DevCollab

Inspiration

What Inspired Us?

Honestly? We didn’t get into the world of hackathons with some grand vision to change the world. We started because everyone else was doing it.

We’re engineering students. We saw our friends posting winning certificates on LinkedIn, staying up all night with Red Bull, and building "cool" stuff. We had major FOMO. So, about a year ago, we jumped in—mostly to see if we could, and partly because we didn't want to be the only ones left behind.

But after dragging ourselves through a few events, the hype wore off and reality hit. We learned three hard truths that no tutorial tells you:

Ideas > Tech Stack: Judges don't care about your fancy tech stack; they care about your idea. Clean code won't save a boring concept.
Shipping is the Real Challenge: Ideas are cheap. Winners are those who can show a working (even if "held-together-with-tape") MVP when the clock runs out. Perfection kills projects.
The Boss Fight is Chaos Management: The hardest part isn't the code—it's coordination. We wasted time with three people building a login page and zero people building the database.

The Birth of DevCollab

We realized there are a million platforms to find a hackathon, but zero platforms to actually help you survive one.

We built DevCollab (powered by the Gemini 3 API) for the 16–24 age group: the first-timers and students staring at a blank IDE, trying to turn a cool idea into a submittable project under a brutal time constraint.

What it does

Basically, DevCollab is the AI version of that one unlucky friend in every group project—the "Team Leader" (which happens to be me for our group).

You know the struggle. In every hackathon, there is always one person who ends up doing everything except coding: finding the right hackathon, hunting for teammates, assigning tasks, keeping everyone on track, and explaining the idea 50 times. It’s exhausting.

DevCollab automates the chaos. It handles every part of the hackathon journey that isn't writing code, so you can actually focus on building.

1. Intelligent Team Formation (The "No-Keyword" Search)

Standard platforms rely on dumb keyword matching. If you search "Node.js", you get everyone who mentioned "Node" once in their bio three years ago. It’s noise. We used Gemini 3’s reasoning capabilities to fix this.

The Input: You type naturally: "I need someone who is good at backend and can handle API integration quickly."
The Match: The AI ignores the buzzwords and looks for intent. It understands that "API integration" implies specific backend skills, matching you with a builder who fits the role, not just the search bar. It saves you from manual filtering when you just need a teammate who ships.

2. The "MVP Machine" (AI Co-Pilot Page)

Once the team is formed, the AI Co-Pilot takes the wheel. To stop the project from dying in "tutorial hell," we hard-coded the hackathon lifecycle into five distinct stages:

Stage 1: Manage Team (The Setup)

The hardest part is starting. You add your members and finalize the problem statement. The AI immediately locks in the context—who is working on what, and exactly what problem you are solving. No more "Wait, what are we building?" two hours in.

Stage 2: Research (The Deep Dive)

Instead of random Googling, the AI analyzes your problem statement and identifies the exact topics you need to research. It uses Gemini 3’s reasoning to distribute these research topics to the team members best suited for them (e.g., "You check the API docs," "You check the frontend feasibility"), cutting down hallucination and wasted time.

Stage 3: Ideation (The Socratic Brainstorm & Pitch)

Brainstorming usually devolves into random shouting matches. We fixed that.

Sequential Interrogation: Instead of generic questions, the AI analyzes your research and forces the team to answer why, who, and how in a structured order.
The Project Pitch: You dump every detail of your solution—every feature, every edge case—into the system. The AI combines your structured answers with this raw input to finalize the concept.

Stage 4: PRD (The Goldmine)

The AI compiles everything into a Product Requirements Document (PRD).

The "Source of Truth": This doc contains everything from user personas to technical specs. You never have to explain the context to the AI (or a new teammate) again. You just attach this doc, and you’re done.

Stage 5: Implementation (The Auto-Manager)

This is the killer feature. The AI takes that PRD and generates a Master To-Do List.

Auto-Assignment: It iterates through the list and assigns tasks to the relevant team member based on their role.
Sectioning: It splits the work into "Sprints"—Setup, Core Build, Testing.
Panic Control: It turns a chaotic 24-hour panic into a calm, step-by-step checklist.

Accomplishments that we're proud of

Making something which is unique and powerful, and honestly making the lives of those people easier, who no one is focusing on, i.e., early age tech enthusiasts new to the world of hackathons.

What's next for DevCollab

automated AI scan for team, sees what is lacking based on the role and skills of the team, and suggests the best candidates who are looking for the team, and fit the role
Enabling maximum parallel working by optimizing the allotted tasks, such that people can work most optimally and also follow the sequential order in which the project needs to be made. This can be done by using AI to make a DAG of the generated to-do list, and using Kahn's algorithm to optimize the task allotment