I wrapped the Zorks with an LLM

Infocom Chat is an LLM-powered interface for playing classic text adventures like Zork I, II, and III using natural language. Built with the Tambo framework, the project demonstrates the application of LLMs to legacy interactive fiction engines by translating free-form user input into game commands.

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Management as AI superpower: Thriving in a world of agentic AI

Recent experiments with MBA students demonstrate that LLMs and agentic tools like Claude Code can compress months of startup development into days by drastically lowering the cost of prototyping and pivoting. Effective AI delegation is governed by a trade-off between human baseline time and the combined overhead of prompting and evaluation, a framework supported by OpenAI’s GDPval research showing that models like GPT-5.2 now rival human experts in specialized tasks. As professional workflows shift from execution to the management of autonomous agents, subject matter expertise remains the critical lever for scoping tasks, providing feedback, and validating outputs.

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LLM-as-a-Courtroom

Falconer addresses documentation rot through an "LLM-as-a-Courtroom" multi-agent framework that automates documentation updates based on PR changes. By replacing inconsistent numerical scoring with an adversarial architecture—comprising Prosecutor, Defense, Jury, and Judge agents—the system leverages LLM strengths in argumentation and legal reasoning. This approach achieves 83% precision in identifying necessary updates by requiring structured evidence and multi-stage deliberation to minimize false positives.

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Mistral Launches Vibe 2.0

Mistral AI has released Mistral Vibe 2.0, a terminal-native coding agent powered by the new Devstral 2 model family. This update introduces custom subagents, slash-command skills, and multi-choice clarifications to streamline developer workflows and codebase orchestration. Mistral Vibe is available via Le Chat Pro and Team plans, while Devstral 2 moves to a paid API model with a free tier for experimentation.

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LLM Ad Blockers are coming

As LLM providers integrate native advertising directly into conversational flows, traditional adblockers are becoming obsolete. A proposed solution involves LLM-based middleware that uses prompt engineering to intercept and sanitize model outputs. By performing a second pass to identify and remove commercial bias or brand placements, these tools ensure informational integrity at the cost of slight inference latency.

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Lightweight Transformer Architectures for Edge Devices in Real-Time Applications

This survey examines lightweight transformer architectures and optimization strategies—including mixed-precision quantization, pruning, and hardware-aware NAS—for edge deployment on platforms like ARM and NVIDIA Jetson. It identifies a 15-40M parameter sweet spot for maximizing hardware utilization and memory-bandwidth efficiency. The research provides a 6-step deployment pipeline capable of 8-12x size reduction with less than 2% accuracy degradation.

ArXiv

Hallucination Stations: On Some Basic Limitations of Transformer-Based Language

This paper analyzes LLM hallucinations and limitations from a computational complexity perspective, concluding that LLMs are unable to perform or verify the accuracy of computational and agentic tasks beyond a certain complexity threshold.

ArXiv

The 17% Gap: Quantifying Epistemic Decay in AI-Assisted Survey Papers

A forensic audit of 5,514 citations in recent AI survey papers reveals a 17.0% "Phantom Rate" of unresolvable references, primarily driven by parsing failures and hallucinated metadata for valid titles. The study identifies a stable trend of informational entropy, suggesting LLMs act as "lazy research assistants" that compromise the scientific citation graph. This systematic degradation of digital chains of custody creates endemic "link rot," threatening the reproducibility of AI research.

ArXiv

Attention Is Not What You Need

The proposed Causal Grassmann layer replaces standard self-attention by encoding token interactions as low-rank subspaces on a Grassmann manifold using Plücker coordinates. This attention-free architecture achieves linear scaling in sequence length and competitive performance on Wikitext-2 and SNLI benchmarks. By shifting computation from unstructured tensor spaces to finite-dimensional manifolds, the design provides a more structured, geometric framework for interpreting neural reasoning.

ArXiv

HetGPU: The pursuit of making binary compatibility towards GPUs

hetGPU is a compiler and runtime system that enables binary compatibility across heterogeneous GPU hardware from NVIDIA, AMD, Intel, and Tenstorrent. By utilizing an architecture-agnostic IR and a dynamic translation layer, it bridges divergent SIMT and MIMD execution models while providing uniform memory and synchronization abstractions. The system further supports live migration between disparate vendors via state serialization with minimal performance overhead.

ArXiv

Honcho – Open-source memory infrastructure, powered by custom models

Honcho is an open-source memory library and managed service designed for building stateful agents through a peer-centric architecture that treats both users and models as unified entities. It features a continual learning system that asynchronously processes interaction history to maintain evolving representations, session summaries, and behavioral insights. Developers can leverage its Chat and Context APIs to retrieve reasoning-informed data and manage long-term memory, facilitating personalized agent behavior and data moats across any LLM or framework.

Repo

DeepSeek-OCR 2

DeepSeek-OCR 2 introduces a "Visual Causal Flow" architecture designed for human-like visual encoding in document understanding tasks. The model supports dynamic resolution with up to 1,120 visual tokens and provides optimized inference via vLLM and Transformers for both images and PDFs. Key capabilities include high-concurrency PDF processing, document-to-markdown conversion, and visual grounding.

Repo

Ouroboros – AI agent framework that asks "why?" before writing code

Ouroboros is an agentic framework designed to transform ambiguous human requirements into executable specifications through Socratic questioning and ontological analysis. It utilizes a Progressive Adaptive LLM (PAL) router to optimize costs by escalating from frugal to frontier models only when task complexity or criticality warrants. The system features a six-phase lifecycle including recursive decomposition, persona-based lateral thinking to resolve stagnation, and a three-stage evaluation pipeline ranging from mechanical testing to multi-model consensus.

Repo

Blink-Edit – Cursor-style next-edit predictions for Neovim (local LLMs)

blink-edit.nvim is a Neovim plugin that offers Cursor-style next-edit predictions using local LLMs, rendering them as ghost text. It sends context-aware prompts, incorporating current file content, visual selections, and LSP references, to a user-configured local LLM backend. The plugin supports OpenAI-compatible APIs (e.g., llama.cpp, vLLM) and Ollama, enabling private and fast code suggestions with models like Sweep or Zeta, and allows predictions to be accepted with <Tab> or rejected with <Esc>.

Repo

Nyxi – Execution-time governance for irreversible

Nyxi is a proprietary execution-time governance system that enforces authority over irreversible actions proposed by humans or models. It operates at a single boundary to ensure only authorized actions reach the irreversible sink, providing a verifiable veto/allow mechanism for high-stakes operations.

Repo