AI Founder & Advisor to F500s | Ex-AWS
Applied AI at OpenAI Codex | Ex-Google


41 people enrolled last week.
🚨 For a limited time, until April 20, you can get our Become an Agent-Native Operator in 1 Day course free with this course and completely change how you work with tools like Claude Code, and Codex. Use this checkout link!
We teach all the the latest & greatest skills, including context engineering, evals, agentic retrieval and RAG, multi agent systems, harness engineering, MCP, skills, fine tuning and more! but as part of a decision map for solving business problems, based on our experience building 50+ AI products, not as a disconnected checklist.
We focus on the why and the how, not just the what. If all you want is a checklist of topics, YouTube already has plenty of that.
Check out out wall of love to see what our students think and to estimate the outcomes of the course, see our capstone showcase here.
No hard prerequisites: We have hands on assignments for both, with no-code and code heavy options.
If you're self-funding, Apply to our scholarship program (Reduced Price: $1750)
We follow a flipped classroom format with 35+ hours of live time
This course is an independent offering and is not affiliated with the instructors' employers.
Contact: problemfirst.ai@gmail.com
Learn to make decisions tailored to business constraints, understand when & how to apply AI effectively & build a multi-agent application
Identify where agentic AI can add value by reframing business challenges through a systems lens
Understand why traditional software assumptions fail in AI-driven environments
Evaluate tradeoffs between model choices, latency, performance and cost
Learn to frame AI problems through measurable outcomes rather than features or model choices
Understand how evaluation acts as the backbone of reliable agentic systems
Identify and quantify failure modes early using proxy metrics and iterative testing
Design smarter prompts using decomposition, meta-prompts, and algorithmic optimization
Compare reasoning and non-reasoning models for different business tasks
Implement evaluation and guardrail techniques using LLM judges and semantic scoring
Integrate retrieval, memory, and self-reflective behavior in agentic systems
Balance tradeoffs between accuracy, latency, and adaptability in agentic systems
Analyze multi-agent coordination patterns and challenges & learn about protocols like MCP/A2A
Work in small teams to design and implement an end-to-end agentic AI solution for a real business problem
Build an agentic search system across three iterations, integrating RAG, MCP, and multi-agent components
Present your final project to 2000+ attendees including enterprise leaders, investors, and hiring managers

AI Founder | Lecturer | Advisor | Researcher


Applied AI Lead | AI Advisor | Ex-Google
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 & lead AI initiatives
Entrepreneurs looking to understand common generative AI use cases and learn how to develop and implement AI-powered solutions
A willingness to work with a few basic terminal commands. The course does include a no code assignment track, but does require a small setup
Live sessions
Learn directly from Aishwarya Naresh Reganti & Kiriti Badam in a real-time, interactive format.
Lifetime access to all future cohort material
Go back to course content and recordings whenever you need to. Any changes made to future cohorts will be available for you to access offline
Community of peers
Our alums are product and engineering leaders from some of the best companies: Amazon, Anthropic, Databricks, Google, Snowflake, Notion, Meta, Microsoft and 130+ other companies
Certificate of completion
Share your new skills with your employer or on LinkedIn.
30+ hours of live interaction time
Flipped content w/ office hour style sessions for two way interaction
2 Separate assignment tracks (Low-Code and Code)
You can choose to use a visual agent builder for or python based agentic framework
Access to curated no non-sense AI resources
We've curated a large collection of practitioner approved free resources for you to continue your learning journey
Option to be part of our invite only Chai & AI community post-course
About our community: https://levelup-labs.ai/community.html
Maven Guarantee
Your purchase is backed by the Maven Guarantee.
24 live sessions • 83 lessons
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Live sessions
5 hrs / week
Sat, Apr 25
4:00 PM—5:00 PM (UTC)
Sun, Apr 26
3:00 PM—4:00 PM (UTC)
Tue, Apr 28
3:00 PM—4:00 PM (UTC)
Projects
3 hrs / week
Async content
4 hrs / week

Nadia V Gill

Karla Congson

Rick Somra

Govind Manoharan

Ravi Nukala

Milli Comstock
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Those who have already deployed GenAI systems in production and want advanced scaling or optimization content
Individuals looking for deep theoretical or research-heavy discussions (e.g., transformer internals, pretraining, or alignment math)
Participants who have never written or worked with code before, even at a basic level
Learners expecting detailed coverage of LLMOps, infrastructure, or large-scale deployment practices
$3,000
USD
3 days left to enroll