Hackathons are designed to compress creativity into a short window, but in practice, most of them fail in a predictable way. Energy is high, ideas are ambitious, and demos look promising—yet very few projects survive beyond the event itself. This gap is especially visible in hackathons with non-technical or mixed-skill participants, where teams often struggle to complete backend logic, integrate AI meaningfully, or deliver a working end-to-end product.
On January 11, 2026, in the heart of Singapore, the Agent Forge Hackathon set out to prove that building software isn't just for career coders anymore. Co-hosted by Momen and AI Builders, the event gathered 80 solo builders from diverse backgrounds, the vast majority of whom were non-technical or semi-technical. The goal was ambitious: take an idea from a blank page to a fully functioning AI application in just seven hours.
The rules were simple but strict: by the 3:30 p.m. submission deadline, builders had to present a live, two-minute demo of a real user journey that actually worked. There was a hard "no faking it" policy—no placeholder logic, no mock payments, and no slide-only prototypes.
What This Hackathon Was Designed to Solve
The challenge with many hackathons isn’t a lack of great ideas; it’s that the format often rewards surface-level progress. When time is tight, it’s easy to spend the bulk of those hours polishing the "look and feel" or crafting a perfect pitch. Meanwhile, the core systems—the data models, secure workflows, and actual AI logic—often remain disconnected or incomplete. This results in "fragile" demos that, while beautiful on screen, rarely have the technical foundation to continue or evolve after the event ends.
This hackathon was designed with a different priority: optimizing for completion over novelty. Rather than chasing the most futuristic concept, the focus was on solving real operational problems through specific challenges like Client Intake Automation, Feedback Analysis, Knowledge-base Q&A, and Subscription Tools. These are practical solutions that require robust backend logic to function at all. The ultimate goal was not to measure how creative an idea could be, but to prove that it could realistically operate as a stable, functional product.
How Builders Actually Built in One Day
The day kicked off with a focused workshop on building agentic AI apps without code, stripping away the mystery of how data, logic, and AI agents connect within a real-world product. Once the groundwork was laid, the room shifted entirely into "build mode" for the remainder of the day.
Participants were free to choose their frontend tools, with many opting for Cursor or Lovable to generate interfaces quickly. However, the backend for each project—including databases, workflows, AI agents, permissions, and payments—had to be built on Momen. This constraint removed a common source of uncertainty. Builders did not need to decide which services to stitch together or how to make them talk to each other. Instead, they could focus on defining a single user flow and making it work end to end.
Throughout the afternoon, live technical support was on standby to keep the wheels turning. Instead of hitting a wall when a data model got complicated or an AI workflow stalled, builders could get instant answers and keep moving. This high-support environment changed the way people worked; instead of getting lost in "feature creep," builders focused on making their core idea rock-solid and reliable.
By the time submissions closed at 3:30 p.m., around 10 projects were ready for live demos, each required to show a complete user journey within a strict two-minute format.
Why a Backend-First Approach Made Shipping Possible
One of the clearest lessons from the event was that backend infrastructure matters more in hackathons than it is usually given credit for. When backend systems are fragmented across multiple tools, non-technical builders spend a disproportionate amount of time dealing with integration issues or avoiding them altogether. This often leads to shallow prototypes that cannot support real users.
Using Momen as a unified backend changed this dynamic. Builders could define data models, connect AI agents to real inputs, enforce permissions, and trigger workflows without switching contexts. When paired with flexible frontend tools like Cursor or Lovable, this created a practical division of labor: the frontend handled presentation, while the backend handled everything required for the product to actually function.
In a time-constrained environment, this reduced the number of irreversible mistakes. Builders were far less likely to hit a wall where a missing backend feature forced them to abandon their project at the last minute. Instead, they could easily adjust their scope while keeping the core system intact, ensuring that their final demo was a stable, working product rather than just a visual concept.
What the Winning Teams Built
The winning projects reflected this emphasis on functional completeness rather than novelty.
The first-place project, Investment Lead Analyser by Ramesh, was built under the Client Intake Automator challenge. Users could input their planned investment amount and risk preference, and the system evaluated lead quality and whether to offer follow-up services, demonstrating real qualification logic rather than a scripted AI conversation.
Second place went to Feedback Analyzer by Chianhao, created for the Smart Feedback Loop challenge. The project analyzed sentiment from individual feedback submissions and generated insight reports that could help product teams identify areas for improvement, connecting user input directly to actionable output.
Third place was awarded to AI Assistant for KB Conversations by YangFeng, built for the AI Knowledge Concierge challenge. The assistant answered questions based on the builder’s own PDF-based knowledge base, showing how document-grounded AI could be deployed quickly with accurate context.
What This Means for Hackathons and Builder Programs
This hackathon reinforced a simple but often overlooked point: non-technical builders can ship real AI products when infrastructure supports completion rather than experimentation alone. Better tools do not replace good ideas, but they make it possible to test those ideas under realistic constraints.
For universities, communities, and organizers running hackathons or workshops, the implication is clear. If the goal is higher completion rates and projects that survive beyond demo day, backend infrastructure should be treated as a first-class concern, not an afterthought.
Let’s build something real together
At Momen, we love seeing ideas actually cross the finish line. We are actively looking to partner with builder communities and educational programs that want to foster this kind of "outcome-focused" creativity.
If you’re interested in co-hosting a workshop or a hackathon, we’d love to support your event with free Momen credits and technical guidance.
Organizers: Drop us a note at hello@momen.app to start a conversation.
Students & Educators: We’ve got your back—visit our Education page to grab a 50% discount and start building.
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