Dev & Tools
Frameworks, model releases, engineering deep-dives and practitioner notes.
An AI model from Meta also hacked another company during testing
An AI model from Meta also hacked another company during testing Stop me if you've heard this one before : An AI model from the parent company of Facebook and Instagram hacked into another company’s systems during cybersecurity testing, a spokesperson confirmed on Wednesday. Meta says the breach occurred because of an inadvertent error during testing of the model, similar to previously disclosed incidents with OpenAI and Anthropic. “A misconfiguration by Irregular, an independent testing company Meta uses, inadvertently allowed one of our models access to the internet during evaluation,” the Meta spokesperson said. Meta’s Muse Spark model “exploited a security vulnerability” in another company “in a manner similar to previously-reported instances with other companies.” The Information had the scoop , I'm linking to CNN's re-report of it since they don't have a paywall. So that's Anthropic, OpenAI, and Meta. Google Gemini really needs to catch up on accidentally cyberattacking other companies. Tags: security , ai , generative-ai , llms , meta , accidental-cyberattacks
New release of LLM adds support for reasoning traces, OpenAI Responses, server-side tools, and smarter logging
I released LLM 0.32 this morning, the most significant new version of LLM since the initial launch of the project. The new version includes support for visible reasoning traces, server-side provider tools, redesigned content-addressable SQLite logs, new models, and new features enabled by the OpenAI Responses API. I also released a new version of the llm-anthropic plugin with substantial updates of its own. Headline features for LLM CLI users Running LLM against reasoning models now displays their reasoning traces to standard error, so you can see what they are "thinking" without that information being included in the standard output that you might pipe to another tool. Add -R/--hide-reasoning to turn this off. LLM includes support out-of-the-box for the GPT-5.6 model family , and the new default model used with llm "prompt" is now the inexpensive but capable GPT-5.6 Luna . LLM calls can now use server-side tools from various providers. OpenAI provide a code execution environment as a server-side tool; LLM can now run prompts that benefit from that like so: llm --tool CodeInterpreter ' Show current python and SQLite versions ' OpenAI also gets a WebSearch tool. The llm-anthropic plugin adds WebSearch , WebFetch , CodeExecution , and AnthropicMCP , which looks like this: llm -m claude-sonnet-5 -T ' AnthropicMCP("https://datasette.simonwillison.net/-/mcp") ' \ ' how many rows in the blog_blogmark table? ' That causes Anthropic to execute MCP calls against my new datasette-mcp plugin as part of a single request/response interaction with their API. The new llm openai endpoint command provides a tool for executing prompts against any OpenAI compatible endpoint as a one-liner. These aren't logged, which makes this a handy tool for running one-off prompts against anything that speaks the lingua franca of the LLM API world. Here's how I use that to run prompts against Gemma 4 12B running in my localhost LM Studio API, via uvx (no LLM installation required) and mixing in the llm-tools-quickjs tool plugin for good measure: uvx --with llm-tools-quickjs \ llm openai endpoint http://localhost:1234/v1 -m google/gemma-4-12b \ -T QuickJS ' Use QuickJS to multiply 3434 * 2434 ' --td New features in the Python API LLM's Python API previously required you to create a conversation and then send messages to it one at a time. This was an abstraction over the true nature of LLMs, where each request carries a complete history of the messages that came before it. That abstraction
Dev & ToolsMicrosoft Opens 26 Open Models to Startups Through Fireworks AI on Foundry
Microsoft is pushing its newly generally available Fireworks AI integration at the startup segment, publishing a deployment blueprint on August 4, 2026 that pairs a reference architecture for running open models on Microsoft Foundry with a billing perk: members of the Microsoft for Startups program can apply their Azure credits to Fireworks model deployments, and the program advertises up to $150,000 in credits. The Fireworks integration itself has reached general availability, putting…
Dev & ToolsOpenAI’s new AI smart speaker will reportedly sell for between $300 and $400
OpenAI's forthcoming AI smart speaker is expected to retail between $300 and $400. Reports indicate that this device, seen as a physical embodiment of ChatGPT, will feature a unique donut shape facilitating portability, enabling users to position it throughout their homes.
