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explainx.ai

Langflow: Build AI Workflows & Agents Without Code
OverviewProjectsAboutAgendaReviewsFAQ
← All workshops/Langflow
Live, hands-on workshopSep 7, 2026

Langflow: Build AI Workflows & Agents Without Code

Build AI Workflows & Agents Without Code

Yash ThakkerAI entrepreneur & educator

No code required. In one session you'll visually build a document Q&A chatbot, an AI agent that connects to live tools, and a multi-step workflow — drag, drop, run, done.

See the curriculum
  • Build a document Q&A chatbot without writing any code
  • Create an AI agent that uses real tools like web search and APIs
  • Chain agents together into a multi-step automated workflow
Explore the projects
Yash Thakker, AI entrepreneur & educatorLive with Yash

Next cohort coming soon

Explore the curriculum and find your next workshop.

Browse open workshops
Beginner friendlyRecordings includedLearn by doing, with your instructorSee the curriculum

Your take-home work

Leave with work you can use.

Build these with your instructor. Keep them, adapt them, and put them to work after the workshop.

How we’ll get there

01Start here

RAG Document Pipeline

A complete retrieval-augmented generation flow over your own documents — ingestion, chunking, vector storage, and a retrieval chain with tuned parameters that returns accurate, grounded answers.

See the session plan

02Make it yours

Tool-Calling Agent

A Langflow agent wired to real external APIs — with conditional tool selection, error handling, and conversation memory — ready to answer questions the LLM alone cannot.

Next cohort coming soon

Sep 7, 2026

Open workshops

03Make it yours

Multi-Agent Supervisor Flow

A production-grade supervisor-worker architecture: one orchestrator routes tasks to specialised sub-agents, aggregates their outputs, and returns a unified response — exported as a deployable REST API.

What you’ll take away

Three working AI pipelines built during the session, ready to deploy

Beginner-level workshop

Langflow is a visual canvas where you build AI workflows and agents by connecting blocks — no code, no boilerplate, no waiting on a developer. You drag in a document loader, connect it to an LLM, add a memory block, and your AI assistant is running. This workshop covers the full picture: how to read and answer questions from your own documents, how to give your agent real tools like web search and APIs, and how to chain multiple agents together so they collaborate on a task. Whether you're a founder, marketer, operations manager, or PM — if you can use a whiteboard, you can build in Langflow. By the end you'll have three working AI workflows built during the session, ready to share or deploy the same day.

  • Understand how Langflow's graph runtime maps to LangChain so you can debug and extend any flow
  • Build RAG pipelines with tuned chunking, embedding, and retrieval — not just a default demo
  • Connect live external APIs and tools as agent nodes with proper error handling
  • Design multi-agent supervisor architectures where agents delegate and collaborate
  • Deploy a Langflow workflow as a REST API ready for production traffic
  • Leave with three working flows you can adapt and ship the same week

The curriculum

What you’ll do in the session

4 hours live · Recordings included

Day 01Langflow — From Visual Prototype to Production Pipeline
  1. 01 Langflow Fundamentals — The Visual Runtime

    Understand how Langflow works: nodes, edges, components, and the underlying LangChain execution graph. Set up your Langflow environment, tour the component library, and build your first end-to-end flow — a basic LLM chat with memory. Learn how Langflow maps to LangChain concepts so you can debug and extend anything you build.

  2. 02 Building RAG Pipelines That Actually Retrieve

    Build a retrieval-augmented generation pipeline from the ground up — document loading, chunking strategy, embedding model selection, vector store ingestion, and retrieval chain assembly. Learn why naive RAG fails and how to tune chunk size, overlap, and retrieval parameters to get the right context into every response. Finish with a working Q&A pipeline over your own documents.

  3. 03 Connecting APIs, Tools, and External Data

    Extend your flows beyond static documents. Connect live APIs as tool nodes, wire in web search, build conditional routing so agents decide which tool to call, and handle errors gracefully when external calls fail. Add memory so your agent tracks conversation state across turns. Leave with a flow that reads from the real world and responds intelligently.

  4. 04 Multi-Agent Workflows and Production Patterns

    Design supervisor-worker multi-agent architectures in Langflow — one orchestrator delegates to specialised agents, aggregates results, and returns a final output. Learn Langflow's deployment options: API export, Docker, and cloud hosting. Add logging, trace your flow's execution, and review the patterns that separate a reliable production workflow from a fragile demo.

