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GitHub Introduces Project HydraFusion: Runtime Multi-Model Orchestration That Builds a Workflow Per Coding Task in Copilot CLI
GitHub's Project HydraFusion research preview builds per-task multi-model workflows (Single, Cascade, Critique) in Copilot CLI, reporting +4.9 quality at 67% lower cost on TerminalBench 2.1.
Project HydraFusion is a research preview available on all GitHub Copilot plans inside Copilot CLI that treats model routing as workflow selection, choosing among Single, Cascade (draft plus quality gate), and Critique (cross-family reviewer) execution patterns per request. Against Claude Opus 5 baselines at medium reasoning, fixed HydraFusion policies cut estimated cost 67% while adding 4.9 quality points on TerminalBench 2.1, and cut cost 36% and 65% with slight quality dips on DeepSWE and CheckpointBench. Billing is per token at each underlying model's standard rate; there are no open weights or self-hosting options.
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NVIDIA Open-Sources OSMO: One YAML Orchestrates Physical AI Training, Simulation, and Robot Testing
NVIDIA open-sourced OSMO, a Kubernetes-native YAML orchestrator running physical-AI training, simulation, and robot testing across mixed GPU tiers.
OSMO (Apache-2.0, latest release 6.3.1) lets teams describe training, simulation, and hardware-in-the-loop pipelines in a single YAML and routes tasks across datacenter GPUs (GB200), workstation RTX hardware, and edge devices like Jetson AGX Thor. It ships Helm charts and containers on NGC, uses the KAI Scheduler with NVLink topology-aware placement, and includes RBAC, OAuth2, and TLS termination. NVIDIA says it is battle-tested on GR00T, Isaac Lab, Isaac Sim, and Isaac ROS, and integrates with Claude Code, OpenAI Codex, and Cursor agents.
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The OpenClaw 2.0 release moves your sessions into SQLite
OpenClaw 2.0 migrates AI agent sessions to SQLite, adds guided credential setup, and flags shared-session controls as not a security boundary.
OpenClaw 2.0, described as the largest update in the project's history, migrates sessions and transcripts into SQLite and adds guided setup that detects existing AI credentials from Codex, ChatGPT, Claude CLI sign-ins, API keys, and local Ollama or LM Studio models. The release expands multiplayer sharing while explicitly stating its permission controls are not tenant isolation or a security boundary, and that revoked access can briefly remain usable. Startup JavaScript requests fell from 140 to 45 and startup time from about 1.6 seconds to 575 milliseconds in simulated tests against a mocked Gateway. Automation wrappers must now inspect reported health because requesting --json does not waive risk acknowledgement.
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Google Open-Sources Mantis: A Modular Skills Toolkit That Lets Coding Agents Find, Reproduce and Patch Vulnerabilities
Google open-sourced Mantis, an Apache-2.0 modular skills toolkit that lets AI coding agents find, reproduce, and patch vulnerabilities with sandboxed verification.
Google released Mantis on GitHub under Apache 2.0 as a stack-agnostic set of slash-command skills that chain through the full vulnerability lifecycle: mining version history, building threat models, filtering findings, reproducing bugs in gVisor or network-disabled VMs, assembling exploit chains, patching, and scoring residual risk from 1 to 10. It runs with Gemini CLI, Antigravity CLI, the Google ADK, or comparable agent frameworks, and a supervisor skill (/mantis-meta-agent) can drive the whole loop. Google says the design targets the sub-7 percent true-positive rate of naive AI code scanning, and that its hierarchical summary tree cuts token overhead by over 85 percent. The toolkit is deployable for local and internal evaluation but not yet recommended for production.
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The VMs Powering Mobile Agents (Instinct, Claude Code)
A teardown reveals Claude Code runs in Firecracker microVMs with a Rust PID 1 and MITM'd egress, while Instinct rents E2B sandboxes with git-based memory.
