Orchestrate

Saai SyvendraComputer Science & Engineering

I entered HackerRank Orchestrate, a global hackathon, mostly out of curiosity. I wanted to see how HackerRank would run a hackathon that openly tells you to use AI. I ended up winning it and learning a lot more than I expected. The task: build a terminal support agent for HackerRank, Claude, and Visa in 24 hours, then defend it to an AI judge. 12,885 people registered, from around 50 countries.

Bhavya KhatriAI Engineer building agentic systems @ Mindtickle · HackerRank Orchestrate Top 2

I came 2nd. HackerRank Orchestrate wasn’t a typing-speed contest. It graded four things end-to-end: the agent you built, the tickets it actually handled, the way you directed your coding tools, and a 30-minute live defence in front of an AI judge. That last one mattered. It is one thing to ship an agent; it is another to explain — under questioning — why your routing, your memory, and your fall-back paths are the right ones. Agentic engineering is becoming a real, measurable skill. "Used Copilot" is not the bar anymore. Designing the loop is. Top 2 of 12,885 across 48 countries is a moment to mark. Then back to work — the standard moves fast.

Faraaz KhanSolutions Engineer | Data & AI Systems Architect | High-Performance Backend & Analytics Infrastructure | 10+ Years in Secure, Compliance-Driven Platforms

I just ranked #3 in HackerRank Orchestrate. 24 hours. One challenge. Build an AI agent that resolves real customer support tickets. No hallucinations allowed. No guessing. Reply or escalate. Here’s what got me to the podium: I didn’t pick the smartest model. I built the smartest system. A 6-agent pipeline where no single LLM makes the final call. No LangChain. No frameworks. 3 npm packages. Just 400 lines of orchestration. The biggest takeaway: In production AI, the system around the model matters more than the model itself.

Ahtasham Ul HaqAI Engineer | Python Developer | 3rd Globally @MIT’25 | 15× Int’l Hackathons | Building Production-level LLM Applications

I thought I was building a chatbot. I wasn’t. I was building a system that knows when to stay silent. I participated in Orchestrate organized by HackerRank — a decision system for HackerRank, Anthropic Claude, and Visa scenarios. Understand the issue. Pull trusted docs. Check risk. Respond or escalate. No hallucinations. While building it a few things became clear: Retrieval > creativity. Confidence > coverage. Escalation > risk. Systems > prompts. Good systems know when to stay silent.

Sarthak SinghBackend & Full-Stack Engineer | Java · Python · Spring Boot · FastAPI · React | Agentic AI | Published Researcher – ICTIS 2026

Just built a multi-domain agentic support triage system for the HackerRank Orchestrate Challenge — one of the most interesting AI engineering problems I’ve worked on. The challenge: handle support tickets across 3 completely different ecosystems — HackerRank, Claude, and Visa — using only a local support corpus. No external knowledge. No hallucinated policies. The hard part wasn’t building the pipeline — it was making it trustworthy. So I focused on safe escalation, deterministic behavior, and zero hallucination. It completely changed how I think about agentic AI. The goal isn’t just "answer the question" — it’s knowing when not to answer and why.

Sujal GuptaB.Tech IT Undergraduate | GSSoC’26 Contributor | MERN & Full-Stack Development

Elated to share that I finished #92 out of 1,349+ participants from 48 different countries in the HackerRank Orchestrate Hackathon! The challenge was to build a production-ready AI Support Triage Agent. My approach focused on deterministic safety and infrastructure resilience — building an agent smart enough to know when it doesn’t know an answer. Pre-retrieval risk gating, domain-aware RAG, a Pydantic circuit-breaker, and a multi-LLM fallback across Groq, NVIDIA NIM, and Gemini. Building reliable AI systems isn’t just about writing a clever prompt — it’s about wrapping unpredictable AI models in rock-solid, predictable software engineering logic.

Saai SyvendraComputer Science & Engineering

I entered HackerRank Orchestrate, a global hackathon, mostly out of curiosity. I wanted to see how HackerRank would run a hackathon that openly tells you to use AI. I ended up winning it and learning a lot more than I expected. The task: build a terminal support agent for HackerRank, Claude, and Visa in 24 hours, then defend it to an AI judge. 12,885 people registered, from around 50 countries.

Bhavya KhatriAI Engineer building agentic systems @ Mindtickle · HackerRank Orchestrate Top 2

I came 2nd. HackerRank Orchestrate wasn’t a typing-speed contest. It graded four things end-to-end: the agent you built, the tickets it actually handled, the way you directed your coding tools, and a 30-minute live defence in front of an AI judge. That last one mattered. It is one thing to ship an agent; it is another to explain — under questioning — why your routing, your memory, and your fall-back paths are the right ones. Agentic engineering is becoming a real, measurable skill. "Used Copilot" is not the bar anymore. Designing the loop is. Top 2 of 12,885 across 48 countries is a moment to mark. Then back to work — the standard moves fast.

Faraaz KhanSolutions Engineer | Data & AI Systems Architect | High-Performance Backend & Analytics Infrastructure | 10+ Years in Secure, Compliance-Driven Platforms

I just ranked #3 in HackerRank Orchestrate. 24 hours. One challenge. Build an AI agent that resolves real customer support tickets. No hallucinations allowed. No guessing. Reply or escalate. Here’s what got me to the podium: I didn’t pick the smartest model. I built the smartest system. A 6-agent pipeline where no single LLM makes the final call. No LangChain. No frameworks. 3 npm packages. Just 400 lines of orchestration. The biggest takeaway: In production AI, the system around the model matters more than the model itself.