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Agents

AI news about AI agents and systems that act on their own.

39 stories in the last 7 days

Today

2 stories
  1. Worth knowing The Verge

    Uber only fulfilled 4 rides from AI agents last quarter

    This disclosure provides a rare, concrete data point showing that real-world consumer adoption of third-party AI agents for routine tasks like booking rides and ordering food remains extremely low.

    Uber executives revealed during a third-quarter earnings call that third-party AI agents arranged only four rides on its platform last quarter. While AI agents placed slightly more Uber Eats orders—around 500 during the week of Halloween—the volume remains minuscule compared to the 320 million total rides and deliveries.

Yesterday

12 stories
  1. Worth knowing The Verge

    Apple starts giving Siri AI access to third-party apps

    Opening Siri's agentic capabilities to third-party developers is a major step toward making voice-driven AI actions across apps a standard part of the iOS ecosystem.

    Apple is rolling out an iOS developer preview that allows Siri AI to perform actions across third-party apps using personal context, natural language prompts, and on-screen awareness. The update also introduces an "app skills" feature that lets developers combine multiple tasks into a single action without requiring users to mention the app by name.

  2. Worth knowing Hacker News

    How I use AI (Oct 2026)

    It offers a detailed practitioner's perspective on how agentic workflows are replacing manual coding and reshaping daily software engineering.

    A research engineer at Salesforce AI Research shares an annual reflection on how his daily AI usage has evolved, noting that he now spends roughly $3,000 a month on tokens and relies heavily on managing multiple coding agents rather than writing code manually. The essay also examines the mental fatigue of supervising agents, the use of AI for search and tutoring, and the necessity of establishing a personal AI policy.

  3. Worth knowing Hacker News

    Postman silently auto-installs AI plugins and attempts to share all API data

    This incident highlights a new class of security and consent risks where third-party software silently modifies local AI agent configurations and instructions to hijack workflows.

    A developer reported on GitHub that the Postman desktop application silently installed plugins and remote MCP connections into their local Claude Code and Codex AI coding agents without consent. Furthermore, the Postman installer bypassed security boundaries by self-approving its own startup hooks, forcing the coding agents to route general API engineering tasks through Postman.

  4. Worth knowing Google DeepMind

    Agentic cheminformatics with Google Antigravity

    This highlights the growing use of specialized AI agents by major frontier labs to automate complex scientific and drug discovery workflows.

    Google DeepMind discusses how Google Antigravity and specialized Cheminformatics Skills can be used for agentic cheminformatics. The tools are designed to accelerate drug discovery workflows, search chemical compounds, and propose novel rigidified macrocycles.

  5. Worth knowing The Verge

    Apple is all in on AI — its own and everyone else’s

    Apple's earnings demonstrate that a major tech company can financially benefit from consumer AI adoption through hardware sales without matching the massive capital expenditures on AI data centers made by its peers.

    Apple posted record fiscal year revenue and earnings per share, driven by strong fourth-quarter sales for the iPhone and Mac. The company is capitalizing on the AI boom while avoiding the massive infrastructure spending of its competitors, though it warned that rising memory costs could squeeze holiday quarter profit margins.

  6. Worth knowing MIT Technology Review

    How “reverse game theory” could keep AI agents in check

    Mechanism design offers a behavioral approach to AI alignment that does not rely on understanding the complex internal workings of frontier models.

    AI safety researchers and economists are exploring "reverse game theory," or mechanism design, to create incentives that make following rules the most rational choice for AI agents. Proposed strategies include rewarding models for predicting another model's output to prevent sandbagging, as well as assigning models alternating roles as problem "solvers" and "auditors" to catch cheating.

  7. Worth knowing Latent Space

    [AINews] LLMs can read & write neural network weights: "Weight Space Programming" cuts Autoresearch out of the RSI loop

    Directly reading and editing neural network weights with an LLM introduces a novel mechanism for mechanistic interpretability and recursive self-improvement that bypasses traditional training loops.

