Techseed Education

AboutUs — Founders & Leadership

Founded by Waseem Akram Shaikh and Shaikh Iqbal Mohammad, Techseed Education empowers software developers to build production-ready GenAI and RAG applications with absolute clarity.

Our Mission

To strip away AI buzzword confusion and give developers actionable mental models to build working GenAI systems in 3 hours.

Built by Engineers

We've spent years building backend systems, APIs, enterprise software, and LLM integrations. We teach what actually works.

1,400+ Developers Trained

Our hands-on workshop approach has helped software engineers transition into GenAI & RAG application development.

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.