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Agentic AI

146 summarised stories about Agentic AI, each linking back to the original source. Browse all topics →

Thursday, 16 July 2026

Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away."

Ars Technica 5 days ago 2 sources

Linus Torvalds stated that Linux will permit AI-powered coding tools and told critics to fork the project or leave if they oppose their use. Sashiko, an AI code review system, identified 53.6 percent of bugs found by human reviewers in tests but generated false positive reports at an estimated 20 percent rate. This position establishes that Linux kernel development will continue integrating AI tools despite opposition from some contributors.

Building a restaurant telephony AI host with Amazon Bedrock AgentCore and Amazon Nova 2 Sonic

AWS Machine Learning 5 days ago

Amazon published a technical guide for building a restaurant AI voice ordering system using Amazon Bedrock AgentCore, Amazon Nova 2 Sonic, and Amazon Chime SDK Voice Connector that can answer incoming calls and take orders end-to-end. The system deploys as three layers—a telephony layer handling phone-specific concerns, an agent layer running the conversation logic in isolated microVMs, and a backend layer managing menus and orders through the Model Context Protocol. The solution addresses the problem of restaurants missing approximately 150 phone calls per location monthly, with 60 percent of those being customers attempting to place orders or book tables.

AI That Rides Along With Truck Drivers

The Neuron 5 days ago 4 sources

Samsara is deploying AI systems across fleet management operations including dash cams, dispatching, maintenance, and safety workflows for truck drivers. The company's AI agents handle real-world physical operations where decision errors directly impact vehicles, workers, and equipment safety. This represents a shift from office-based AI software to autonomous systems managing logistics and transportation infrastructure.

Towards a Harness That Can Do Anything

TLDR Dev 5 days ago 2 sources

A developer describes Ambiance, a framework for deploying large language models as autonomous agents by designing a harness inspired by Unix/Linux architecture principles. The system uses a virtual filesystem hierarchy, event-driven kernel, and multiple LLM instances (root, pai, librarian) communicating via an event bus to reduce token overhead and improve agent reliability. The framework is available for testing at whitematterlabs.ai and emphasizes leveraging the LLM's existing knowledge of filesystems, text streams, and modular tools rather than teaching it novel interfaces.

Boop Agent

TLDR Dev 5 days ago

Boop is an open-source iMessage-based personal agent template that runs on Claude or ChatGPT subscriptions, using the Claude Agent SDK or Codex runtime without requiring separate API keys. The system connects to 1000+ integrations through Composio (Gmail, Slack, GitHub, etc.), manages tiered memory with daily consolidation, dispatches tasks to specialized sub-agents, and includes a debug dashboard with timeline, automation, and memory visualization. Users can text natural language requests and receive responses with full context, plus optional local browser automation and Apple data access, though the creator explicitly states it is not optimized for cost or security and should be reviewed before personal use.

‘We want to make bookkeeping less painful’: How Visma and its AI portfolio are reshaping accounting

Sifted 5 days ago

Visma, a European accounting software company, operates over 600 AI initiatives across its portfolio of accounting businesses to automate accounting tasks like invoice processing and bank reconciliation. The company's AI applications focus on four value categories: automation saving time, anomaly detection, advisory insights, and agentic workflow automation, with portfolio companies like Chaintrust and Dinero implementing these technologies in production systems. This shift moves accountants from manual data entry work to higher-value advisory roles such as client consultation and financial analysis.

Introducing Muse Spark: Scaling Towards Personal Superintelligence

Meta AI Blog 3 sources

Meta released Muse Spark, a multimodal reasoning model that supports tool-use, visual reasoning, and multi-agent coordination as the first product from its restructured AI efforts. The model requires over an order of magnitude less compute than Meta's previous Llama 4 Maverick model to reach equivalent performance levels. The release includes a private API preview and marks the beginning of Meta's stated scaling roadmap toward what it calls personal superintelligence.

Introducing Muse Image and Muse Video

Meta AI Blog 3 sources

Meta launched Muse Image, an image generation model that uses search tools, code execution, and self-refinement to follow instructions and edit images precisely, alongside a preview of Muse Video for video generation. Muse Image ranks No. 2 on Arena's human-preference Elo rankings for text-to-image and image editing tasks as of July 5, 2026. The models are now available in Meta AI app, meta.ai, and Instagram Stories in the US, with integration into Facebook and broader creator access coming soon.

Introducing Muse Spark 1.1

Meta AI Blog 3 sources

Meta released Muse Spark 1.1, a multimodal reasoning model designed for agentic tasks with improved capabilities in tool use, coding, and computer interaction. The model supports a 1 million token context window and is now available in public preview through the new Meta Model API. Developers can access Muse Spark 1.1 to build agents that handle complex workflows, debugging, and automation across multiple applications without extensive human intervention.

OpenAI’s GPT-5.6 Family, New Ways to Train Robots, Models Invoking Models

The Batch 5 sources

OpenAI released a preview of its GPT-5.6 family of models—including GPT-5.6 Sol, Terra, and Luna—with performance comparable to Claude 5 Mythos, but initial access is restricted to approximately 20 U.S. government-approved organizations. GPT-5.6 Sol achieved 91.9 percent on Terminal-Bench 2.1 for command-line coding and scored 68.3 percent on World-Class Bio tests, a 10-point improvement over the prior generation. The restricted release and safeguards against dangerous biological, chemical, and cybersecurity information mean legitimate developers may face refusals or account reviews when using these cheaper models for security verification work.

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