The author inspects the virtual machines hosting cloud agents: Claude Code runs in a Firecracker microVM with a custom Rust init (process_api) as PID 1, a 324 MB Bun harness on a read-only disk, and 443-only MITM'd SSE egress to api.anthropic.com with host-rotated OAuth tokens and no inbound access. Instinct rents E2B sandbox-as-a-service Firecracker microVMs (Ubuntu 22.04, 2 vCPU, 1.9 GB RAM) where agent memory is a git repo of Markdown committed by the agent and pushed to S3 as a single bundle, using short-lived STS credentials. Both platforms rely on Firecracker, differing mainly in fleet operator and guest boot configuration.
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llm 0.35
llm CLI tool version 0.35 adds support for OpenAI's new GPT-6 Astra model exposed as gpt-6-astra.
Simon Willison released llm 0.35, which adds an OpenAI model definition for GPT-6 Astra under the model ID gpt-6-astra. No other release details were provided in the post.
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Show HN: Engrim – A universal, local-first SQLite memory engine for AI CLIs
Developer launches Engrim, an open-source local-first SQLite memory engine giving AI CLI agents persistent memory.
Engrim, shared on Hacker News (89 points), is a universal, local-first memory layer built on SQLite for AI CLI tools. It targets agent-style CLI applications that need durable cross-session memory without cloud dependencies. Details beyond the repository description were not provided in the source text.
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numbat - AI agent observability, (Fri, Sep 4th)
SANS reviews Perplexity's open source numbat, a Go-based tool giving security teams observability, detection rules, and enforcement for AI agents like Claude and Gemini.
Numbat, Perplexity AI's open source observability tool, monitors desktop, CLI, IDE, and gateway AI agents through local hooks, OTLP/HTTP logs, and on-disk session artifacts. It ships detection rules mapped to MITRE ATT&CK (e.g., recon.network_sweep / T1046), supports enforcement mode, and packages investigations with SHA256-verified manifests and timelines. The SANS review positions it as a response to unmanaged AI agent and MCP server sprawl highlighted by the OpenAI/Hugging Face incident.
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llm-openrouter 0.7.1
Simon Willison released llm-openrouter 0.7.1, a performance fix for loading OpenRouter models in his LLM CLI plugin.
Version 0.7.1 of the llm-openrouter plugin addresses a performance problem when loading OpenRouter models in the LLM command-line tool. The fix was contributed by GitHub user waveplate. It is a minor maintenance release with no security implications noted.
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llm 0.34
Version 0.34 of Simon Willison's llm CLI adds response-duration metrics to log output, plus bug fixes and faster log querying.
The open-source llm command-line tool for interacting with large language models released version 0.34. The headline change adds response duration in milliseconds and human-readable form to llm logs --usage Markdown output, plus a new duration_ms field in llm logs --short. The release includes several contributed bug fixes and a significant performance improvement to llm logs, alongside the related llm-openrouter 0.7.1 release.
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ToolHive: The open-source way to run any MCP server securely
Stacklok's open-source ToolHive runs Model Context Protocol servers in isolated containers with per-request identity enforcement, audit logging and a signed registry.
ToolHive, shipped under Apache 2.0, containersizes MCP servers locally via Docker or Podman or in clusters through a Kubernetes operator, applying permissions, network filtering, and secrets management. The platform includes a Registry Server implementing the official MCP Registry API with signing and provenance verification, a Virtual MCP Server gateway with OIDC/OAuth single sign-on and OpenTelemetry traces, and a desktop Portal for one-click installs. The browser-based cloud UI is retired, so the desktop app and CLI are the supported rollout paths.
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HOL Guard: Open-source antivirus for AI agents
HOL Guard is an open-source local guardrail that pauses AI coding agents before risky actions like secret access and prompt injection.
HOL Guard sits between AI coding agents (Claude Code, Cursor, Codex, Gemini CLI and others) and the host machine, intercepting risky commands before execution with checks taking under 50 milliseconds and running fully offline. It offers four sensitivity modes — Gentle, Balanced (default), Strict, and Paranoid — and parses command structure, environment, sensitive-path access and network destinations to decide when to interrupt. The core runtime is free and open source on GitHub, with 552,000 downloads reported; the vendor says it has no telemetry on adoption because collection is off by default.
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