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dashi-ppt-skill provides a PPT skill package for AI Agents

The open-source project dashi-ppt-skill is released as an Agent skill package, providing AI Agents with the ability to generate presentations. According to a report by Alibaba Cloud Developer Community AI, this skill package generates HTML presentations with a built-in editing console, and can export editable PPTX that restores each node when needed. The project includes 12 visual themes and 1,020 layout pages, following a template orchestration approach, and by default only replaces text without modifying the layout; the official claim is that it provides 8,576 adjustable controls. The project uses the AGPL-3.0 license and can be installed into local Agents such as Claude Code, Codex, and Cursor via npx skills add; exporting PPTX/PDF requires Chrome, Chromium, or Edge installed on the local machine. Currently there is only this one report, and no subsequent developments have been reported.

View story:dashi-ppt-skill provides a PPT skill package for AI Agents

Shao Meng introduces Tibo's nine-step process for building an AI UGC creator team with Agents

On October 24, 2026, Shao Meng compiled and introduced a process from Tibo: using Agents to build your own AI UGC creator matrix. The process is designed by buyer segment, with 3–4 AI creators who have fixed faces and daily routines, completing each day the tasks of finding viral hits, rewriting them in the character's voice, rendering with the same face, and scheduling 24 hours in advance; humans only review the queue and weekly topic updates. The process has 9 steps in total and comes with 12 prompts, starting from connecting to the Revid MCP and writing the brain.md master brain, through creating faces, setting topics, breaking down viral structures, running daily batches, operating independent accounts, and weekly reviews. The article emphasizes that account bios should state AI creator, that fake reviews and health/medical claims are prohibited, that the product should occupy only one beat of the video, and that content is only scheduled rather than published directly so as to leave room for human review. There are currently no subsequent developments.

English translation is being prepared.

Perplexity Agent API launches Batch API

On October 23, 2026, Perplexity launched the Batch API for its Agent API. According to the same report, this batch processing interface supports up to 50,000 requests per file, each request runs the full agent loop, and it supports the use of web_search and fetch_url in batch mode. The company states that this can be used for large-scale data enrichment tasks, such as enriching a table containing 50,000 companies with real-time web data overnight. The feature is currently live, and there are no subsequent developments yet.

Perplexity Agent API launches Batch API

On October 23, 2026, Perplexity launched the Batch API for its Agent API. According to the same report, this batch processing interface supports up to 50,000 requests per file, each request runs the full agent loop, and it supports the use of web_search and fetch_url in batch mode. The company states that this can be used for large-scale data enrichment tasks, such as enriching a table containing 50,000 companies with real-time web data overnight. The feature is currently live, and there are no subsequent developments yet.

View story:Perplexity Agent API launches Batch API

Shao Meng introduces Tibo's nine-step process for building an AI UGC creator team with Agents

On October 24, 2026, Shao Meng compiled and introduced a process from Tibo: using Agents to build your own AI UGC creator matrix. The process is designed by buyer segment, with 3–4 AI creators who have fixed faces and daily routines, completing each day the tasks of finding viral hits, rewriting them in the character's voice, rendering with the same face, and scheduling 24 hours in advance; humans only review the queue and weekly topic updates. The process has 9 steps in total and comes with 12 prompts, starting from connecting to the Revid MCP and writing the brain.md master brain, through creating faces, setting topics, breaking down viral structures, running daily batches, operating independent accounts, and weekly reviews. The article emphasizes that account bios should state AI creator, that fake reviews and health/medical claims are prohibited, that the product should occupy only one beat of the video, and that content is only scheduled rather than published directly so as to leave room for human review. There are currently no subsequent developments.

View story:Shao Meng introduces Tibo's nine-step process for building an AI UGC creator team with Agents

Artificial Analysis publishes AA-AgentPerf results for Muse Spark Open

Artificial Analysis on October 24, 2026 published on AA-AgentPerf preliminary test results for Meta's newly open-weight model Muse Spark Open. The model is a 816B-parameter, 42B-active MoE, scoring 39 on the Artificial Analysis Intelligence Index. Tests show that NVIDIA B300 and GB300 each reach about 150M tokens/s per megawatt of power under throughput-first configurations; GB300 reaches about 108M and B300 about 92M at 100 tok/s output speed; AMD MI355X reaches 70M tokens/s per megawatt at 65 tok/s. Of the model's 62 layers, 46 use 2,048-token sliding window attention, reducing KV cache requirements at 1M context by about 75% versus full attention. Meta released an NVFP4 checkpoint, and AMD released an MXFP4 checkpoint. There are currently no subsequent development facts.

