#Agent

AIXiaomi's MiMo team released MiMo Code, an MIT-licensed terminal coding agent built on OpenCode for long-horizon programming tasks. The design centers on three areas: Max Mode parallel sampling that generates five candidates per turn, Goal-based completion verification, and a memory system that checkpoints session state and rebuilds context. The article reports offline benchmark results and a double-blind A/B test with 1,213 pairs in which MiMo Code's win rate exceeded 65% beyond 200 execution steps.

Why it matters: The article explains how MiMo Code handles long-horizon coding through computation, checkpointed memory, and cross-session evolution, useful for judging design tradeoffs in coding agents.

AIEthan Mollick, who had early access to Claude 5 Fable, reports that it outperformed other public models in his tests, including an isochrone travel-time map and a nine-and-a-half-hour software build called Concord. He says the model delegated work to other agents and made many design choices he could not see or weigh in on, leaving him closer to a client than a hands-on operator. He also notes high token usage, frequent fallback to Claude 4.8 Opus under security guardrails, and persistent quirks in its writing style.

AIApple's MLX team released three videos at WWDC covering running agents locally, distributed inference and training, and MLX Swift. The post shares YouTube links for each talk, presented by Angelos Katharopoulos, Tatiana Likhomanenko, and David Koski.

AIMichael Truell says working with agents should feel like collaborating with a colleague, not just exchanging text chats. He envisions interacting with them through gestures on a shared screen and live conversation. The post builds on Cursor's Design Mode, which lets users point, draw, or talk to update a UI.

AINitroGen, an embodied agent project, received a CVPR Best Paper Honorable Mention, marking progress toward general-purpose agents that master real-world physics and a range of simulated physics. The post also notes that MineDojo, the team's earlier Minecraft agent, won a NeurIPS Best Paper award four years ago.

AIThe 8th BAAI Conference will be held June 12–13 at the Zhongguancun Innovation Center in Beijing, with Turing Award laureates and China's large-model leaders attending. Core focuses include world models and agents, plus two new flagship sessions on AI-native education and the token economy. The event will feature 25 forums, over 200 speeches, and a first-ever on-site AI agent conference companion for real-time listening and summarization.

AICohere and Cohere Labs released North Mini Code 1.0, an open-weights 30B-A3B mixture-of-experts model for code generation and agentic terminal tasks, under Apache 2.0. The model has 256K context and 64K max output, and is trained for tool use. Its benchmark table lists Terminal-Bench v2 at 36.0, SWE-Bench Verified at 67.6, and LiveCodeBench v6 at 70.3, below Qwen3.6 on several tasks.

Why it matters: The card lists benchmark results against Qwen3.6, Gemma4, and other models, showing where North Mini Code trails on some coding and agentic tasks.

AIEthan Mollick is releasing Co-Existence on October 20, a new book about working with AI systems that are sometimes, but not always, better than humans. The book follows his 2024 title Co-Intelligence, which he says was written about an era of chatbots rather than autonomous agents. Mollick also reports writing every chapter draft himself while using AI readers and fact-checkers, and building the book's website with Claude Code using Opus 4.8.

AIAntigravity has enabled the /teamwork-preview command for all paid plans, letting users run parallel implementation and verification agents on complex tasks. The post says the team built a working OS with it, but warns that it can consume a large number of tokens.

AIAnthropic's internal data shows Claude is accelerating AI development, possibly toward recursive self-improvement in which AI autonomously builds a more capable successor. Sam Bowman says the acceleration in technical R&D over recent months has been wild and faster than expected.

AIBaidu CoBuddy is now available for free on Novita AI, a code-focused model aimed at developers and AI agents. It offers a 131K context window, up to 65K output tokens, and native tool calling. The model is served through Novita's serverless API for high-throughput, low-latency inference.

AICognition introduced the AI Productivity Guarantee, under which it will issue credits up to $10M if Devin delivers less engineering value than enterprise customers pay for. The company uses an AI estimator to measure hours of productive output, validated against engineers' own estimates of how long the same work would have taken by hand. Value is converted to dollars at a standard global rate and compared against each customer's consumption near the end of the annual contract.

Why it matters: The post explains how Cognition estimates Devin's output in hours and backs the estimate with a $10M credit commitment, a concrete model for measuring AI vendor value.

AICognition built an automated agent that classifies Devin sessions as productive and estimates the human engineering hours each one would have taken. On 233 held-out sessions the estimator reached an rlog of 0.74, with individual errors often 2 to 3 times in either direction but roughly unbiased in aggregate. The system is calibrated to underestimate and is currently running with Devin customers.

Why it matters: The post shows how the measurement design, from hours-based metrics to conservative calibration, determines whether agent productivity estimates can be trusted in aggregate.