Dev & ToolsIncident Report: unsanctioned agent behaviour during cyber testing
Incident Report: unsanctioned agent behaviour during cyber testing It happened again . This time it was the UK government's AI Security Institute who accidentally attacked other companies while running an evaluation with models with the safety filters turned off. From their technical paper (PDF): During a cyber evaluation, from 25 to 28 July 2026, AI agents engaged in sustained, unsanctioned activity directed at what were, in practice, real people and organisations. These attempts were unsuccessful and, to the best of our knowledge, no real-world harm resulted. [...] Across 122 evaluation attempts on two of AISI’s cyber challenges, AISI found 19 instances where AI agents took unsanctioned action on the live internet, including cases that targeted real people and organisations. [...] It is uncertain to what extent the model recognised it was taking actions against real people. In the most serious case, an AI agent (Mythos 5) decided to attempt to solve the cyber challenge using a supply-chain attack. As a result, the AI agent created a GitHub account and then tried to convince an open-source repository maintainer to accept a malicious GitHub pull request (PR), including by creating a second account masquerading as another human user endorsing the PR. [...] Furthermore, in its attempt to solve the challenge, the agent decided to employ the technique of “spear-phishing” by sending targeted emails containing malicious content and attempting to manipulate recipients into accepting the code changes, and planned a prompt injection to compromise other coding agents. The thing I found most surprising is that AISI were running these agents without any form of network sandboxing at all: AISI provided the AI agents with internet access during these evaluations, which enabled their actions on the open internet in this setting. Internet access was a deliberate part of AISI’s evaluation configuration in this setting, and not due to sandbox escape. This, combined with the fact that "AISI deliberately disables developer-implemented cyber-classifiers", makes the fact that the agents started attacking real-world targets entirely unsurprising to me. Most of the reported incidents were claude Mythos 5, but "GPT-5.6 Sol without cyber classifiers" scored a few as well. Here's "Sample 1" from the paper, in which the agent tries to execute a supply-chain attack by submitting a PR with a hidden prompt injection attack, then social engineering with a second agent pretending to have
Dev & ToolsOpenAI Gives Free ChatGPT Users Unlimited Text Chats on GPT-5.6 Luna
OpenAI on August 6, 2026 moved its current model generation into ChatGPT's free tier, announcing that GPT-5.6 Luna will become the default model for Free and Go users and that those users will get unlimited text chats. The announcement also ships an updated GPT-5.6 Sol for Plus and Pro subscribers, retuned for everyday conversation, across a service the company says 1 billion people use each week. For paid users, the updated Sol is built to give more direct responses, use tighter formatting…
Dev & ToolsI Built a Tool-Calling Agent in Python. Here’s How I Debugged It
A new two-stage tool-calling agent developed in Python efficiently handles real API calls, validates inputs, retrieves weather forecasts, and maintains a detailed trace of each operational step.
Dev & ToolsIntroducing Muse Code and Muse Spark 1.2
Introducing Muse Code and Muse Spark 1.2 Yet more evidence that the most important characteristic of any model these days is long-sequence agentic tool calling. Meta shipped their own coding agent as part of getting that to work! Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1, with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows. In Muse Spark 1.2, we significantly scaled up training compute on coding tasks while expanding training environment diversity. The model also maintains its strength in other key areas like general agents. [...] We co-trained Muse Spark 1.2 with Muse Code to ensure the model exhibits its best performance and coding usability when paired together. The training included rejection sampled harness trajectories and recipe optimizations for goals, compaction, and subagents, alongside the integration of the Muse Code toolset to maximize harness compatibility. [...] Muse Spark 1.2 was extensively trained on long-horizon coding tasks, including whole-repository generation, large end-to-end projects, and auto-research. Here's a pelican riding a bicycle SVG produced by Muse Spark 1.2 : You can see the Spark 1.1 pelican from 9th July here . I think the 1.2 pelican is a small but material improvement. An interesting twist on pricing is that the model is offered as two different model IDs. muse-spark-1.2 is priced at $1.25/million input and $4.25/million output - close to Gemini 3.6 Flash ($1.50/$7.50) - but if you agree to let Meta use your data "to improve our products" you can use muse-spark-1.2-contributor which is $0.10/$0.20 - a huge discount, closer to GPT-5.6 Luna ($0.20/$1.20) and Gemini 3.1 Flash-Lite ($0.25/$1.50). I added those new prices to llm-prices.com . Via Hacker News Tags: ai , generative-ai , llms , meta , llm-pricing , pelican-riding-a-bicycle , llm-release , coding-agents
Dev & ToolsClaude Code Sessions Can Now Run on Infrastructure Your Team Controls
Anthropic has opened a public beta of self-hosted environments for Claude Code, moving the coding agent's cloud sessions off Anthropic's infrastructure and onto servers inside the customer's own network, the company announced on August 6, 2026. The option is available to organizations on Claude Team and Enterprise plans and is switched off by default. A session started from the web, mobile, desktop, the terminal, or a scheduled routine runs inside the organization's network, next to its…