DEV Community: Tirupathi Sekhar

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Tirupathi Sekhar — Sat, 03 Oct 2026 04:13:32 +0000

Tirupathi Sekhar

Oct 3

From Hackathon Idea to Working Prototype: What I’ve Learned

#ai #studentdeveloper #hackathon #buildinpublic

4 min read

From Hackathon Idea to Working Prototype: What I’ve Learned

Tirupathi Sekhar — Sat, 03 Oct 2026 04:13:11 +0000

I was wrong.
The hardest part is taking an idea that sounds exciting and turning it into something that actually works.
As a Third-year B.Tech Data Science student, I’ve been exploring AI, backend development, APIs, databases, deployment, and different technologies through projects and hackathons. Along the way, I’ve learned that a hackathon is not just about building something quickly. It is about learning how to turn a problem into a solution.

Start With the Problem, Not the Technology One mistake I made early was starting with technology. “Let’s use AI.” “Let’s build an app with React.” “Let’s use a database.” But technology alone doesn't make a good project. Now I try to start with: What problem are we solving? Then I ask:
Who has this problem?
Why does it matter?
How are people solving it today?
Can technology actually improve the process?
What is the simplest version we can build? This changed the way I approach project ideas.
Don't Try to Build Everything Hackathons have limited time. It is very easy to create a huge feature list:
Authentication
AI model
Mobile app
Admin dashboard
Payment system
Notifications
Analytics
Maps
Cloud deployment And suddenly the project has become much bigger than the time available. I’ve learned to focus on an MVP — Minimum Viable Product. The first question should be: “What is the smallest version of this idea that demonstrates the solution?”

Build that first.
Then add features if time allows.

Architecture Matters As I started working on backend projects, I realized that writing code is only one part of development. You also need to think about:
How will the frontend communicate with the backend?
Where will the data be stored?
How will users authenticate?
How will different services communicate?
What happens when something fails?
How will the application be deployed? For example, while designing one of my projects, I started thinking about separate services for different types of users instead of putting everything into one huge backend. That experience taught me an important lesson: Good architecture starts with asking the right questions before writing thousands of lines of code.
Things Will Break This is probably one of the biggest lessons I've learned. Packages fail. Dependencies conflict. APIs return unexpected responses. CORS causes problems. Deployment doesn't work. Environment variables are missing. The application works locally but breaks on the server. At first, these problems were frustrating. Now I see them differently. Every error is giving me information about how the system actually works. Instead of immediately searching for a complete solution, I try to understand: What exactly failed? Then: Why did it fail? And finally: How can I prevent the same problem next time?
GitHub Is More Than Code Storage I started using GitHub mainly to store my projects. Over time, I realized it can become a public record of my learning. A good repository can show:
What I built
Why I built it
How it works
Technologies I used
How to run it
What I learned
What I plan to improve This is one reason I’m trying to build my projects publicly instead of keeping everything on my computer. Your GitHub can tell a story about how you are growing as a developer.
A Working Demo Is Powerful A project can have a great idea and thousands of lines of code. But showing someone a working prototype makes the idea much easier to understand. During a hackathon, I would rather demonstrate: “Here is the problem → here is our solution → let me show you how it works.” than spend the entire presentation explaining what the project could do. That is why I now think about the demo while building the project.
Documentation Is Part of the Project Earlier, I considered documentation something to write at the end. Now I understand that good documentation is part of good development. A simple README should answer: What is this project?

Why does it exist?

How does it work?

How can someone run it?

What technologies are used?

What are its limitations?

Good documentation also helps your future self.
A few months later, you may forget why you made a particular decision. Your README and code comments can save a lot of time.

