Operational doctrine for practical AI systems design.
AI companion for your workspace, with per‑project memory, coding agents, and a native desktop chat UI
[EuroSys 2026] TokenFlow: Buffer-aware preemptive scheduling and proactive KV-cache management for responsive LLM streaming.
The AI Contract Runtime
Perpenda — Android learning path for product professionals learning LLM systems through trade-offs, rubrics, and calibrated AI grading.
A muti-agent Dnd DM that directs you to dive into a fantasy world!
PyTorch DDP and multi-GPU LLM training — from a minimal distributed example to NanoGPT speedruns, Muon, H100 profiling, and modded-nanogpt. FBA LAB https://bubblnet.com
Structure-first pipeline that transforms GitHub repositories into question-indexed, graph-grounded semantic assets for code search, Graph-RAG, and LLM-based reasoning.
AI-Powered Ad Campaign Orchestration Platform
Documentation and design artifacts for Channel AI, a multi-agent conversational analytics system.
Open-source harness distillation: frontier teachers improve prompts, tools, validators, skills, and runtime policies around weaker models.
PromptGuard is a pragmatic, opinionated framework for establishing continuous integration for LLM behavior. It operates on a simple, verifiable principle: run the same prompts across multiple model configurations, compare outputs against defined expectations, and flag semantic regressions.
A unified, production-grade LLM training and alignment framework. Features modular implementations for downstream tasks BERT, DPO, and GRPO to streamline model alignment and optimize memory overhead.
nanhudev / Xuanjun Yu — AI-native builder working on agent systems, Brain x Harness infrastructure, local-first AI and creative tooling.
Automatically extracts, validates, and structures invoice data from images and PDFs using OCR + a local LLM—eliminating manual data entry.
IntelliMesh AI is an **agentic decision system** designed for enterprise AI architectures—integrating **decision intelligence**, **multi-agent orchestration**, and **document intelligence pipelines** into a unified execution layer.
Research-grade neuro-symbolic RAG framework where retrieval is a policy, not a vector search, built for evaluation, ablation, and reliability analysis.
A hands-on technical book and Python lab for building and evaluating agentic systems.
Prototype for execution-plan-driven data standardization, schema profiling, validation, and preview generation.
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