most if you’re building or deploying in t

What AI Practitioners Should Focus On Next

Integrating Agentic AI into Enterprise Architecture

Tech Lead @ AWS

Helen Yu

CEO @Tigon Advisory Corp

We’ll talk about what actually happens when agentic AI meets enterprise systems and why tech isn’t always the blocker

AI Integration Isn’t the Hard Part, It's the Alignment

You’ll walk away with a clearer lens on the real tradeoffs (cost, latency, control) and how to ask the right questions

The Build vs. Buy Debate

Most teams stall after the demo. We’ll cover what it takes to break out of PoC mode and start solving real problems with

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