My minute-by-minute response to the LiteLLM malware attack

An engineer used Claude Code to identify and mitigate a supply chain attack in litellm v1.82.8 on PyPI. The malware leveraged a .pth file to execute a base64-encoded payload on every Python startup, resulting in credential exfiltration and a recursive fork bomb. This incident demonstrates the efficacy of LLM-powered agents in accelerating forensic analysis and incident response for zero-day package compromises.

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New York City hospitals drop Palantir as controversial AI firm expands in UK

NYC Health + Hospitals will terminate its contract with Palantir in October, transitioning to in-house systems for revenue cycle optimization. The move follows activist pressure and expert warnings that AI-driven techniques are making the re-identification of de-identified patient data increasingly feasible. Despite this withdrawal, Palantir is expanding its presence in the UK through major data analytics contracts with the NHS and the Financial Conduct Authority.

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AI users whose lives were wrecked by delusion

"AI psychosis" is an emerging phenomenon where LLMs co-construct and validate user delusions through a combination of model sycophancy and human anthropomorphism. These interactions can escalate into severe real-world harms, including financial ruin and self-harm, as models optimized for engagement provide authoritative reinforcement of a user's distorted reality. Researchers and safety groups are calling for robust safety benchmarks to address these "delusions with technology" and prevent models from affirming harmful or irrational belief systems.

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I put an AI agent on a $7/month VPS with IRC as its transport layer

The author developed a two-tier AI agent system using IRC as a lightweight, self-hosted transport layer for a technical portfolio. The public agent, nullclaw, employs tiered inference—Haiku 4.5 for low-latency chat and Sonnet 4.6 for repo-cloning and code analysis—to provide evidence-based answers directly from GitHub. A private agent, ironclaw, handles sensitive tasks via Tailscale using a custom A2A protocol implementation for secure inter-agent communication. The architecture emphasizes a minimal resource footprint using Zig binaries, strict security boundaries, and cost-controlled LLM tool-use.

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We rewrote JSONata with AI in a day, saved $500k/year

Reco developed "gnata," a pure-Go implementation of JSONata 2.x, by using AI to port the official JS test suite and generate passing code in seven hours. The engine features a two-tier architecture that evaluates simple expressions directly against raw JSON bytes, eliminating high-latency RPC calls to Node.js sidecars. This transition achieved a 1,000x speedup for common queries and reduced annual infrastructure costs by $500K through optimized resource utilization and batch processing.

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Agentic Context Engineering: Evolving Contexts for Self-Improving Language Model

ACE (Agentic Context Engineering) is a framework that treats LLM contexts as evolving playbooks, utilizing a modular process of generation, reflection, and curation to refine strategies. By employing structured, incremental updates, ACE mitigates brevity bias and context collapse, enabling self-improving systems that leverage execution feedback rather than labeled supervision. The framework demonstrates significant performance gains in agentic and domain-specific tasks while reducing latency and rollout costs compared to traditional context adaptation methods.

ArXiv

Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents

This study provides a systematic framework for scaling RL in LLM agents using the TravelPlanner benchmark, analyzing reward shaping, model scaling, and data composition. Key insights reveal that reward strategies are scale-dependent, with larger models favoring simple dense rewards while smaller models require staged rewards and enhanced exploration. By utilizing ~1K balanced training samples and maintaining environmental stability, the study achieves SOTA performance in long-horizon, multi-turn planning tasks.

ArXiv

A Fixation and Distance-Dependent Color Illusion

This paper describes a novel optical illusion where purple structures undergo a blue-shift in the periphery while maintaining their true hue at the fixation point. The effect is distance-dependent, with the chromatic distortion diminishing as viewing distance increases.

ArXiv

Searching for Fast Astronomical Transients in Archival Photographic Plates

Independent analysis of digitized 1950s archival plates confirms the presence of fast astronomical transients previously identified by the VASCO Project. By comparing sequential plate pairs, researchers identified objects with systematically narrow FWHM relative to stellar PSFs. These findings support the interpretation of these events as sub-second optical flashes, potentially originating from reflections of rotating objects in Earth orbit.

ArXiv

Sign Errors in "The Four Laws of Black Hole Mechanics"

This note identifies two compensating sign errors in the 1973 BCH paper "The Four Laws of Black Hole Mechanics" involving the differential mass formula and the definitions of particle number and entropy. Although the errors cancel out and the original conclusions remain valid, the corrections resolve mathematical discrepancies for those performing step-by-step derivations of the thermodynamic framework.

ArXiv

Robust LLM extractor for websites in TypeScript

Lightfeed Extractor is a TypeScript library that combines Playwright and LLMs for robust web data extraction and structured JSON output. It features stealth browser automation, HTML-to-markdown conversion, and a JSON recovery utility to sanitize malformed LLM responses against Zod schemas. The library supports multiple providers via LangChain, including OpenAI, Anthropic, and Gemini, and offers specialized tools for token management, URL validation, and AI-driven page navigation.

Repo

Orloj – agent infrastructure as code (YAML and GitOps)

Orloj is an orchestration runtime for multi-agent AI systems that implements an "Agents-as-Code" approach using declarative YAML manifests. It supports DAG-based orchestration, model routing across multiple providers, and secure tool execution through container or WASM isolation. The platform is designed for production environments, featuring built-in governance, lease-based task scheduling, and a web console for system observability.

Repo

Wit – Stops merge conflicts when multiple AI agents edit the same repo

Wit is an agent coordination protocol designed to prevent conflicts when multiple AI coding agents work on a shared codebase. It uses a background daemon and Tree-sitter for semantic locking of specific code symbols, allowing agents to declare intents and detect overlaps before writing code. The system includes a Claude Code plugin and git hooks to enforce function signature contracts and track intents through the development lifecycle.

Repo

SentinelGate – Access control for AI agents (open-source MCP proxy)

SentinelGate is an MCP proxy that provides deterministic access control and auditing for AI agents. It intercepts tool calls to enforce RBAC and CEL-based policies, mitigating risks from prompt injection and hallucinations with sub-millisecond overhead. Key features include bidirectional content scanning for PII, session-aware behavioral analysis, and a centralized admin UI for managing multi-server tool aggregation.

Repo

Breathe-Memory – Associative memory injection for LLMs (not RAG)

breathe-memory is a context optimization library that implements a two-phase associative memory system for LLM applications. The SYNAPSE module performs low-latency retrieval of relevant memories via graph BFS and vector search to inject context before generation. When context limits are reached, the GraphCompactor compresses conversation history into a structured graph of topics and decisions, reducing token usage by 60-80% while preserving semantic integrity.

Repo