🚀 New: Cracking the GenAI Interview for DevOps, SRE, Platform & Forward-Deployed Engineers — Limited Seats Available. Enroll Now →
Built for DevOps, SRE, Platform & Forward-Deployed Engineers

Crack the GenAI Interview

A 90-day intensive for DevOps, SRE, Platform & Forward-Deployed Engineers

For the first time, a course built specifically for engineers whose infrastructure work now meets Generative AI, LLMs, Python, system design, automation, and AI agents.

Enroll NowHow It Works
90-Day IntensiveLive Instructor-Led$299 Live · $149 Self-PacedEx-Red Hat, Apple & Uber
Programs & Courses

Learn Generative AI by Building Real Systems

Every program is cohort-based, hands-on, and designed for engineers who want to go beyond tools and understand how AI systems actually work.

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First of its kind · Enrolling Now · Sep 2026

Cracking the GenAI Interview

for DevOps, SRE, Platform & Forward-Deployed Engineers

For the first time, we have a course built specifically for DevOps, SRE, Platform, Cloud, and Forward-Deployed Engineers. Traditional infrastructure knowledge is now combined with Generative AI, LLMs, Python, system design, automation, and AI agents — and this program prepares you for those interviews.

September 14 – December 1290-Day Intensive Interview Preparation
$299live

₹24,999

Self-paced $149 · ₹12,999

Special Payment Option for India (Details below)

Instead of focusing only on theory, the program combines five major areas of interview preparation:

🧠
Generative AI & LLM Engineering
🐍
Python & DSA
🏗️
System Design
⚙️
DevOps/SRE Automation
🚀
Hands-on AI Projects

Based on student request, we can modify the content of the course — but we are determined to complete all the concepts.

Prerequisites

We start from the basics. These are good to have, not hard blockers.

  • Basic knowledge of DevOps concepts
  • Basic knowledge of Python

Weekly Curriculum Cadence

Same weekly rhythm for Morning and Evening live batches.

DayFocus Area
MondayGenAI for DevOps
TuesdayPython for DevOps / Interview Preparation
WednesdayGenAI for DevOps Project
ThursdayBreak
FridaySystem Design
SaturdayPython for DSA
SundayPython for DSA

Learn from 3 engineers

Ex-Red Hat & Salesforce · Ex-Uber · Ex-Yahoo & Apple

Prashant Lakhera · Ex-Red Hat & SalesforceRahul · Ex-UberPramod · Ex-Yahoo & Apple
🌅Morning
$299₹24,999
Sep 14 – Dec 12
Mon–Fri (Thursday break): 7:00 – 8:00am PST
Sat–Sun: 7:00 – 9:00am PST (common for both batches)
Enroll — Morning →
🌙Evening
$299₹24,999
Sep 14 – Dec 12
Mon–Fri (Thursday break): 7:00 – 8:00pm PST
Sat–Sun: 7:00 – 9:00am PST (common for both batches)
Enroll — Evening →
▶️Self Paced
$149₹12,999
Start anytime
Instant access · learn on your schedule

Note: Daily lecture recordings are uploaded by 5 PM PST throughout the 90-day program (except Thursdays).

Enroll — Self Paced →

All timings in PST — Thursday is a break day. Weekend sessions are common for Morning and Evening batches.

🇮🇳Special Payment Option for India
Paytm / UPI QR Code
₹24,999live cohort
$299 · Morning or Evening
OR
₹12,999self-paced
$149 · start anytime

You can pay using the Paytm / UPI QR code. Scan with any UPI app — Paytm, PhonePe, Google Pay, or BHIM.

After payment, please email your transaction ID and registered email address to:

help@ideaweaver.ai

We will confirm your enrollment and add you to the batch within 24 hours of receiving your email.

Self-Paced · Instant Access

NVIDIA-Certified Associate

AI Infrastructure and Operations (NCA-AIIO)

The live cohort has concluded. Get instant access to the full session recordings, exam preparation guide, and 2 full-length practice tests — covering GPU vs CPU architecture, AI infrastructure design, cluster operations, GPU monitoring, datacenter management, and cloud vs on-prem trade-offs.

Session RecordingsPrep Guide2 Practice TestsGPU ArchitectureAI InfrastructureCluster Operations
$19one-time
Get Access →
Our Approach

Most AI courses focus on tools and prompts. We focus on systems.

