LIVE 2-HOUR HANDS-ON BUILD SPRINT FOR DEVELOPERS

BUILD YOUR FIRST GENAI APPLICATION IN 2 HOURS

You already know how to build software. Now learn how to build software with AI. A live, code-first engineering sprint where developers build a working GenAI application from scratch, add RAG and tool calling, and understand how the architecture evolves toward production.

No 40-hour video lectures. No math theory. Just 2 hours of building.

₹199 · ONE-TIME PAYMENTLive Sprint • Recording Included
Live Hands-On Sprint Full Source Code Recording Included One-Time Payment
genai-app-architecture.ts
Developer Architecture Diagram
CLIENT
User
GATEWAY
API
RAG / APP
Retrieval
MODEL
LLM
OUTPUT
Structured Response
SECTION 02 — THE TUTORIAL TRAP

YOU DON'T NEED ANOTHER AI COURSE.

You've probably already seen tutorials, saved GitHub repositories, and followed AI engineers:

LLMsRAGAgentsEmbeddingsVector DatabasesLangChainMCP ProtocolStructured Outputs

THE REAL GAP

"How do I actually turn this into a real application?"

That's the exact gap this 2-hour build sprint is designed to close.

SECTION 03 — TRANSFORMATION

FROM "I CAN CALL AN LLM" TO "I CAN BUILD AN AI APPLICATION"

BEFORE THE SPRINT
  • Can call LLM API
  • Knows AI buzzwords
  • Watches endless tutorials
  • Doesn't know application architecture
AFTER 2 HOURS
  • Understands AI application architecture
  • Integrates LLMs into backend systems
  • Understands RAG & vector retrieval
  • Understands tool calling & production concerns
SECTION 04 — HANDS-ON DELIVERABLE

WHAT YOU'LL BUILD

You will build a functional, working GenAI application during the 2-hour sprint while mastering how real-world enterprise architectures evolve.

Application Architecture Flow
Live Implementation
CLIENT
User Input
GATEWAY
API Layer
RAG STORE
Retrieval
MODEL
LLM Inference
OUTPUT
Structured Response

Architecture Evolution Path Covered in 2 Hours

STEP 1

01. LLM Call

Direct API Request

STEP 2

02. Context

System Instructions

STEP 3

03. RAG

Vector Retrieval

STEP 4

04. Tool Calling

Function Execution

STEP 5

05. Agent Workflow

Decision Loop

STEP 6

06. Production

Resilient Architecture

You will walk away with a working application + the production engineering mental model to build custom AI software.

SECTION 05 — 2-HOUR BUILD SPRINT

THE 2-HOUR BUILD SPRINT TIMELINE

00:00 ➔ 00:30 ➔ 01:00 ➔ 01:30 ➔ 02:00

01PHASE 1

BUILD THE AI CORE

Start with an empty project. Connect your application to an LLM, structure responses, control model behavior, and handle tokens and context.

LLM API Connection
Structured JSON Outputs
Context & Tokens
Latency & Error Handling
02PHASE 2

GIVE YOUR AI REAL CONTEXT (RAG)

Build the fundamentals of a RAG pipeline. Understand chunking, embeddings, retrieval, vector stores, and common RAG pitfalls.

Context Injection
Embeddings Pipeline
Vector Databases
When RAG is Useful
03PHASE 3

CONNECT AI TO YOUR APPLICATION

Understand function execution and tool-calling loops. Learn when agents add real value and when deterministic logic is better.

Tool Calling Loops
Function Execution
Agent Decision Boundaries
Engineering Patterns
04PHASE 4

THINK LIKE A PRODUCTION ENGINEER

Break down production concerns: latency, token costs, retries, timeouts, guardrails, observability, and scaling for real users.

Latency & Cost Controls
Retries & Guardrails
Observability
Production Blueprint
SECTION 06 — ARCHITECTURAL LAYERS

THE ENGINEERING MENTAL MODEL

You don't need to memorize 50 AI frameworks. You need to understand the 6 core layers.

LAYER 01Pillar 1

LLM

Generate, reason, and transform text & structured data

LAYER 02Pillar 2

CONTEXT

Inject the exact instructions and domain knowledge

LAYER 03Pillar 3

RETRIEVAL

Search & extract relevant chunks from private business data

LAYER 04Pillar 4

TOOLS

Allow model to interact with APIs, databases, and services

LAYER 05Pillar 5

ORCHESTRATION

Control execution loops, state management, and fallback paths

LAYER 06Pillar 6

PRODUCTION

Ensure system reliability, cost efficiency, guardrails, and low latency

"Once you understand these 6 layers, frameworks become simple implementation details."

SECTION 07 — WHAT YOU WALK AWAY WITH

WHAT YOU'LL HAVE AFTER 2 HOURS

This isn't just a certificate or a collection of videos. You'll walk away with real engineering deliverables.