AIEugene Yan says stronger models have made finding software vulnerabilities easier, so the bottleneck has moved to verification, triage, and patching. He shares lessons from working with security teams on these new bottlenecks and links to a Claude blog post on using LLMs to secure source code.

AIGoogle has released a new version of Gemini 3.5 Flash in Antigravity that reportedly shows less drift and greater endurance on harder tasks. The company also reset Gemini rate limits for all users so they can start using the updated model immediately.

AIMiniMax has released MiniMax-M3, a native multimodal model with a 1M-token context window, roughly 428B total parameters, and about 23B activated parameters. The model introduces MiniMax Sparse Attention, which the source says delivers 9× prefill and 15× decode speedups over M2 at 1M context. M3 supports enabled, adaptive, and disabled reasoning modes through the thinking parameter, and weights are available on Hugging Face.

Why it matters: The source gives concrete attention-efficiency figures and three reasoning modes, which helps readers judge long-context cost against deployment choices.

AICognition has announced Devin Desktop, the next generation of Windsurf, which makes the Agent Command Center the default IDE surface for managing local and cloud agents, PRs, and context. Spaces let related agents share context, and Agent Client Protocol (ACP) support lets any ACP-compatible agent run alongside Devin. The IDE remains fully backwards-compatible with Windsurf, including editor extensions, keybindings, LSPs, and terminal workflows.

AIPaddleOCR and ERNIE Image are now available as official Dify plugins, bringing document parsing and image generation into Dify's agent workflows. PaddleOCR, powered by PP-OCRv5, PP-StructureV3, and PaddleOCR-VL, turns images, scanned PDFs, and multilingual documents into structured data for chunking, vectorization, and RAG, with private or on-prem deployment supported. ERNIE Image offers free generation, a Turbo mode with 8-step inference, and an OpenAI-style API.

AIMiniMax released M3, an open-weight model with a 1M-token context window, native image and video input, and desktop operation support. The post credits a new sparse attention architecture, MSA, for long-context gains, reporting over 9x prefilling and over 15x decoding speedups and 59.0% on SWE-Bench Pro. The API and MiniMax Code are available now, with the technical report and open weights promised within 10 days.

Why it matters: The post pairs a new sparse attention design with benchmark figures and a 1M-token context window, letting readers judge the architecture's practical effect on long-context work.

AIXiaomi describes an end-to-end inference optimization for the MiMo-V2.5 series, centered on Hybrid SWA, which it says cuts KVCache storage to roughly 1/7 of Full Attention. The post covers a dual KVCache pool design, SWA-aware prefix cache matching, the GCache distributed cache, and scheduling changes, and reports cache hit rates averaging 93% in server-side observations. It also covers prefill and decode optimizations, multimodal encoder improvements, and open-source contributions to SGLang.

Why it matters: The post explains how Hybrid SWA's theoretical KVCache savings were realized in production through dual pools, SWA-aware prefix caching, and tiered storage, giving concrete engineering patterns for long-context inference.

AICognition describes autonomous testing in Devin, where the agent writes a source-grounded test plan, operates the app through computer use, and returns labeled screenshots and an annotated video. Login steps are handled by a deterministic testing skill, and the company says test runs approved per day more than doubled in recent months. Known limits include timing errors with transient UI elements and models sometimes triggering states through JavaScript instead of clicking the interface.

Why it matters: The post explains how computer use, test plans, deterministic login scripts, and annotated recordings let Devin verify its own code changes end to end.

AICognition raised over $1B at a $26B valuation, led by Lux Capital, General Catalyst, and 8VC. Enterprise Devin usage grew more than 10x since the start of this year, and run-rate revenue reached $492M. The company also said it launched SWE-1.6, which reaches up to 950 tok/s and has become the most used model in Devin Desktop.

AIMiniMax has upgraded its Agent, renamed Mavis, and introduced Agent Teams that run multiple role-based Agents in parallel on desktop. The team uses Leader, Worker, and Verifier roles so complex tasks can be split, checked, and reported at key checkpoints, and it merges TokenPlan and Agent Plan into one subscription with credits shared between Agent and API. The post also discusses the added token, handoff, and retry costs of multi-Agent work, and says the Agent will be open-sourced alongside MiniMax M3.

Why it matters: The post explains why multi-Agent helps long tasks and where its verification, token, and aggregation costs come from, useful for judging when a team setup beats a single Agent.

AIEthan Mollick argues that using AI as a default for writing, without thinking, risks undermining the human effort that builds skill and style. He cites two Wharton-linked studies: a Turkish high school experiment where ChatGPT access hurt test performance, and a Taipei Python course where a personalized AI tutor raised exam scores by 0.15 standard deviations. Mollick calls the difference how AI is used, not whether, and notes that the tools for tutor-style learning are not intuitive to access.

