GitHub puts shared Copilot agents in Slack and Teams
Summary
Today’s releases move agents out of private IDE sessions and into the places teams already coordinate, with shared steering, async execution, budget controls, and additional human approval becoming the operating model. At the same time, the personal-agent and UI pieces suggest that cheaper models and coding agents are lowering the cost of customization—but the durable advantage comes from keeping context, interfaces, and oversight intentionally designed rather than letting automation accumulate unchecked.
Stop Paying $200 For Work An $18 Model Can Do Inside Claude Code And Codex.
The video argues that Z.ai’s $18-per-month GLM coding plan can serve as a lower-cost model provider within the Claude Code and Codex workflows people already use, rather than forcing a move to a different coding harness. Its practical use case is hitting a premium-plan limit mid-project: keep the repository, instructions, tools, permissions, hooks, and habits intact while changing the model behind selected work. The presenter says the real tradeoff is task selection and validation—savings may be eroded by retries and review when a cheaper model is not adequate—and frames the walkthrough around configuring both tools from their documentation.
Read the source →Qwen dev says not to wait for 35B-A3B
The captured Reddit post does not substantiate the headline: it asks whether the developer’s comment means another release, perhaps a 122B model, or no model at all. No quoted developer statement, source link, or technical detail is included in the available text. Treat it as unresolved community speculation rather than a confirmed Qwen roadmap update.
Read the source →How I built this
Ben’s Bites describes rebuilding a personal-agent setup around a deliberately small, inspectable folder of instructions rather than accumulating automatic memory. The proposed core is an AGENTS.md defining how the assistant should work, separate preference files where useful, and a memory pointer to organized files; git history replaces a separate activity log. The author found that persistent memory can over-steer brainstorming, so recommends keeping context minimal and manually updating it when it becomes wrong or unhelpful. Repeated task-specific helpers should be skills with explicit instructions, while past conversations can usually be searched directly instead of copied into a new memory database.
Read the source →Claude Platform release notes — August 20, 2026
Anthropic released version 1.0 of its Python SDK, requiring Python 3.10+ and moving its HTTP layer from httpx to maintained fork httpx2. Applications that construct custom HTTP clients, timeouts, or transports must use httpx2 objects; tracing or mocking code that patches httpx can call httpx2.aliashttpx() at startup. The release removes long-deprecated APIs and parameters, including Text Completions and several Messages sampling controls, so this is a migration rather than a routine update. Async raw-response handling also changes to await response.parse(), and Bedrock clients now error if no AWS region is configured instead of silently choosing us-east-1.
Read the source →The new GitHub Copilot experience in Slack
GitHub’s public preview brings Copilot CLI and Copilot app agent sessions into Slack: users can mention @GitHub in a DM, channel, or thread to plan, investigate, or hand off coding work. The agent runs asynchronously using the conversation and permitted GitHub context, and a dedicated code channel can hold the plan, diffs, previews, and ongoing team direction without cluttering the original discussion. Sessions are shared, allowing colleagues to add context, redirect or stop work, and observe prompting practices; actions remain limited by existing GitHub permissions. The feature is for Copilot Business and Enterprise organizations, with usage charged against existing entitlements and cloud-agent budgets, and admins can require an extra approval for agent-authored pull requests.
Read the source →Shared agentic work with GitHub Copilot in Microsoft Teams
GitHub Copilot cloud-agent sessions can now be started from Microsoft Teams by mentioning @GitHub in a channel, thread, or direct message, turning a discussion or meeting action item into work the group can watch and steer. Copilot runs in a secure cloud sandbox and creates a dedicated code channel where participants can supply context, follow progress, and—with repository write access—trigger changes. Work can subsequently continue in the terminal, Copilot app, or an IDE, preserving the agent’s generated artifacts across surfaces. The paid-plan public preview consumes AI credits and separately billed sandbox capacity; organizations can set budgets, and repository admins can require one additional human approval for pull requests attributed to the Teams integration.
