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Sarmad Khan
Sarmad Khan

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How I Built EchoAI with Kiro IDE – A Game-Changer for Productivity

Introduction

Every developer knows the frustration of juggling specs, debugging, and endless boilerplate issues. During the recent hackathon, I set out to build EchoAI, an intelligent chatbot platform that businesses can embed on their websites in minutes.

What made this project possible wasn’t just the idea—it was the Kiro IDE, which changed the way I worked. From planning to execution, Kiro gave me the tools to stay focused, eliminate repetitive errors, and deliver a production-ready product within the hackathon timeline.

  • In this post, I’ll walk you through:
  • The inspiration behind EchoAI
  • What EchoAI does and why it matters
  • The role of Kiro in building it
  • Challenges I faced and how I overcame them
  • Key lessons I learned along the way

Inspiration: The Problem with Chatbots Today

Businesses often rely on chatbots for customer support, but most solutions fall into one of two categories:

  1. Rigid – They can only handle predefined questions.
  2. Complicated – They take too much time to set up and integrate.

I wanted to create something that was both simple to launch and powerful enough to adapt to real conversations. That vision became EchoAI.

What EchoAI Does

EchoAI is a chatbot platform designed to be:

  • Easy to deploy: Create, customize, train, and embed with a single script.
  • Intelligent: Understands sentiment, extracts topics, and suggests next questions.
  • Customizable: Train it with company data (PDFs, docs, or custom prompts).
  • Practical: Add FAQs instantly and display them in the chatbot.
  • Reliable: Save and track conversation history tied to authenticated users.
  • Action-driven: Trigger automations that integrate with Slack, HubSpot, and Google Sheets.
  • Human-ready: A helpdesk dashboard lets teams monitor live chats, step in anytime, or allow users to hit a “Talk to Human” button.

In short, EchoAI is more than a chatbot—it’s a workflow and engagement platform.

How We Built It

The technical backbone of EchoAI includes:

  • FastAPI for backend services
  • Hugging Face models for NLP tasks like sentiment analysis and topic extraction
  • Custom automation engine for triggers and workflows
  • Integrations with third-party apps like Slack, HubSpot, and Google Sheets

But the real productivity boost came from Kiro IDE.

How Kiro Changed the Game

1. Specs that Guided the Entire Build

Instead of diving into code blindly, I started with an MVP spec prompt in Kiro. It generated a clear task.md roadmap that broke the build into actionable steps. This kept me focused and prevented the common “what do I do next?” problem.

2. Fixing Errors with “Vibes”

Errors are inevitable, but Kiro’s vibes feature allowed me to resolve them quickly—sometimes across entire files—without wasting hours. This was especially helpful when working under the tight hackathon deadline.

3. Automating My Development Workflow

I dislike repetitive TypeScript issues (any types, unused variables, no-var errors). To solve this, I built a custom Kiro hook that automatically checked recently updated files for such problems and fixed them instantly. This saved enormous amounts of time.

4. From Concept to Production

With a guided spec, rapid debugging, and automated checks, I was able to move EchoAI from idea → MVP → production faster than I ever thought possible.

Challenges I Faced

Even with Kiro, some areas were tricky:

  • Model integration: Finding the right Hugging Face model for FastAPI and optimizing it was challenging.
  • Workflow automation: Detecting the right triggers inside conversations required iteration and testing.
  • Third-party integrations: Making sure Slack, HubSpot, and Google Sheets worked seamlessly took extra effort.

Accomplishments I’m Proud Of

  • Delivering a production-ready chatbot platform within hackathon limits.
  • Implementing advanced features like sentiment detection and human handover.
  • Building a workflow automation engine that integrates with real-world tools.
  • Using Kiro not just as an editor, but as a true partner in development.

Key Lessons Learned

  • A spec-first approach (via task.md) keeps development efficient and structured.
  • Automating repetitive tasks frees mental bandwidth for solving bigger problems.
  • Chatbots create more impact when they are intelligent, proactive, and integrated with business workflows.

Final Thoughts

Kiro IDE fundamentally changed how I approach building software. Instead of spending time wrestling with errors or second-guessing my workflow, I was able to focus on creating real value.

EchoAI is the proof: in just a short time, I built a platform that combines intelligent conversations, real-time human support, and workflow automation—all thanks to the productivity boost from Kiro.

If you’re serious about shipping faster and smarter, Kiro is worth trying. It’s more than an IDE—it’s a game-changer for developers.

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