Don't Be Afraid to Ask for Help Hackathons are also about collaboration. You don't need to know everything. If you don't understand something, search for it. Read documentation. Ask teammates. Look at examples. Experiment. Make mistakes. Try again. One of the biggest advantages of participating in hackathons is being surrounded by people who are also trying to solve problems.
Focus on Learning, Not Just Winning Of course, everyone wants their project to do well. But for me, especially as a first-year student, the bigger value is what I learn during the process. Maybe I learn:
A new framework
A new API
How authentication works
How databases work
How deployment works
How to use Git properly
How to explain a technical idea
How to work with a team Even if the project doesn't win, those skills remain with me.
Build → Break → Fix → Learn → Repeat This is probably the simplest way I can describe my current approach to development. Build something. Break something. Understand why it broke. Fix it. Learn from it. Build something better. I'm still at the beginning of my journey. I don't know every framework. I don't know every programming language. I don't understand every part of software engineering yet. And that's okay. I'm trying to learn by actually building. My current goal isn't to become someone who knows everything. It's to become someone who can look at a problem and say: “I don't know how to solve this yet, but I can figure it out.”

That's what hackathons are teaching me.
And that's what I want to continue learning.

Building Observability-First Microservices in Go with GoFr

Tirupathi Sekhar — Mon, 21 Sep 2026 04:12:02 +0000

When developing backend microservices in Go, standard libraries and minimal routers give you complete control, but assembling production essentials—structured logging, OpenTelemetry tracing, Prometheus metrics, and datasource health checks—often leads to heaps of repetitive boilerplate.

Enter GoFr: an opinionated Go framework designed to simplify microservice architecture while providing built-in observability and container-ready defaults.

Here is a hands-on look at what makes GoFr stand out and how quickly you can get a production-ready REST service running.

What Makes GoFr Different?
Built-in Observability: Structured logs, OpenTelemetry traces, and runtime metrics work out of the box without requiring dozens of external middleware imports.

Standardized REST Routing: Idiomatic response handling and request binding that adhere strictly to REST conventions.

Datasource Health Checks: Native support for SQL, NoSQL, and key-value stores with integrated pinging and connection lifecycle management.

Zero-Downtime Reconfiguration: Built-in ability to adjust log levels dynamically at runtime without restarting processes.

Quickstart: Building an API in GoFr

Prerequisites & Setup Ensure you have Go installed, then initialize your project and pull the framework:

mkdir gofr-quickstart && cd gofr-quickstart
go mod init gofr-quickstart
go get -u gofr.dev/pkg/gofr

Writing the Service Create a main.go file with a basic health and entity route:

'''
Go
package main

import (
"errors"
"gofr.dev/pkg/gofr"
)

type User struct {
ID int json:"id"
Name string json:"name"
Role string json:"role"
}

func main() {
// Initialize a new GoFr application
app := gofr.New()

// Simple greeting endpoint
app.GET("/greet", func(ctx *gofr.Context) (any, error) {
    name := ctx.Param("name")
    if name == "" {
        name = "Developer"
    }
    return "Hello, " + name + "!", nil
})

// JSON response endpoint with parameter binding
app.GET("/users/{id}", func(ctx *gofr.Context) (any, error) {
    id := ctx.PathParam("id")
    if id != "1" {
        return nil, errors.New("user not found")
    }

    return User{
        ID:   1,
        Name: "Alex Mercer",
        Role: "Software Engineer",
    }, nil
})

// Starts server on port 8000 by default
app.Run()

}
'''

Running and Testing Start your microservice:

Bash
go run main.go
Test your endpoints using curl:

Bash

Greet endpoint

curl http://localhost:8000/greet?name=GoDeveloper

User endpoint

curl http://localhost:8000/users/1
Notice the terminal output: every incoming request automatically generates structured logs containing trace IDs, latency metrics, and HTTP status codes with zero custom logging logic.

Final Thoughts
For engineering teams aiming to scale Go services efficiently without spending days configuring tracing exporters and routing boilerplate, GoFr offers a cohesive, battery-included framework. It bridges the gap between raw HTTP handlers and full-blown microservice platforms.

Repository: github.com/gofr-dev/gofr

Documentation: gofr.dev