Artificial Analysis launches AA-AgentPerf results for Muse Spark Open

Artificial Analysis on October 24, 2026 published on AA-AgentPerf preliminary test results for Meta's newly open-weight model Muse Spark Open. The model is a 816B-parameter, 42B-active MoE, scoring 39 on the Artificial Analysis Intelligence Index. Tests show that NVIDIA B300 and GB300 each reach about 150M tokens/s per megawatt of power under throughput-first configurations; GB300 reaches about 108M and B300 about 92M at 100 tok/s output speed; AMD MI355X reaches 70M tokens/s per megawatt at 65 tok/s. Of the model's 62 layers, 46 use 2,048-token sliding window attention, reducing KV cache requirements at 1M context by about 75% versus full attention. Meta released an NVFP4 checkpoint, and AMD released an MXFP4 checkpoint. There are currently no subsequent development facts.

View story:Artificial Analysis publishes AA-AgentPerf results for Muse Spark Open

Bayer Crop Science builds an agentic decision engine based on AgentCore

Bayer Crop Science built ADE (Agentic Decision Engine), a multi-agent natural language interface based on Amazon Bedrock AgentCore, covering its Connected Decision Engine. According to information released by AWS Machine Learning on October 24, 2026, ADE runs 22 specialized agents in production, routed by a Supervisor Agent according to intent, and exposes backend APIs as MCP tools via AgentCore Gateway. In the first phase, about 80% of user questions were resolved without engineer intervention; fault diagnosis time was shortened from manual troubleshooting that previously took more than 1 hour to within 10 minutes. There are currently no subsequent development facts.

Bayer Crop Science builds an agent decision engine based on AgentCore

Bayer Crop Science built ADE (Agentic Decision Engine), a multi-agent natural language interface based on Amazon Bedrock AgentCore, covering its Connected Decision Engine. According to information released by AWS Machine Learning on October 24, 2026, ADE runs 22 specialized agents in production, routed by a Supervisor Agent according to intent, and exposes backend APIs as MCP tools via AgentCore Gateway. In the first phase, about 80% of user questions were resolved without engineer intervention; fault diagnosis time was shortened from manual troubleshooting that previously took more than 1 hour to within 10 minutes. There are currently no subsequent development facts.

View story:Bayer Crop Science builds an agentic decision engine based on AgentCore

Tripo showcases Claude Agent generating 65 3D models to build a game

On October 23, 2026, Tripo showcased a 3D content generation case completed by a Claude agent: over 2 days and across 5 worlds, the agent progressively generated 65 Tripo 3D models for building game scenes. Tripo also encourages users to create their own 3D games in a vibe coding way. Currently this news comes from a single source, Tripo, with no cross-verification from other independent sources and no disclosure of follow-up progress.

Tripo showcases Claude Agent building a game with 65 generated 3D models

On October 23, 2026, Tripo showcased a 3D content generation case completed by a Claude agent: over 2 days and across 5 worlds, the agent progressively generated 65 Tripo 3D models for building game scenes. Tripo also encourages users to create their own 3D games in a vibe coding way. Currently this news comes from a single source, Tripo, with no cross-verification from other independent sources and no disclosure of follow-up progress.

View story:Tripo showcases Claude Agent generating 65 3D models to build a game

Artificial Analysis releases Coding Agent Index v2.0

On October 23, 2026, Artificial Analysis released Coding Agent Index v2.0, replacing DeepSWE with Cognition's FrontierCode v1.1 and tightening the repository question-answering scoring; the leaderboard evaluates model-plus-harness combinations. Reports that day showed Claude Code paired with Claude Opus 5.5 (max) topping the list with 61.7 points, Claude Code paired with Sonnet 5.5 second with 59.3 points, Muse Code paired with Muse Wonder Full at 58.9 points, and the first OpenAI combination, Codex paired with GPT-6 Astra, at 54.7 points. Regarding comparisons between the old and new leaderboards, earlier reports said the average score of 21 configurations fell from 58.8% to 57.1%; later reports said the mean for the same batch of 21 configurations dropped from 54.8 to 47.4, with 20 declining, and stated that the main reason was FrontierCode's mean of about 45.1%, far below DeepSWE's 65.6%.

