This article is a field report from the second Build Small Hackathon, describing v2 of the 'Thousand Token Wood' simulation. In this version, each of the five woodland creature agents is powered by a different small language model (from OpenAI, OpenBMB, NVIDIA, and a fine-tuned Qwen). The player takes on the role of a shadow financier, able to lend, tip (truthfully or falsely), short, bribe, and broker alliances. The article details engineering challenges: serving layer heterogeneity (vLLM, CUDA toolkit), per-model quirks, a tolerant JSON parser, and a critical information asymmetry firewall to prevent secret flags from leaking into agent prompts. Persistent memory is handled via bounded summaries rather than raw history to avoid prompt inflation. Results show zero leaks, reliable fine-tu…

Job Searcher is an AI-powered job search assistant for new grads. It analyzes resumes, generates LinkedIn search queries, and scores job postings across five dimensions: skills, experience, education, industry, and seniority. Built with a teacher-student model (DeepSeek V4 Pro and Qwen3-8B), it uses a curated dataset of 2,500 resumes and 10,000 job postings. Open-source and available on HuggingFace Spaces.