#Tutorial/How-to

AICursor's new /visualize command builds charts and diagrams directly in the chat, letting users ask follow-up questions in the same conversation to get new charts. The feature analyzes data and shows answers inline, and it is available now in the Agents Window.

AIProximal has published details of its internal post-training infrastructure, which runs on Modal GPUs and Kubernetes to support its experiments. The company says the blog is written to be educational about how the stack works.

AISam from LangChain discusses where decision models fit inside an agent harness and how to use Jev with LangChain. The post links to a LangChain blog on building a harness with Jev, which the background post says Jev from typesafeai popularized alongside OpenAI's Decisions API and Databricks' ai_decide function.

AIA ComfyUI developer generated 15-second 448×256 video in 15 seconds or less on one RTX 5090 using MiniMax H3 with FastVideo's FastH3 V2 checkpoint in four sampling steps. The setup combined sparse attention, a smaller ClipProj text encoder, a pruned INT8 checkpoint, and a fused FP4 MLP, cutting VRAM needs from 80GB to under 30GB. The custom ComfyUI node is open source.

AILeapfrog, a small team doing high-volume AI visual and production work for fashion and brand clients, is building a "one brain" system that makes company knowledge and client context searchable through natural-language agents. The starter stack described is OpenClaw in a sandbox, a GitHub repository, Obsidian on the local machine, and Telegram as the access point. The system's research structure had roughly 1,200 files at the time of the talk.

AIJohn Groetzinger, writing in a personal capacity rather than for Cisco, argues that enterprise skills need packaging, evaluation, syncing, and distribution rather than scattered markdown files. He describes using skills to make cheaper models viable, converting curated TAC knowledge-base articles into maintained skills, and rolling out an eval framework across teams. He also describes syncing a repository README to Confluence with a deterministic script.

AIAmazon Bedrock AgentCore payments lets AI agents pay for model inference one request at a time, using x402 with USDC on the Base network. Incarna used the service to connect its agents to BlockRun, a pay-as-you-go router serving more than 90 models from more than 15 providers. Spending limits are enforced at the infrastructure layer, outside the model.

AIGoogle Cloud Tech says skills provide Gemini with instructions and tools provide it with connections, while grounding supplies the context it needs. The post argues that grounding Gemini in enterprise data yields more accurate, higher-impact results.

AIGoogle Cloud Tech suggests packaging proven procedures as Skills and sharing them through one central registry so the whole team can access them. The post claims this raises accuracy and reduces token spend.

AIThe author argues that agent systems are converging on shared primitives grouped into doing the work, continuing the work, and delegating the work. These include instructions and skills, tools and connectors, sandboxes, sessions, compaction, schedules, and subagents. He also flags memory, proactivity, and agent identity as emerging areas still lacking settled standards.

AIAWS published a reference architecture for running multiple teams on one Amazon SageMaker HyperPod EKS cluster, with each team isolated in its own Kubernetes namespace. The design combines AWS IAM Identity Center for authentication, per-team SageMaker AI domains, HyperPod Task Governance for fair resource allocation, and namespace-level cost allocation for per-team spend visibility.

AI3D is still impressive with GPT-6 Astra. I had it read my Memory and, based on my preferences, make a poster with several models built in Blender. The model details, materials, and lighting all come out very well.

AIAnthropic says the fastest way to use its new credits is through Claude Managed Agents. Developers can build an agent with the claude-api skill in Claude Code by running /claude-api managed-agents-onboard.

AIFish Audio's Drama 3 voice model lets users direct tone, emotion, and pacing in plain language, and can shift emotion mid-sentence. The poster, who found it remarkably effective in testing, says the control over delivery is unlike anything previously seen. A preview is available through the API as drama-3-preview.

AIHamel Husain answers that the same model can usually serve as both the main task model and the evaluation judge. He advises testing whether the judge agrees with human labels on a held-out test set.

AIThe author says GoodCase's case clustering, similar-case recommendations, mobile layout, and multi-country web acceleration, including how storage is split across Vercel, Cloudflare, and Supabase, were all rewritten with Opus 5.5. The post also notes Claude's usage quota has held up well for this work, with a longer write-up planned.

AIThe author says Opus 5.5 keeps improving and works well for producing weekly product short videos, with all materials generated directly without extra services. GoodCase added 269 new AI showcase cases, prompts, and 7 new Skills, bringing its total to 1,699 cases, 95 Skills, and 426 creators. The post also highlights awesome-seedance, which now lists 795 video cases, 367 prompt retests, 27 prompt templates, and 77 installable video Skills.

AITessl's Code Review defines review standards as skills in the repository, called lenses, routed to files by a repo-owned profile file. Because these team-visible standards are portable, lessons from review can feed back into code generation and maintenance, not only the next review.

AIGrok bot works great with foldable phones. Chat on the left, publish directly on the right.

AIAllie K. Miller describes a workflow where she had Instinct write a large prompt for Codex to execute her 19-item task list, then emailed that prompt to herself. She also had Instinct write the prompt telling Codex to search her email and find the note Instinct left for it.

AIReplit and Databricks integration, now generally available with native Lakebase support, lets enterprise teams build apps from plain-language prompts using Replit Agent and deploy them as Databricks Apps. Deployed apps inherit automatic user authentication and Unity Catalog access controls, and Replit Agent auto-provisions a managed Lakebase Postgres database for operational data. Lakebase keeps app-written data inside the Databricks perimeter instead of a separate external database.

AIElevenLabs explains how to build meeting transcription products using its Scribe v2 and Scribe v2 Realtime models through its API. Real-time transcription suits live captions and in-meeting bots, while batch transcription suits post-meeting notes and records, with Scribe v2 Realtime reporting 150 ms latency and supporting up to 50 key terms for prompting.

