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TodayOct 8Thu48 items
  1. Tessl Blog42

    Tessl Says Merge Rate Shows Whether AI Adoption Is Real

    Tessl argues that an AI-native organization collapses the handoff between people who own outcomes and the work itself, so product managers and designers can execute changes through agents. It says PR count and token spend are insufficient measures, and that merge rate better shows whether the new workflow is working. The article also says the boundary should follow decision authority, with engineers still owning architecture and data models.

  2. Tessl Blog52

    Simon Martinelli Explains Using System Use Cases as Specs for AI Code Generation

    The author argues that system use cases, with actors, preconditions, scenarios, and acceptance criteria, work better than user stories as the input for AI code generation in enterprise business applications. He describes a process that skips the plan-and-task phase, reverse-engineers legacy systems into use cases and entity models for modernization, and recommends self-contained system verticals and risk-based review.

  8. AWS Machine Learning Blog40

    Cornerstone cuts database diagnosis time 78% with Orion AI on Amazon Bedrock

    Cornerstone OnDemand built Orion AI, a multi-agent system using Amazon Bedrock and the open source Strands Agents framework, that cut database diagnosis from 45 minutes to 10, a 78% reduction. The system also reduced manual lifecycle steps from more than 10 to a single interaction and filtered redundant alerts by a median of 65%. A three-person team delivered it in six months.

  9. 雷峰网 Leiphone54

    Simplexity Robotics uses robots to tend CNC lathes at 0.5 mm tolerance

    At IROS 2026, Simplexity Robotics presented a robot that autonomously tends two CNC machines, grasping workpieces, loading them into chucks, and placing finished parts, with 0.5 mm clearance. The system was trained on only 600 real robot trajectories, using the SimpleWAM world action model, DRAM recurrent memory, and DPE candidate action scoring. The talk was reported as an edited transcript from the conference presentation.

  10. MarkTechPost48

    Laya Open-Source Decision Engine Tutorial: Zero-Shot Decisions and Calibration

    Laya is a 421-million-parameter non-autoregressive decision engine from Convai Innovations that returns calibrated option probabilities in a single forward pass with zero output tokens. This tutorial tests its zero-shot accuracy, probability calibration, temperature fitting, and abstention gating on the CLINC150 banking intent dataset.

  12. Rowan Cheung23

    GrokBot gains native X monitoring with four copy-paste routines

    Rowan Cheung shares four GrokBot routines enabled by its new native X monitoring, covering AI workflow discovery, brand mention tracking, prospect detection, and contact follow-ups. Each routine comes with a copy-paste prompt specifying schedules, search criteria, output formats, and Slack delivery. The routines are tailored for newsletter and marketing use cases, such as monitoring The Rundown's mentions and finding readers searching for AI newsletters.

  13. ClaudeDevs36

    How to build automations with Claude Managed Agents: https://claude.dev/blog/building-effective-agent-automations/ Deploy an agent that reads Slack/GitHub on a schedule (with credentials and memory) and posts updates. You can set it up with a Claude Code command and use the new API credits included in Max and Team.

    How to build automations with Claude Managed Agents: https://claude.dev/blog/building-effective-agent-automations/ Deploy an agent that reads Slack/GitHub on a schedule (with credentials and memory) and posts updates. You can set it up with a Claude Code command and use the new API credits included in Max and Team.

  14. Replit4

    You’ve analyzed the survey results and your findings report is ready. Now continue in the same Replit conversation: – “Draft an action plan.” – “Create a presentation.” – “Prepare a research brief.” Choose the next step using findings you’ve already explored as the starting point.

    You’ve analyzed the survey results and your findings report is ready. Now continue in the same Replit conversation: – “Draft an action plan.” – “Create a presentation.” – “Prepare a research brief.” Choose the next step using findings you’ve already explored as the starting point.

  15. Databricks Blog38

    Lakebase Branches Give Parallel Coding Agents Isolated Databases

    Databricks introduces database branching in Lakebase Postgres, letting each coding agent work in its own isolated database branch created in under a second regardless of size. Branches use copy-on-write storage, consuming extra space only as they diverge, and scale to zero when idle so unused branches incur no compute cost. Schema changes are tracked in code and promoted to the parent branch through migrations rather than merged back, and ephemeral branches are created per pull request for testing.

  17. NVIDIA Newsroom46

    Developers Use Frontier AI Agents to Build NVIDIA Omniverse Simulations

    NVIDIA developers are pairing frontier AI models, including GPT-6 Astra and Claude Fable 5, with Omniverse libraries to turn simulation ideas into working applications. Examples include a humanoid warehouse simulator, an autonomous-driving testing workflow, and sensor-matching digital twins. The projects are guided through natural-language instructions and reviewed by developers.