01. Working GenAI Application

A real, functional application you build during the 2-hour session.

02. Complete Source Code

Clean, documented repository you can use directly as a project foundation.

03. Reusable Architecture

Mental model for LLM APIs, prompt context, and output parsing.

04. RAG Implementation Knowledge

Practical understanding of chunking, embeddings, and vector stores.

05. Agent Engineering Fundamentals

Function execution, tool-calling loops, and decision boundaries.

06. Production Engineering Roadmap

Actionable steps to optimize latency, costs, and guardrails for real users.

SECTION 08 — LEARNING COMPARISON

LEARN THE ARCHITECTURE. NOT THE HYPE.

Most AI courses teach tool syntax. This workshop teaches system architecture.

Typical Online AI Course

  • Framework-first (memorize SDK APIs)
  • Hours of academic math theory
  • Many disconnected toy demos
  • 40+ hours of passive video lectures

Techseed 2-Hour Sprint

  • Architecture-first (system design)
  • Code while learning (100% hands-on)
  • One coherent, functional application
  • 2 intensive hours of building
SECTION 09 — TARGET AUDIENCE

BUILT FOR SOFTWARE ENGINEERS

Designed specifically for developers who already write code.

Software Engineers

You know programming and want to add GenAI capabilities to your applications.

Backend Developers

You want to understand how LLMs, RAG, and tools fit into real backend systems.

Full-Stack Developers

You want to move beyond basic ChatGPT API calls and build actual AI features.

Technical Founders & Builders

You have an AI product idea and want the fastest path from concept to working code.

Qualifier: You should already be comfortable with basic programming and APIs.

SECTION 10 — INTENTIONAL EXCLUSIONS

THIS IS NOT FOR YOU IF...

We are here to build software. We skip the academic fluff.

Deep mathematical derivations of transformer attention weights
Academic machine learning research
Complete programming tutorials for total beginners
40-hour passive video lecture courses
Prompt tricks without application backend code
Framework collectors hopping between libraries
TECHSEED IT CONSULTING SERVICES

MEET YOUR INSTRUCTOR & FOUNDERS

Founded by senior engineers with extensive enterprise backend and AI consulting experience. We don't teach theory — we teach what actually ships in production.

Waseem Akram Shaikh
FOUNDER & LEAD ARCHITECT

Waseem Akram Shaikh

AI Engineer & Lead System Architect | 5+ Years Experience

Fintech & Backend SystemsMicroservicesProduction GenAI

"I've spent my engineering career building software where things like reliability, latency, cost, and scalability actually matter. You don't need to learn everything about AI. You need to understand the small set of engineering concepts that let you build with it."

Shaikh Iqbal Mohammad
CO-FOUNDER & SR. AI ENGINEER

Shaikh Iqbal Mohammad

Co-Founder & Senior AI Engineer @ Techseed Education

Production RAGTool AgentsVector Architectures

"Together under Techseed Education, we're building practical learning experiences for engineers who want to move from consuming technology to shipping with it in 2 hours."

Our Teaching Philosophy

"Learn the architecture first. Choose the framework second."

Connect LLM → Add RAG Context → Integrate Tools → Production Architecture

Instead of spending hours memorizing framework-specific APIs, we focus on the engineering decisions that remain relevant even when tools change.

TANGIBLE OUTCOMES

What You Will Build and Deploy

Design and architect production-ready GenAI pipelines from scratch
Deploy your first functional LLM backend service
Control model behavior with deterministic system instructions & JSON schemas
Deploy production RAG pipelines with custom context injection
Master embeddings and vector database integration patterns
Build tool-calling AI agent loops with strict execution boundaries
Evaluate frameworks like LangChain, LlamaIndex, and MCP Protocol
Follow a senior engineering post-workshop scaling roadmap
Ship custom AI features confidently without tutorial paralysis
Most importantly: You won't just memorize AI buzzwords. You'll architect, wire up, and deploy working systems.
EVERYTHING INCLUDED FOR ₹199

WHY ₹199?

Because the goal isn't to sell you another expensive course. The goal is simple: get developers to start building. ₹199 removes the friction.

2-Hour Live Build Sprint
Complete Source Code Included
RAG Implementation & Vector Retrieval
Tool-Calling / Agent Fundamentals
Architecture Blueprint & Mental Model
Full Recording Included
Lifetime Access & Source Code Updates
₹199One-Time Payment

No subscription. One-time access. Instant repository access after payment.

SECTION 13 — FAQ

FREQUENTLY ASKED QUESTIONS

SECTION 14 — FINAL STEP

YOU'VE WATCHED ENOUGH TUTORIALS.

Now build something.

BUILD & DEPLOY YOUR FIRST GENAI APPLICATION IN 2 HOURS.

₹199

One-time payment · Full Source Code · Recording Included

₹199 • ONE-TIME ACCESS
GenAI 2-Hour Sprint