Artificial Analysis releases Coding Agent Index v2.0

On October 23, 2026, Artificial Analysis released Coding Agent Index v2.0, replacing DeepSWE with Cognition's FrontierCode v1.1 and tightening the repository question-answering scoring; the leaderboard evaluates model-plus-harness combinations. Reports that day showed Claude Code paired with Claude Opus 5.5 (max) topping the list with 61.7 points, Claude Code paired with Sonnet 5.5 second with 59.3 points, Muse Code paired with Muse Wonder Full at 58.9 points, and the first OpenAI combination, Codex paired with GPT-6 Astra, at 54.7 points. Regarding comparisons between the old and new leaderboards, earlier reports said the average score of 21 configurations fell from 58.8% to 57.1%; later reports said the mean for the same batch of 21 configurations dropped from 54.8 to 47.4, with 20 declining, and stated that the main reason was FrontierCode's mean of about 45.1%, far below DeepSWE's 65.6%.

View story:Artificial Analysis releases Coding Agent Index v2.0

Dongxi NLP says Agent-building ability is the least important

On October 23, 2026, the blogger "Ma Dongxi NLP" published a post arguing that in "Agent +" scenarios, the ability to build Agents is the least important, and what matters more is familiarity with the business of specific scenarios. The same article also said that in the current context, an AI engineer has little to do with AI and is not valuable, and advised young people in the AI field to turn to training, quantization, inference, or AI infrastructure construction. At present, this view is seen only in this one source, and there are no other development facts.

Dongxi NLP says Agent-building capability is the least important

On October 23, 2026, the blogger "Ma Dongxi NLP" published a post arguing that in "Agent +" scenarios, the ability to build Agents is the least important, and what matters more is familiarity with the business of specific scenarios. The same article also said that in the current context, an AI engineer has little to do with AI and is not valuable, and advised young people in the AI field to turn to training, quantization, inference, or AI infrastructure construction. At present, this view is seen only in this one source, and there are no other development facts.

View story:Dongxi NLP says Agent-building ability is the least important

Carl's AI Watts shares a beginner's ranking of Personal Agents

On October 23, 2026, Carl's AI Watts published an article ranking 13 Personal Agents by the number of apps they can connect to. According to the article, meta muse tops the list with 54, chatgpt dots has 50, gemini spark has 35, today and poke each have 30, grok bot has 20, manus cue has 15, Instinct has 12, and hark, Lingguang 2.0, Qwen Go, Hermes, and OpenClaw each have about 10. The article also notes that Hark is free with no feature limits, muse is only available in the US and Canada, and Qwen Go, Lingguang 2.0, cue, and Instinct still require invitation-only beta access. This ranking is currently only seen in this source, with no subsequent developments yet.

View story:Carl's AI Watts shares Personal Agent entry rankings

Replit launches Monitoring Agent

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Anthropic donates Agent Skills to the Agentic AI Foundation

Anthropic announced that it will donate Agent Skills to the Agentic AI Foundation (AAIF). According to its first-party information, MCP had previously also been donated to the same foundation; since December 2025, more than 70 agent platforms have adopted the standard, including ChatGPT, Cursor, GitHub Copilot, and VS Code. Subsequent reports stated that AAIF, under the Linux Foundation, announced on October 22, 2026 that it had accepted four projects: in addition to Anthropic's Agent Skills, these include OpenAI's Open Responses, Hugging Face's OpenEnv, and Alibaba's OpenSandbox; Agent Skills is a universal format that allows different agents to reuse business knowledge and workflows, and Anthropic made it public as an open standard in December 2025. Reports also stated that the donation includes the name, logo, the GitHub organization account agentskills, and the agentskills.io domain; going forward, a technical operations committee composed of core maintainers from multiple organizations will decide the development direction, with Anthropic's David Soria Parra and Mahesh Murag serving as lead maintainers; the number of projects under AAIF has grown from three at its founding to ten.

Carl's AI Watts shares Personal Agent entry rankings

On October 23, 2026, Carl's AI Watts published an article ranking 13 Personal Agents by the number of apps they can connect to. According to the article, meta muse tops the list with 54, chatgpt dots has 50, gemini spark has 35, today and poke each have 30, grok bot has 20, manus cue has 15, Instinct has 12, and hark, Lingguang 2.0, Qwen Go, Hermes, and OpenClaw each have about 10. The article also notes that Hark is free with no feature limits, muse is only available in the US and Canada, and Qwen Go, Lingguang 2.0, cue, and Instinct still require invitation-only beta access. This ranking is currently only seen in this source, with no subsequent developments yet.