AI fatigue is real and nobody talks about it

AI reduces the cost of production but increases the cognitive load of coordination and review, shifting engineers from creative flow to draining evaluative tasks. The nondeterministic nature of LLMs and rapid framework churn create a "FOMO treadmill" that leads to decision fatigue and skill atrophy. To remain sustainable, developers should focus on durable infrastructure like context management and authorization, time-box AI sessions, and prioritize first-principles reasoning over endless prompt engineering.

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DoNotNotify is now Open Source

DoNotNotify has open-sourced its full codebase on GitHub to provide transparency and independent verification of its privacy-focused architecture. The project is now open for community contributions, including bug reports, feature requests, and pull requests.

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Slop Terrifies Me

The author warns against the "temufication" of software, where LLMs facilitate a "good enough" culture that prioritizes development speed over craftsmanship and deep technical understanding. While AI can handle 90% of a task, it tends to produce uninspired, median outputs that struggle with unique architectural or design requirements. The primary concern is that both developers and users will accept this "AI slop," leading to the death of artisan software development in favor of high-velocity, low-quality churn.

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AI makes the easy part easier and the hard part harder

The provided text is a 404 error page from the website BlunderGOAT for an article titled "AI makes the easy part easier and the hard part harder." No substantive content regarding AI or LLMs is available as the requested page could not be found.

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Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs

CineGraphs leverages fine-tuned LLMs and graph theory to transform narrative inputs into probabilistic story branches for screenwriting. The platform enables iterative exploration of AI-generated narrative paths while maintaining consistency, ultimately exporting work to industry-standard Fountain format.

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Psychometric Comparability of LLM-Based Digital Twins

Researchers evaluated LLMs as "digital twins" using a construct-validity framework to assess their psychometric alignment with human respondents. While LLMs demonstrate high population-level accuracy, they exhibit systematic divergences such as compressed variance, normative rationality over heuristic biases, and a lack of metric invariance in personality networks. Feature-rich conditioning improves alignment but fails to resolve fundamental psychometric gaps, indicating that LLMs require clearly defined boundary conditions when used as proxies for human behavior.

ArXiv

Shifts in U.S. Social Media Use, 2020–2024: Decline, Fragmentation, Polarization (2025)

Analysis of 2020-2024 ANES data reveals a contracting and fragmented social media landscape, with declining usage on legacy platforms and modest growth on TikTok and Reddit. While platforms generally remain Democratic-leaning, there is a significant shift toward Republican users, particularly on Twitter/X where posting activity flipped by 50 percentage points. This trend, driven by affective polarization, results in a digital public sphere that is smaller, more partisan, and ideologically extreme.

ArXiv

Nonreciprocal wave-mediated interactions power a classical time crystal

Acoustic standing waves facilitate nonreciprocal interactions between trapped particles via scattered wave exchange, enabling energy harvesting for sustained steady-state oscillations. This system exhibits four distinct dynamical states, including emergently active states that break spatiotemporal symmetry to form a classical time crystal.

ArXiv

Open Problems in Mechanistic Interpretability

Mechanistic interpretability aims to reverse-engineer the internal computations of neural networks to enhance AI safety and scientific understanding. While the field has advanced, it faces significant hurdles in scaling methodologies, defining application strategies, and addressing socio-technical challenges. This review outlines the current frontier and identifies priority open problems necessary to bridge the gap between research and practical engineering goals.

ArXiv

Causal World Modeling for Robot Control

LingBot-VA is an autoregressive diffusion framework that unifies video world modeling and policy execution through a shared latent space using a Mixture-of-Transformers (MoT) architecture. It employs a closed-loop rollout mechanism for environmental feedback and an asynchronous inference pipeline to parallelize action prediction and motor execution. The model demonstrates high data efficiency and strong generalization in long-horizon robotic manipulation tasks.

ArXiv

LocalGPT – A local-first AI assistant in Rust with persistent memory

LocalGPT is a lightweight (~27MB) Rust-based AI assistant featuring a local-first architecture with persistent Markdown-based memory. It utilizes SQLite FTS5 for keyword search and sqlite-vec for semantic search with local embeddings, supporting providers like Anthropic, OpenAI, and Ollama. The system includes an autonomous heartbeat for background task execution and offers CLI, web, and GUI interfaces with OpenClaw compatibility.

Repo

Matchlock – Secures AI agent workloads with a Linux-based sandbox

Matchlock is a CLI tool and SDK designed for securely executing AI agents within ephemeral microVMs. It provides isolated Linux environments with network allowlisting and MITM proxy-based secret injection, ensuring credentials never enter the VM. This architecture prevents data exfiltration and credential leakage, even if an agent is compromised, while offering a full, disposable sandbox for agent operations.

Repo

The biggest achievement of my life so far

Explore Singapore is a RAG-based platform utilizing over 33,000 pages of legal and historical documents to provide factual information about Singapore. The architecture features local BGE-M3 embeddings, FAISS for vector search, and a triple-failover LLM backend leveraging Gemini 2.0 Flash and Llama 3.3 70B. The system is deployed via Docker on Hugging Face Spaces with a Flask-based REST API.

Repo

Pilot Protocol – UDP overlay network stack for AI agents(Go, zero deps)

Pilot Protocol is a zero-dependency overlay network stack that provides AI agents with permanent virtual addresses and encrypted peer-to-peer communication over UDP. It replaces centralized API dependencies with secure tunnels using AES-256-GCM, featuring automated NAT traversal, reliable transport, and built-in services for data exchange and pub/sub event streaming. The Go-based infrastructure includes a daemon and CLI for managing agent identities, discovery, and mutual trust handshakes.

Repo

A Prompting Framework for Non-Vibe-Coders

Projex is a framework for collaborative agentic development that uses self-contained markdown documents to manage LLM workflows. It replaces autonomous "vibe-coding" with a human-piloted system of structured planning, execution, and evaluation files stored within the repository. This approach ensures persistent context across sessions, provides clear traceability via git-integrated ephemeral branches, and reduces LLM context retrieval requirements by treating documents as external memory.

Repo