What you’ll leave with
  • ✓Build a RAG pipeline over your own documents with tuned retrieval
  • ✓Create a tool-calling agent that connects to a live API
  • ✓Design a multi-agent supervisor workflow and export it as a deployable API

Skills you’ll practice: Langflow graph runtime · RAG pipeline design · Chunking and embedding strategy · Vector store integration · Tool node wiring · Conditional routing · Conversation memory · Multi-agent orchestration · Langflow deployment · Flow observability

skills

Skills you’ll master

Everything you practise hands-on across the live sessions.

✓Langflow✓LangChain✓RAG Pipeline Design✓Vector Databases✓Embeddings✓Document Retrieval✓Tool Calling✓Multi-Agent Architecture✓Supervisor-Worker Pattern✓Conditional Routing✓Conversation Memory✓Flow Deployment✓API Export✓Flow Observability

Meet your instructor

Yash Thakker

Yash Thakker

Founder of AISOLO Technologies; AI entrepreneur & educator

350K+

Students

12+

Yrs exp

3

Startups

Yash Thakker is the founder of AISOLO Technologies and one of the most sought-after AI educators in the country. He's known for one thing above all: by the end of any session, students have already built something — no saving it for 'later.' His classes are built around real-life, happening-right-now examples, zero dry theory, and a teaching energy that makes complex things feel obvious. With over a decade shipping AI products across media, fintech, and edtech, Yash has delivered every learning format imaginable — in-person workshops, live bootcamps, online courses, and hybrid sessions — always exploring new ways to make learning land faster. He's obsessed with what learning looks like for this generation, now that AI changes what's even worth teaching. He has reached 350,000+ learners and is the creator behind Olly.social, BGBlur.com, Infloq.com, and explainx.ai.

explainx.aiolly.socialbgblur.comUdemy

faq

Frequently asked questions

Everything you need to know before enrolling.

No. Langflow is a visual canvas — you build by connecting blocks, not writing code. If you can use a tool like Notion or Figma, you can build in Langflow. No programming background required.

A Langflow account (free tier works for all exercises), an OpenAI or Anthropic API key, and a browser. No downloads or local setup — everything runs in the Langflow cloud.

Founders, marketers, operations managers, PMs, and anyone who wants to build AI-powered tools without depending on engineering. If you have a workflow problem you want to automate with AI, this workshop is for you.

Yes. Session 4 covers how to share your Langflow workflow, embed it in other tools, or export it so a developer can deploy it. You'll leave with something you can actually use or hand off.

The full session is recorded and available within 24 hours. Recordings are accessible for 1 year. All flow templates and component libraries are included regardless of live attendance.

Full refund up to 7 days before the first session. After that, transfer your seat to a future cohort. Email support@explainx.ai from your purchase email. Refunds go to the original payment method. If we cancel or fail to deliver the sessions, you receive a full refund regardless of timing.

Yes. Add up to 20 seats at checkout. Save 10% with 2 or more seats, 20% with 5 or more, or 30% with 10 or more. After payment, claim and assign seats by email in your dashboard. For larger groups or private sessions, email support@explainx.ai.

Two colleagues in everyday clothes working together at a laptop
Built around real work

Private team sessions

Train your team

Bring Langflow: Build AI Workflows & Agents Without Code to your company with examples, projects, and guidance shaped around the tools your team already uses.

  • ✓Live remote, in person, or hybrid
  • ✓Projects adapted to your team workflows
  • ✓Shared resources and a clear adoption plan
Plan team training

What students say

Real messages from students who trained with Yash across his live AI workshops and bootcamps.

“I'd tried building a RAG app in pure LangChain and spent a week on plumbing. In Langflow I had the same pipeline working in under an hour. The chunking and retrieval session alone was worth attending.”

Divya Nair

ML Engineer, Pune

“As a PM I couldn't write the LangChain boilerplate myself, but I could design and test the full agent flow in Langflow. I showed the working prototype to engineering and we shipped it in two weeks.”

“The multi-agent session was the highlight — Yash builds a supervisor-worker system live on screen. Watching it come together step by step made the architecture click in a way blog posts never did.”

“We were prototyping an internal knowledge-base chatbot. After this workshop I had a working RAG flow connected to our Notion docs by end of day. Deployed to our Slack bot the next morning.”

Tom Bergström

Product Manager, Stockholm

Kenji Watanabe

AI Developer, Tokyo

Priya Iyer

Full-Stack Developer, Bangalore