AIGoogle claimed a team of agents built an operating system from a single prompt for about $916 in API fees, using Gemini 3.5 Flash and Antigravity 2.0. The authors argue the prompt was many thousands of lines, the scaffold and human intervention are undefined, and no code, logs, or similarity analysis were released to verify the claim. They still see value in such open-world evaluations, which need stronger methodological norms and independent scrutiny.

AICognition's Devin AI software engineer can now build, run, and test code natively in its own Windows virtual machine, including migrating .NET Framework apps to .NET Core. The Windows capability is in beta for Enterprise Cloud and Dedicated Deployment customers, with the same SOC 2 Type II and ISO 27001 controls as the Linux version. Citi and Mercedes-Benz are named as existing Devin users.

AIGoogle's Gemini 3.5 Flash outperforms Gemini 3.1 Pro on Terminal-Bench 2.1 (76.2%), GDPval-AA (1656 Elo), and MCP Atlas (83.6%). The post also claims it is 4x faster than other frontier models, or 12x in Antigravity, and reports 83.6% on MMMU-Pro for multimodal performance.

Why it matters: The post gives specific benchmark scores against Gemini 3.1 Pro, letting readers compare coding, agentic, and multimodal results directly.

AIAt Google I/O, Google introduced Gemini 3.5 Flash, which the author says has become part of the daily research cycle. The author says a team of agents in Antigravity 2.0 recreated the original AlphaZero paper and built a playable web version from two prompts, coding the reinforcement learning pipeline in JAX/Flax and training a ResNet model via self-play on multi-TPU pods.

AIGoogle's Gemini 3.5 Flash is available today globally, according to Oriol Vinyals. The post invites developers to build agents and apps with it and links to Google's blog for more details.

AIGemini 3.5 Flash produces fully tactile, interactive HTML/SVG hardware simulations in a single shot when given complex agents and tasks. The output includes bump-mapped metals, spring physics, and procedural audio, according to the post.

AIGoogle's Gemini 3.5 Flash reaches 76.2% on Terminal-Bench 2.1, 1656 Elo on GDPval-AA, and 83.6% on MCP Atlas, showing strong performance on multi-step agentic tasks. The model is positioned as an ultra-fast reasoning engine for powering AI agents.

AIComposer 2.5 is now the most-chosen model in Cursor, according to Cursor co-founder Michael Truell. To celebrate, Cursor is giving users 10x usage for the rest of the day.

AIMichael Truell of Cursor says Composer 2.5 is a significant step up from Composer 2. He adds that this is only the start of work with SpaceXAI, with more improvements expected soon. Cursor's announcement describes the model as more intelligent, better at long-running tasks, and more reliable at complex instructions, with doubled included usage for the next week.

AIEugene Yan shares Cloudflare's description of a vulnerability discovery harness that runs eight stages, from reconnaissance to report writing. The pipeline uses about 50 concurrent agents to hunt for bugs, independent agents to try to disprove findings, and a trace step to confirm whether attacker input reaches each bug. Reachable findings feed back into new hunt tasks before a report is written against a predefined schema.

AICognition has released Auto-Triage in Devin Automations, which lets Devin respond to Slack messages, Linear events, GitHub activity, schedules, and webhooks. Devin can investigate with connected observability tools and the codebase, then post a summary, tag an owner, or open a PR. Devin runs in network-sandboxed environments with added protections against prompt injection and data exfiltration, and a limited-time offer gives $200 in credits for a first automation.

Why it matters: The post shows how an agent handles alerts and bug reports from existing team channels, a practical pattern for teams weighing automated incident response.

AIAmazon has rolled out Alexa for Shopping to all customers, combining its Rufus and Alexa+ assistants into a single AI shopping tool. The assistant remembers users' preferences, past purchases, and conversations, and carries that context across phones, laptops, and Echo devices.

AIEugene Yan relays two evaluations of Mythos: UK AISI reports it completed a 32-step network attack, estimated at about 20 expert hours, in 6 of 10 tries and was the first model to solve its end-to-end cyber ranges. XBOW's evaluation describes its performance as token-for-token and unprecedented in precision. The post links both AISI and XBOW blog posts for details.

AISoumith Chintala posted more demos of Interaction Models collaborating live on system design, paper reading, and fact-checking with generative UI. A quoted demo shows the model seeing the user's screen and drawing on it together while building a scalable system architecture.

AIAwni Hannun says Claude Code's new agent view is where he starts and manages much of his work, calling it an exceedingly useful feature. Anthropic's Claude account introduced agent view as a single list of all sessions, available now as a research preview.

AIThinking Machines, founded to advance human-AI collaboration, says its first bet is interactivity built into the model rather than added as scaffolding around a turn-based core. The company argues that how people work with AI matters as much as how intelligent the model is, and that interactivity should scale with intelligence. The post links to a blog detailing these interaction models.