IdeaWeaver AI Labs is a hands-on learning platform built for Software Engineers and DevOps Engineers who want to transition into Generative AI by understanding how real systems work.

Here, you learn how Generative AI actually works — how models are trained, evaluated, and used in real-world systems. We start from the basics. A basic knowledge of DevOps concepts and Python is good to have.

You’ll work on real-world patterns, interview problems, and hands-on projects. Built by engineers, for engineers.

Explore Programs
🏗️

Learn by Building

Weekly live classes and hands-on exercises focused on real-world Generative AI systems — not slides, not theory dumps.

⚡

Start from the Basics

We begin from first principles. Basic knowledge of DevOps and Python is good to have, but not a hard blocker.

🧠

From Basics to Models

Start from first principles and progress all the way to building and understanding small language models from scratch.

👥

Cohort-Based Learning

Learn alongside other engineers at the same stage. Live sessions, shared exercises, and a community that moves together.

LangChain & Prompt Engineering
Hugging Face & Model Hubs
Retrieval-Augmented Generation (RAG)
Fine-Tuning & Model Evaluation
AI Agents (CrewAI, LangGraph, n8n)
Ollama & vLLM (Local Inference)
Tokenization & Positional Encoding
Attention Mechanisms & KV Cache
Building Small Language Models
PyTorch & Neural Networks
MCP & Quantization
Kubernetes + GenAI Workflows
What You’ll Work On

A complete path from engineer to AI builder

Our programs are cohort-based and focused on learning by building. Instead of relying on prompt-only workflows, students work on practical exercises and mini-projects that reflect how Generative AI systems are designed, trained, evaluated, and deployed in real-world environments.

All programs emphasize practical implementation, clear mental models, and engineering depth.

See All Programs
Student Feedback

What students are saying

Thank You Prashant for the wonderful course. It was really helpful.

H
Hari

Thank you so much for this wonderful deep-dive course and looking forward for RAG deep-dive session too.

K
Karthik

Thanks Prashant Sir, The way you explained concepts and supported us throughout the batch helped build both our understanding and confidence. 🙏

G
Gourav

It was an incredible journey @IdeaWeaver Support — You have helped learn the basics and given the opportunity to expand our horizons. Your teaching methodology has the power to take your audience to another world. It was a great learning experience. Thank you!!

K
Kamal

Thanks Prashant — I didn't even realize our batch was over (I came Sat morning as usual to join in and then realized 😅). Indeed all the classes were very good — your deep knowledge in each aspect (and humility to not 'hallucinate' when you didn't know something 😅) was appreciated.

T
Taher

I think you did a fantastic job and I learned some important things.

A
Anonymous
Your Instructors

Learn from 3 engineers

PL

Prashant Lakhera

Founder, IdeaWeaver AI Labs · Ex-Red Hat & Salesforce

Generative AI & LLM Engineering

With 20+ years of experience across Software Engineering, DevOps, Cloud, Kubernetes, and Large-Scale Distributed Systems. Over the years, I’ve worked on systems used by millions of users, built and operated production-grade cloud platforms, and helped teams debug, scale, and secure complex infrastructure.

More recently, my focus has been on Generative AI — specifically how LLMs actually work under the hood and how to build reliable, real-world GenAI systems. I’m the author of multiple technical books, a CNCF Kubestronaut, RHCA, and an AWS Community Builder.

I created IdeaWeaver AI Labs to help engineers transition into Generative AI the right way — by building systems, understanding fundamentals, and learning through hands-on work, not hype.

CNCF KubestronautRHCAAWS Community BuilderPublished Author20+ Years Engineering
R

Rahul

Ex-Uber

Python Data Structures & Algorithms (DSA)

Software engineer with experience building scalable products. At Uber, he built recruiting tools used across 70 countries — including an Approval Chain module that cut decision-to-hire time by 83% and an Offers tool that reduced processing time by 93%.

Skilled in Go, Python, and MySQL, with a strong foundation in distributed systems and microservices — the same problem-solving depth he brings to Python and DSA interview prep.

P

Pramod

Ex-Yahoo & Apple

System Design

Designed, deployed, and scaled distributed applications on AWS, Kubernetes, EKS, Helm, Kafka, Docker, and serverless — including high-availability design, performance optimization, and IaC.