AIThe author suggests installing a coding agent such as Pi or DeepSeek Harness in a cloud computer and allocating unused Code plan quota to it. Grok Bot could then use those tokens to write code and render videos, so leftover quota is not wasted.

AILangChain has added three engineering upgrades to Skills in its Deep Agents framework: tool-binding Skills, pinned Skills, and mid-thread reloading. Tool-binding lets a SKILL.md declare tools via metadata.include_tools, so tools are injected only when the Skill is read, and pinned Skills inject full instructions before the next model call, skipping a round trip. Setting skills_metadata to None rescans the Skills library mid-thread without restarting, at the cost of invalidating the cache.

AINVIDIA AI highlights how H-Company optimizes vision-language model (VLM) serving for computer use agents using NVIDIA Dynamo. The post is a broadcast announcement with a link, and no performance figures or technical details are given in the text.

AIMuse, Dots, or other agents with cloud computers can all be used.

AIThe author set up a Grok bot to produce a daily morning AI news video on a schedule, running content collection, code writing, and video rendering entirely on Grok's cloud virtual machine without local computers. The author says the results are quite good and shares the full prompt so others can run the same workflow with their own Grok bot.

AI笑死，你永远不知道一个设计师会在产品的哪个地方开始抠细节，做着做着就跑偏了。 把"关于"页面这个罗盘做成 3D 的，细节非常丰富，设计比较现代，而且指针还会跟随你的鼠标去转动

AIThe author built a Qimen Dunjia chart-plotting teaching website using Opus 5.5 and has now launched it. After positive user demand, the site was improved with added exercises and explanations to function more like a learning platform.

AIEvery moved its Slack-based Every Agent from its own OpenClaw fleet to Anthropic's Claude Managed Agents, letting the team focus on building a shared coworker. The newsletter, written by engineer Paridhi Agarwal, covers the gains and trade-offs of stopping self-run agent infrastructure.

AIJohns Hopkins astrophysicist Brice Ménard, working as an Anthropic researcher, used Claude Science to produce the first complete map of the sky in ultraviolet light. Claude orchestrated agents to merge GALEX, Swift, and FIMS/SPEAR data, then predicted roughly a third of the sky that no UV telescope had observed, using relationships to visible, infrared, and radio data. Hidden test regions were reconstructed to within about 10% of real measurements, and each pixel is labeled measured or predicted with uncertainty estimates.

Why it matters: The post shows how an astrophysicist used Claude Science agents to merge UV surveys and predict missing sky regions, with a validation step that makes the method reusable.

AILangChain built Restock, a sample office-supply agent that runs in Slack on Managed Deep Agents and pays through Stripe's Link wallet. The agent searches products, builds a cart, and pays over the Machine Payments Protocol, with the user approving the purchase in Slack and the payment in Link. The post uses a pens order at $22.18 to show the flow from request to confirmed order.

Why it matters: The post walks through how an agent handles search, budget limits, Slack review, and Link approval, showing where each control sits outside the model.

AICS 329Z: Engineering AI Agents Stanford / Fall 2026 @stanfordnlp Lectures 4 and 5 are now public! @Diyi_Yang's "Tool Use" @Diyi_Yang @michaelryan207 @jyangballin's "Frameworks & Orchestration"

AIThariq, of Anthropic, says the most common failure in AI coding is users working outside their domain who cannot write precise prompts and plans. As a result, they spend many turns iterating imprecisely. The quoted post contrasts this with programmers' advantage in vibe coding.

AIUnsloth Studio binds remote-code approval to a fingerprint of the scanned code, so changed code requires fresh consent before it runs. It also blocks weight files that Hugging Face has flagged for malware in the path the selected loader would deserialize. The article describes these checks as one layer among several, alongside package-content scans and OS sandboxes, and notes that the scanner is not a sandbox and cannot catch every evasion.

AIGoogle Developers Blog introduces AQuA, an ambient quality agent that runs in a customer's Google Cloud project and samples production sessions to find recurring agent failures. In a 32-session travel-concierge sweep, it verified six issues and traced two of them to specific prompt lines, and a replay after the fixes raised full-session passes from 5/32 to 13/32. The post notes that verification and diagnosis are model-based, and that the tool proposes edits without applying them.

Why it matters: The post walks through a concrete production workflow, from sweep and verification to a code-anchored fix and replay, that shows how to diagnose silent agent failures.

AIA Hugging Face blog author used the ML-Intern agent in HuggingChat to build six small models by writing detailed prompts that specify datasets, base models, baselines, smoke tests, and spending limits. The projects include a citrus disease vision-language model, a Huggy character LoRA, a camera-angle LoRA, a doodle-to-object LoRA, a 0.8B prompt rewriter, and a 4-step distilled Agate model, with total compute cost of about USD 103. Each project's prompts and public models are linked from the post.

Why it matters: The author shows how prompt structure, baselines, smoke tests, and budget caps shape an agent-driven training workflow, with per-project costs given.

AIAdaption Labs has launched Invent-a-dataset, which creates post-training datasets from a natural language description alone. A technical report compares the Invent API against frontier proprietary and open-weight LLMs used for data generation. Sara Hooker's post links to the launch page and the report's technical details.

AIPaige Bailey says she used the Gemini app with Google Tasks to hold herself accountable for reading a different New Yorker article every night. She is looking forward to an article about a fraudulent wine dealer.

AICat Wu, who works at Anthropic, says a favorite product manager use case for Claude is asking who used a given feature most last week. She suggests having Claude build an artifact of the top 10 users by usage, then reaching out to schedule 15-minute chats, which she calls the fastest way to get user feedback.