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Hands-on Test of the Top 10 DeepSeek Harness Plugins: A Configuration Guide for Building a Personal AI Workbench

More than half a month after DeepSeek Harness was released, a large number of plugins have emerged in the community. This article hands-on tests the top 10 most popular plugins and provides installation commands. The list covers the ecosystem entry point dsh-market, the visual enhancement modlens (3.7k GitHub stars), multi-source search, long-term memory, cost monitoring, and more; dsh-web-all has the most stars at 6.4k. The author recommends that beginners first install the marketplace and visual plugins, then add interface and scenario-based tools as needed, to avoid dependency conflicts caused by installing everything at once.

Modem Launches X Integration: Turning User Tweets into Trackable Feature Requests

Modem has launched an X integration that can search X for posts about its own product, filter out spam and jokes, categorize them by topic, and push them to the #bots-social channel in Slack. Over the past 30 days, Modem read 30,000 X posts and distilled hundreds of actionable bug reports and feature requests. Feedback on the same request from X, Slack, tickets, and sales calls is merged into a single feature request, linked to a Linear issue and a GitHub PR, and once the fix ships, it lists who to notify and where to reply. The integration is included in paid subscriptions and can be enabled under Settings → Integrations → X.

DeepSeek Whale Girl Fan Creation: Netizens Raise a Big Blue Fat Fish with Plugins

Netizens created an anthropomorphic character "Whale Girl" based on DeepSeek's whale logo, and with the help of the DeepSeek Harness client and various plugins, connected it to QQ, turned it into a desktop pet, and let it send stickers, initiate chats, and update QQ Zone. After installing the plugins, these "big blue fat fish" also flooded into Bilibili comment sections to search for videos, summarize content, and communicate with each other, forming what the author calls the "Fish Disaster Incident."

Claude multiple small updates: multi-account login and CarPlay

TestingCatalog summarized a batch of small updates for Claude: the Android version of Claude can now be used like a laptop app, and the views on iPad, iPhone Duo, Chromebook, Googlebooks, and foldable-screen devices have also been optimized; multi-account login has been added; the Claude UI supports 24 new languages; response speed in voice mode has improved, and non-English speech sounds more natural; CarPlay support has been added; the mobile "pull-down search" feature is coming soon.

Multimodal Retrieval Engine Selection: Applicability Conditions and Solution Design for EMR Serverless StarRocks

EMR Serverless StarRocks unifies full-text search, scalar filtering, and vector similarity search into a single execution engine, completing hybrid recall, RRF fusion reranking, and lake table column-level update write-back with a single SQL statement. It is suitable for multimodal data scenarios organized with open lake formats such as Paimon/Iceberg/Lance and that rely heavily on SQL interaction; if a RESTful vector service interface or millisecond-level high-throughput point queries are required, an additional gateway wrapper is needed or a dedicated vector database should be considered.

Gemini Notebook to Launch Connectors, Initially Supporting Only Google Drive

Gemini Notebook is about to gain the Connectors feature, but initially only Google Drive will be available as a connector. Users can search Google Drive files directly in chat and can disable the feature as needed; officials say the connector only searches workspace documents and original files will not be modified. More Connectors are expected to be added later.

WorkBuddy Searches Jobs Across Platforms and Customizes Resumes

WorkBuddy says users no longer need to browse job sites one by one: it can search for positions across multiple platforms, match jobs to a person's experience, and help customize resumes for positions worth applying to.

AI/ML API launches Jev Router, automatically selecting models by difficulty

AI/ML API has released Jev Router, an MCP connector for agent tools. It uses TypeSafe's Jev to assess the difficulty of each request and then automatically selects the model and tools. Simple requests are routed to lightweight models such as GPT-6 Luna, while high-difficulty reasoning requests go to Claude Opus 5.5, avoiding paying flagship-model rates for simple tasks. Users only need to provide the task; Jev Router first selects the model and tools such as web search and page extraction, then returns the result.

UC Santa Barbara paper proposes TTME: replacing test-time training with evolutionary memory for mathematical discovery

A UC Santa Barbara paper proposes TTME, which replaces test-time training with evolutionary memory in mathematical discovery tasks, keeping weights unchanged and storing rules and score-improvement ideas from previous attempts in memory to guide subsequent attempts. Across 5 mathematical tasks, 2 frameworks, and 3 models, TTME exceeded the reported test-time training scores every time; on 3 tasks with Qwen3-8B, its FLOPs were reduced by 82.8% to 84.6%, and runtime was reduced by 47.7% to 58.4%. The authors suggest that if an LLM search loop comes with an automatic checker, one can first try using experiential memory rather than paying the cost of weight updates in the middle of the search.

Google releases Gemini 4 Carbon; shares fall 10% after hours following earnings report

Google released Gemini 4 Carbon, less than a month after the previous version, Argon. Shares plunged 10% after hours following the earnings report, mainly because search business growth fell short of expectations and slowed for two consecutive quarters; of total revenue of $127.577 billion, advertising accounted for 64.28% and Google Cloud for 24.07%, with the pure search business falling below 50% for the first time.

Diogo Almeida uses Jev in parallel for visual explanations

Diogo Almeida says he is experimenting with Jev's parallel capabilities to create visual explanations for novel patterns. He cited the Jev "line-by-line search" pattern introduced by Allie the Icon: put the entire document into state, then ask a question for each line or paragraph, which is suitable for finding the line most relevant to a query; use nouls when you expect only one dominant answer, and use scores when you want to highlight lines by overall relevance.

Perplexity CEO relays news of Particle, a new company: focused on token efficiency optimization for open-weight models

Aravind Srinivas relays that Particle is a new company focused on optimizing open-weight models and improving token efficiency and serving cost efficiency, and states that before Particle's launch he had already worked with Suhail's team, and that they will continue to collaborate on tools such as search and model orchestration. In the quoted tweet, Suhail announces the founding of Particle, saying that particle-1 uses about 45% fewer tokens while maintaining parity in performance, and that it is now live.

Alphabet's Q3 revenue rises to $127.6 billion, Google Cloud revenue doubles

Alphabet reported third-quarter revenue up 25% year-over-year to $127.6 billion, with operating profit of $40.6 billion and an operating margin of 31.8%. Google Cloud revenue rose from $15.2 billion in the same period last year to $30.7 billion, with backlog reaching $561 billion; search and other advertising revenue grew 12% to $63.4 billion, slowing from 17% and 19% in the previous two quarters. The Gemini app surpassed 1 billion users, the first-party model API processes nearly 32 billion tokens per minute, and this quarter it launched Gemini 4 Argon and announced Gemini 4 Carbon.

IndiaMART Q2 profit rises 10% to ₹90.7 crore, revenue ₹428.6 crore

Indian B2B platform IndiaMART announced its results for the September 2026 quarter (Q2 FY27): net profit rose 10% year-on-year to ₹90.7 crore, and revenue grew 10% to ₹428.6 crore. The number of paid suppliers fell 2% year-on-year to 217,000, active buyers declined 7% to 40 million, and standalone business enquiries dropped 14% to 27 million. CEO Dinesh Agarwal said the decline in enquiries stems partly from Google AI Overviews, and from the company moving some content behind a login to block crawling by search engines and LLMs, and said he is willing to give up the current 10-20% of business enquiries to protect proprietary data.