    Researchers including Alex Zhang demonstrated "Weight Space Programming," showing that large language models can directly read, debug, and generate the raw weights of smaller neural networks without executing training code. The newsletter also covers DeepSeek's open-source "super-agent" harness prototype, results from SemiAnalysis's new GDPx agent benchmark, and research on JEPA representations.

Mon, Nov 2

9 stories
  1. Worth knowing Latent Space

    Building AI for Lawyers - Jacob Lauritzen, CTO of Legora

    It offers a detailed look into the engineering, evaluation, and product architecture required to scale an enterprise AI agent company in a strict, high-stakes domain where customer traces cannot be inspected.

    In an interview on the Latent Space podcast, Legora CTO Jacob Lauritzen discusses building AI agents for the legal industry following the company's $550 million Series E at an $8.8 billion valuation. He details how Legora evaluates models using simulated environments when customer data is strictly confidential, structures its product around core primitives like Tabular Review, and employs both legal engineers and forward-deployed engineers.

  2. Worth knowing Hacker News

    Claude Opus 5.5 Can Draw Permit-Level Architectural Drawings

    This demonstrates how frontier models combining coding, vision, and long-horizon agentic loops are expanding into complex technical domains like CAD and architectural drafting that previously resisted AI automation.

    Architect Stephen Gallagher evaluated 13 AI models on their ability to generate technical architectural drawings directly from rough concept sketches and reference files. He found that Anthropic's Claude Opus 5.5 can produce permit-level construction sets and detailed blueprints by writing over 15,000 lines of Python code to generate vector linework and iteratively inspecting its own visual drafts.

  3. Worth knowing TechCrunch

    Elon Musk throttles Grok Bot limits due to ‘unsustainably high’ costs

    The move highlights the ongoing challenge of unit economics and inference costs for agentic AI products, even within profitable AI divisions.

    SpaceX suddenly lowered weekly usage limits for its agentic AI, Grok Bot, causing many users to see their quotas unexpectedly maxed out over the weekend. CEO Elon Musk confirmed the throttling was intentional because the cost of serving the product had become unsustainably high relative to its revenue.

  4. Worth knowing TechCrunch

    OpenAI is finally merging ChatGPT’s chat and Work tabs

    Consolidating conversational and agentic workspaces reflects an industry trend toward unified AI interfaces, following a similar move by rival Anthropic.

    OpenAI is merging the Chat and Work tabs in the ChatGPT desktop app into a single interface, starting with a rollout to select users. As part of the update, both ChatGPT and the separate Codex section will draw tokens from a unified allowance pool.

  5. Worth knowing MIT Technology Review

    The agentic web is here

    The shift toward autonomous agents browsing and transacting online is reshaping web design, online business models, and cybersecurity as AI becomes a primary user of the internet.

    Autonomous AI agents capable of browsing and interacting with the internet are transforming the human-centric web into an "agentic web." While some companies build specialized connectors and agent-targeted ads to accommodate these tools, others block external agents as models grow increasingly adept at navigating graphical interfaces and acting independently.

  6. Worth knowing SemiAnalysis

    GDPx: Measuring Frontier Model Capabilities Across the Most Valuable Domains

    GDPx addresses the saturation and unrealistic constraints of existing knowledge-work benchmarks by testing AI agents within rich, interactive work environments across economically critical sectors.

    SemiAnalysis has introduced GDPx, a new benchmark developed in collaboration with 14 specialized data partners to evaluate the agentic capabilities of frontier AI models across 11 high-value domains, including chip design, cybersecurity, and finance. Unlike previous static evaluations like OpenAI's GDPval, GDPx utilizes complex, realistic environments and currently sees top models scoring no higher than 12%.

  7. Worth knowing Apple ML Research

    Online Dense Reinforcement Learning with Planning-Grounding Agent for UI Navigation on Live iOS Apps

    Training small, efficient models via online reinforcement learning on live apps shows how Apple could deploy practical, error-recovering UI agents directly on iOS devices.