Also worked on security/compliance platforms (SSO, Vault, centralized logging) and big-data stacks (EMR, Spark, Kafka, S3) — useful context for system-design interviews at scale.

Community & Content

Learn beyond the classroom

▶️

YouTube Channel

9.5K Subscribers

Free tutorials on DevOps, Kubernetes, Cloud, and Generative AI. Hundreds of videos for engineers at every level.

Visit Channel →
✍️

Medium Blog

6.5K Followers

In-depth technical articles on Generative AI, DevOps, Kubernetes, and cloud engineering. Written for practitioners.

Read on Medium →
Products

Free Tools & Resources

Open-source projects and practice tools built by IdeaWeaver, free for anyone to use.

Open Source

DevOps Open Agent

An open-source AI agent built for DevOps workflows — automate troubleshooting, infrastructure tasks, and day-to-day operations. Fully open source and free to use.

Free
View on GitHub →
Certification Prep

NVIDIA-Certified Associate: AI Infrastructure and Operations — Practice Exam

A free 50-question practice test covering GPU architecture, the NVIDIA software stack, distributed training, and infrastructure operations. Includes a Practice Mode with instant explanations and a timed Exam Mode.

Free
Start Practice →
FAQ

Frequently Asked Questions

We start from the basics. It is good to have a basic knowledge of DevOps concepts and a basic knowledge of Python — neither is a hard blocker.
No. We start from first principles. All programs are designed for Software and DevOps Engineers making the transition.
You learn alongside a group of engineers at the same stage. This is a 90-day program with live, instructor-led sessions 6 days a week (Thursday is a break). Recordings are available for enrolled students.
The 1-month programs (GenAI for DevOps, AI Agents, SLM) focus on a single domain. The 90-day program is a full interview-preparation curriculum covering Generative AI, Python & DSA, system design, DevOps/SRE automation, and hands-on AI projects — with live sessions 6 days a week.
Yes, we record every live session. If you miss any session, you will be able to access the recording and catch up at your convenience.
All labs will be provided through Google Colab. You will have lifetime access to the labs, repositories, and updated course materials.

The main difference is access to the live classes.

Live Program: You can attend the live instructor-led sessions and interact with the instructors directly.

Self-Paced Program: You will not be able to attend the live classes, but you will receive access to the same recordings, labs, repositories, projects, and course materials.

For self-paced students, each day’s lecture recording is uploaded by 5 PM PST throughout the 90-day program. There are no uploads on Thursdays, which is our weekly break day.

Yes, the self-paced program covers the same 90-day intensive interview preparation curriculum. The primary difference is that you will follow the program through recordings rather than attending the sessions live.

Yes, hands-on projects are included as part of the program. We will also provide the supporting documentation and architecture/materials required for the projects.

We will cover multiple practical projects. Some examples include:

  • GitHub PR Reviewer Agent
  • Performance Debugging Agent
  • Log Reviewer/Analysis Agent
  • AWS/GenAI-related hands-on exercises
  • Kubernetes and GPU infrastructure labs

You can find the detailed curriculum, projects, and program structure here.

Here are two sample labs that you can review:

These should give you a good idea of how some of the hands-on exercises will be structured.

We will have hands-on labs for AWS services such as AWS Bedrock. For cloud-based labs, students will need to use their own cloud accounts. IdeaWeaver does not provide AWS/Azure/GCP accounts or cloud credits.

Yes, we will build and work with Kubernetes clusters, especially from a GPU and GenAI infrastructure perspective.

For GPU-related labs, we plan to use platforms such as Lambda Labs and RunPod. Students will need to create their own accounts on these platforms and cover any associated usage costs.

Lifetime access applies to the course materials, recordings, Google Colab notebooks, repositories, and other learning resources we provide.

For external cloud platforms such as AWS, Lambda Labs, and RunPod, access and usage depend on your own account and the respective provider’s pricing and policies.

At this time we do not offer refunds. If you have questions about a program before enrolling, reach out directly.
Stay in the Loop

Let’s Keep in Touch

Join the IdeaWeaver AI Labs mailing list to get early access to cohort launches, hands-on GenAI workshops, and deep technical content for engineers transitioning into Generative AI.

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