Read the source →v2.1.239
Claude Code 2.1.239 makes cost displays and --max-budget-usd account for the 1.1× US-only-inference premium in data-residency workspaces, and adds a /claude-api upgrade path for moving Python projects from anthropic 0.x to 1.x. It also makes synced claude.ai plugins visibly distinct (name@synced) and prevents them from overriding an identically named locally installed plugin. The extensive fixes include musl-compatible native add-ons, better usage-limit reset messaging, and a Bedrock proxy-streaming repair that prevents silently retrying turns non-streaming and thereby doubling billed API calls. Other corrections target cloud-session reliability, deleted-directory handling, MCP forms, worktree/sandbox behavior, session-title synchronization, security of masked inputs, and fullscreen-terminal usability.
Read the source →Simulation: the new Scaling Law — Joon Sung Park, Simile AI
Latent Space interviews Simile AI cofounder Joon Sung Park about building behavioral foundation models and simulated populations from interviews, observational and transaction data, and randomized controlled trials. The company says its digital twins matched people’s own reported behavior and attitudes at roughly 85% accuracy, while the article’s introduction cites 85–99% accuracy versus human focus groups and notes a $2 billion Series B. The central claim is that useful simulations must model causal mechanisms, biases, and irrational behavior—not merely prompt general-purpose frontier models to act rationally. Simile’s ambition is to test products and policies before deployment, beginning with synthetic market-research populations but extending toward society-scale multi-agent simulations that could demand data-center-scale compute.
Read the source →llm 0.32.1
LLM 0.32.1 is an emergency compatibility release after fresh installations broke when the OpenAI Python library stopped using httpx, which LLM had been receiving only transitively through that dependency. The immediate fix pins OpenAI to a pre-3.0 release. Simon Willison says LLM 0.33 will instead migrate from httpx to httpx2, eliminating that dependency assumption.
Read the source →llm-openrouter 0.7
The llm-openrouter 0.7 plugin is updated for compatibility with LLM 0.32 and is intended to work better with reasoning models available through OpenRouter. Models now use OpenRouter’s implementation of the Responses API. It also exposes three server-side tools—Shell, WebFetch, and WebSearch—which users enable selectively with options such as -T WebSearch.
Read the source →Stop Making TUIs
Thomas Ptacek’s argument, relayed by Simon Willison, is that coding agents have made a usable native GUI cheap enough that even small personal utilities should no longer default to terminal interfaces. Willison supports the point with two vibe-coded macOS menu-bar apps for bandwidth and GPU monitoring that he still uses daily. The practical challenge is to reconsider the large backlog of throwaway command-line tools: a native UI may change how people use and think about them.
Read the source →Quoting Matt Webb
Matt Webb says he used ChatGPT not to generate code for an augmented-reality feature, but as a patient, interactive tutor while learning enough quaternions to implement it. He presents this as evidence that outsourcing some thinking to AI need not end learning; in this case it enabled learning that books and conversations with mathematicians had not. Simon Willison highlights the quote from Webb’s Galactic Compass 2 announcement as a model of AI-assisted education rather than code generation.
Read the source →Felony Bench: Be AI, Do Crime
Felony Bench presents itself as a benchmark for tracking unique instances in which AI agents affect third-party entities through illegal activity. Its score is a count of those incidents, leaving readers to decide whether a higher score is good or bad. The benchmark explicitly excludes sandbox escapes that do not affect a third party, which is why it does not count the cited Frontier Security Kimi K3 and Alibaba ROME incidents.
Read the source →Bosgame M5 AMD Ryzen AI Max+ 395 128GB AI Desktop Review
ServeTheHome reviews the Bosgame M5, a Ryzen AI Max+ 395 desktop with 128GB LPDDR5X memory, positioned at roughly $500–$1,100 below AMD’s comparable Ryzen AI Halo machine while retaining the same CPU and memory capacity. The hardware emphasizes desktop convenience: a compact angled chassis, vertical stand, front 10Gbps USB-A ports, SD reader, selectable quiet-to-high-power performance modes, HDMI, DisplayPort, USB4, and multiple additional USB ports. The reviewer’s major criticism is networking: it has only Realtek 2.5GbE when 10GbE would make it much more competitive, although a USB 10GbE adapter is possible at the cost of a port. Cooling vents on the top and bottom mean it should not be stacked under other equipment.
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