Sathvik Pilyanam@slowerpath1669

Boundary Forge is a model-agnostic AI safety pipeline that helps enterprises deploy LLMs with measurable confidence. Instead of relying on manual red-teaming or hoping a system prompt is enough, Boundary Forge automatically attacks a model, identifies where it behaves unsafely or inconsistently, and converts those discovered failures into runtime guardrails. For this hackathon, we demonstrated Boundary Forge using Qwen 2.5-72B on AMD Developer Cloud with AMD MI300X. Qwen powered the adversarial red-team workflow and was also the model under test, allowing the system to expose real behavioral failure boundaries such as jailbreak attempts, policy drift, unsafe financial guidance, KYC bypass, fraud patterns, coercion signals, asset concealment, and inconsistent refusals. The pipeline works in five stages: generate adversarial probes, run high-throughput model inference, mathematically detect boundary failures, compile those failures into semantic safety rules, and enforce them through middleware before risky prompts reach the LLM. This creates a practical enterprise safety layer that can block, flag, or ask for clarification in real time. The important point is that Boundary Forge is not tied to one model. Qwen 2.5-72B was used to demonstrate the system, but the architecture can benchmark and harden other open-source or proprietary models as well. The goal is to improve models exactly where they fail and make model evaluation repeatable across different deployments. In our AMD Cloud production run with Qwen 2.5-72B, Boundary Forge generated 1,009 unique adversarial probes, fired 4,036 total inferences, discovered 25 boundary failures, and compiled 15 semantic safety rules. The middleware intercepted 68% of known attacks and reduced the effective failure rate from 2.48% to 0.79%. Boundary Forge turns AI safety into an automated engineering workflow: attack, measure, learn, protect, and benchmark again.

Grab your ideas, spin up compute, and start building what’s next! Start with $100 in AMD Developer Cloud credits and begin building right away. Get access to hands-on tutorials, workshops, and curated learning resources to help you build faster and go further. To unlock credits and join the hackathon, sign up for the AMD AI Developer Program. 🤝 Go solo or team up — ship something real. 💰 $21,500+ total prize pool & 1 × AMD Radeon™ AI PRO R9700 GPU up for grabs. 📍 On-site Venue (May 9-10): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 📍On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑‍💻 Developers, builders, and innovators - bring your boldest ideas and let’s turn them into real AI systems on AMD.

Build solutions that improve how software is built. Work with an AI that understands your codebase, helping you reduce repetitive work and build with real context. ⏳ Build your project in 48 hours. 🚀 Get hands-on with IBM Bob and explore how AI fits into real development workflows before it becomes standard. 💡 Build tools and workflows that developers would actually use. ⭐ Learn directly from experts throughout the event. 🤝 Join a team or build solo. 💰 Prize pool: $10,000 🧑🏻‍💻 Register before the Kick-Off Stream and start building with Bob.