Forem: Ashwinhegde19

I won my first hackathon by building something I barely understood

Ashwinhegde19 — Fri, 13 Mar 2026 16:34:08 +0000

A few weeks ago I was using OpenClaw to set reminders and run basic cron jobs.

That's it. Nothing impressive.

Then I walked into the HSRFC x OpenClaw Builders event in Bengaluru. 4 hours, real constraints, ship something or go home.

I had never built a complete agent before. No plan. Just enough curiosity from weeks of tinkering to figure things out as I went.

What I built
A GitHub Issue Resolver — an autonomous agent that discovers, ranks, and analyzes open GitHub issues. Fully local, no cloud, no servers. Everything runs on your own machine.

The idea was simple: point it at a repo, and it would:

Pull open issues
Rank them by complexity and impact
Suggest fixes with context from the actual codebase
Nothing groundbreaking on paper. But getting an agent to do all of that reliably, in 4 hours, with tools I'd barely used before — that was the real challenge.

What actually happened
Did it break multiple times? Yes.

Was I debugging in the last 20 minutes? Also yes.

There's a specific kind of stress that comes from knowing your demo is in 15 minutes and your agent just threw an error it hasn't thrown before. You don't think clearly. You just try things faster.

The thing that saved me wasn't some clever architecture decision. It was that I'd spent enough time tinkering with OpenClaw beforehand that I had intuition for where things go wrong. Not knowledge — intuition. There's a difference.

The lesson
Still took first place.

But the lesson wasn't about the win. It was this — you don't need to know everything before you start. You just need enough curiosity to keep going when it breaks.

I think a lot of developers (myself included) wait too long to build things. We want to understand the full picture first. Read the docs. Watch the tutorials. Make sure we won't look stupid.

But the people who build interesting things are the ones who start before they're ready and figure it out along the way.

What's next
The project still needs work. The ranking algorithm is basic, the error handling is rough, and there are edge cases I haven't touched. But it's real, it runs, and it's on ClawHub.

I'll probably keep hacking on it. Maybe write about the technical side in a follow-up post.

Built with OpenClaw 🦞

The AI Learning Trap: Why Copy-Pasting Code Is Costing You

Ashwinhegde19 — Fri, 30 Jan 2026 08:56:01 +0000

I just read a wild study from Anthropic. They had developers learn a new Python library—half with AI help, half without.

The AI group finished 2 minutes faster.

But scored 17% lower on the test. Nearly two letter grades.

Here's what hit me: the biggest gap wasn't writing code. It was debugging. You know, that thing you need when AI hallucinates a API call.

What Separated the Winners

The devs who did learn didn't use AI less. They used it differently:

Asked "why does this work?" after getting code
Requested explanations alongside solutions
Posed conceptual questions while coding solo

The ones who failed treated AI like Stack Overflow on steroids—copy, paste, pray.

The Real Talk

AI is incredible for stuff you know. Anthropic's own data shows 80% speedups on familiar tasks.

But learning? That's different. Learning requires friction. Getting stuck. That 20-minute rabbit hole that finally clicks.

AI skips the rabbit hole. You get the code, miss the lesson.

My Take

I'm not ditching Claude. But I'm changing how I use it.

Generate → Then comprehend.

Ask one extra question. Type it out yourself once. Suffer through the error message before asking for help.

Your debugging skills are the ceiling on how much you can trust AI. Don't let that ceiling drop.

What about you? Has AI made you faster, or has it made you think less?

Why "Just Coding" Won't Save You in 2026 (My Take on Akshay Saini's Advice)

Ashwinhegde19 — Sun, 28 Dec 2025 17:57:50 +0000

I recently watched a video by Akshay Saini titled "The Software Engineer Who Will WIN in 2026," and honestly, it hit home.

As developers, we often get stuck in the loop of learning the "next new framework," but Akshay points out a hard truth: Coding itself is no longer the differentiator.

With AI models writing cleaner, faster code every day, the bar has shifted, but here are my top takeaways and why I think he’s 100% right.

1. The Rise of the "Full Stack AI Engineer"

For years, we've categorized ourselves: "I'm a Frontend Dev" or "I'm a Backend Dev." Akshay argues that in 2026, those silos will be dead.

Because AI can handle the heavy lifting of syntax and boilerplate, we need to become orchestrators.

Frontend devs: You need to understand how the backend and deployment pipelines work.
Backend devs: You need to understand UI/UX and client-side logic.

The goal isn't to know everything by heart, but to use AI to bridge your skill gaps and build the whole product. As he said, we need to use AI to 10x our productivity, not just to write a function faster.

2. Stop Closing Tickets, Start Taking Ownership

This was the point that resonated with me the most. We often measure our day by how many Jira tickets we moved to "Done."

But in a world where code is cheap, value is expensive.

"If your code is not creating value, it's just garbage." — Akshay Saini

The engineers who will "win" in 2026 are the ones who care about the product outcome, not just the code output. We have to move from being "task completers" to "problem solvers."

3. System Design is the New King

If AI is writing the implementation, what is left for us? Decisions.

System Design is becoming the most critical skill because AI can suggest five different ways to build a feature, but it can't always tell you which one is right for your specific constraints, security needs, or scale.

The human element is now about architectural trade-offs. We move from writing the "how" to deciding the "what" and "why."

My Verdict

I've felt this shift happening for a while. It’s scary to think that "being a good coder" isn't enough anymore, but it's also liberating. It means we can stop stressing over memorizing syntax and start focusing on building cool, valuable things.

I’m planning to pivot my learning path to focus more on System Design and AI orchestration rather than just deep-diving into another JS framework.

What do you think? Is AI making pure coding skills obsolete, or is this just hype?

Let me know in the comments!