  18. NVIDIA Blog49

    How Developers Use Frontier AI Agents to Build Omniverse Simulations

    Developers are pairing frontier AI models with NVIDIA Omniverse libraries to turn simulation ideas into working applications, from humanoid warehouse simulators to autonomous-driving test environments. In the examples, developers direct AI agents through natural-language instructions and review results, while Omniverse provides GPU-accelerated physics, rendering and sensor simulation. One experiment reported a simulated Unitree G1 humanoid clearing a hurdle in 64 of 100 trials.

  20. Databricks Blog29

    Biomedical Imaging's Real Bottleneck Is Data Access, Not AI Models

    Hospitals, academic centers, medtech firms, and pharma companies all face the same obstacle: imaging data is locked in clinical systems and hard to share. The EXAM study across 20 institutions showed federated learning, which shares model weights rather than patient data, improved AUC by 16% on average. Collaboration remains difficult due to scanner and protocol heterogeneity, privacy governance, and the lack of a common data substrate.

  21. NVIDIA Technical Blog26

    How to create SimReady robotics assets from CAD with frontier AI models

    NVIDIA's Omniverse libraries, guided by SimReady Foundation specifications and agentic NVIDIA skills, provide a structured workflow for converting CAD assets to OpenUSD for robotics simulation. The workflow covers configuring and validating materials, collision geometry, joints, and other physics properties before testing robot behavior.

  24. wh22

    Today, we are sharing more about our post-training infrastructure @ProximalHQ We build on top of @modal GPUs and Kubernetes to support our experiments. Had a ton of fun working on this, and we tried to make the blog as educational as possible! More cool details below :)

    Today, we are sharing more about our post-training infrastructure @ProximalHQ We build on top of @modal GPUs and Kubernetes to support our experiments. Had a ton of fun working on this, and we tried to make the blog as educational as possible! More cool details below :)

  26. Comfy Blog34

    How I Generated Live Video with MiniMax H3 on a Single GPU

    A 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.

  27. Tessl Blog29

    One Brain Means Owning Your Organizational Memory

    Leapfrog, 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.

  28. Tessl Blog52

    Cisco engineer argues agent skills need a context pipeline with evals

    John 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.

  30. Google Cloud Tech16

    1️⃣ Turn your best employee’s workflow into the team default. Package proven procedures once as Skills and share them in one central registry for your whole team to access, raising accuracy and cutting token spend.

    1️⃣ Turn your best employee’s workflow into the team default. Package proven procedures once as Skills and share them in one central registry for your whole team to access, raising accuracy and cutting token spend.

  31. Artificial Ignorance52

    Charlie Guo maps the core primitives that make AI agents work over time

    The 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.

  32. AWS Machine Learning Blog27

    Share SageMaker HyperPod GPU clusters across teams with isolation and fair scheduling

    AWS 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.

  35. Hamel Husain17

    Q: Can I use the same model for both the main task and evaluation? A: Usually, yes. Test whether the judge agrees with human labels on a held-out test set. https://hamel.dev/blog/posts/evals-faq/can-i-use-the-same-model-for-both-the-main-task-and-evaluation.html

    Q: Can I use the same model for both the main task and evaluation? A: Usually, yes. Test whether the judge agrees with human labels on a held-out test set. https://hamel.dev/blog/posts/evals-faq/can-i-use-the-same-model-for-both-the-main-task-and-evaluation.html

  36. 卡尔的AI沃茨16

    Author rewrites GoodCase case clustering and storage allocation using Opus 5.5

    The 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.

  37. 卡尔的AI沃茨14

    Claude Opus 5.5 gains traction for weekly product videos and GoodCase expansion

    The 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.

  39. Allie K. Miller14

    Perhaps my most unhinged workflow: I was talking nonstop to Instinct about everything on my list - drafting, prioritizing, strategizing. Before I went to bed, I had Instinct create a massive prompt for Codex to execute the entire 19-item list and then email that prompt to me. Then I had Instinct write the prompt I gave to Codex to search my email and find the note Instinct left for it. 1/3

    Perhaps my most unhinged workflow: I was talking nonstop to Instinct about everything on my list - drafting, prioritizing, strategizing. Before I went to bed, I had Instinct create a massive prompt for Codex to execute the entire 19-item list and then email that prompt to me. Then I had Instinct write the prompt I gave to Codex to search my email and find the note Instinct left for it. 1/3

  40. Databricks Blog35

    How to build governed enterprise apps on Databricks with Replit and Lakebase

    Replit 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.