    Apple ML Research introduces an online reinforcement learning framework that trains AI agents to navigate user interfaces directly on live iOS applications. The method separates the agent into planning and grounding components to avoid the high inference costs of large vision-language models and the brittle execution of smaller fine-tuned models.

Sun, Nov 1

2 stories
  1. Worth knowing Hacker News

    The AI cost of JavaScript frameworks

    As software development shifts toward coding agents, empirical benchmarks help developers choose frameworks and toolings that minimize token costs and build failures rather than relying on anecdotal claims.

    Developer Nolan Lawson created a benchmark to evaluate how efficiently AI coding agents build the same web application across twelve different JavaScript frameworks. Testing with Claude Code revealed significant variance in token usage, cost, and build time, with lightweight setups like Hono+htmx and Astro proving faster and cheaper for agents than Angular or SvelteKit.

Sat, Oct 31

4 stories
  1. Worth knowing Hacker News

    GPT-5.6 Sol can beat Factorio on peaceful mode

    Completing a complex, long-horizon logistics game like Factorio serves as a legible benchmark for how well AI agents handle multi-step planning, system design, and error recovery.

    A developer successfully got the GPT-5.6 Sol model, running in Codex, to autonomously beat the factory-building game Factorio on peaceful mode in 13.5 hours of game time. Interacting via a Python library under human-like game restrictions, the model improved upon GPT-5.5 by using transport belts and ultimately launched a rocket, despite struggling with late-game scaling.

  2. Worth knowing Latent Space

    Agents Prompt People: Using Agents for Long-Horizon Financial Work

    It provides a practical case study of how companies are architecting agent memory, custom harnesses, and deterministic guardrails to deploy AI in high-stakes, regulated industries.

    Aman Singh, lead AI Engineer at AI-native wealth management firm Arca, explains how the company uses AI agents to manage multi-day financial tasks while keeping human advisors in control of final decisions. Arca built its own agent harness, persistent memory system, and deterministic safety guardrails around frontier models like Claude to safely handle client data and propose financial plans.

  3. Worth knowing Wired

    Meta’s Muse Could Upend All Kinds of Businesses. It Hasn’t Yet

    Real-world corporate data provides a reality check on the hype surrounding consumer AI agents, showing a gap between tech companies' adoption claims and actual commercial impact.

    Despite Meta claiming that millions of users are shopping with its agentic AI tool Muse, executives across roughly 50 companies report that actual transactions and subscription cancellations driven by AI agents remain minimal. Even so, businesses like Chipotle and Costco are starting to optimize their websites for AI navigation, while others weigh the security risks and transaction fees associated with agentic commerce.

Fri, Oct 30

4 stories

Thu, Oct 29

4 stories
  1. Worth knowing TechCrunch

    Wabi, the AI agent that builds mini apps, now valued at $1.25B after latest round

    The unicorn valuation for Wabi underscores continued investor enthusiasm for consumer-facing AI agents that move beyond standard chat interfaces to generate custom software on the fly.

    Wabi, an AI startup founded by Replika creator Eugenia Kuyda, has raised $55 million at a $1.25 billion valuation in a funding round led by IVP. The company recently pivoted from a prompt-based app builder to an AI messenger and personal agent that generates custom mini-apps for everyday tasks.

  2. Worth knowing TechCrunch

    Deepgram acquires Pipecat-maker Daily to bolster its voice AI infrastructure

    This acquisition consolidates key voice AI model and orchestration infrastructure while ensuring a widely used open-source voice agent framework remains vendor-neutral.

    Deepgram is acquiring Daily, the company behind the open-source voice and video AI framework Pipecat, for an undisclosed amount. The two companies pledged to keep Pipecat open-source and vendor-neutral while also launching the Real-Time Context Standard (RCS), an open protocol for voice agents.

  3. Worth knowing TechCrunch

    Amazon updates Alexa to help you manage shopping lists and subscriptions and update delivery instructions

    This incremental update shows how major retail platforms are embedding agentic AI into everyday consumer tasks to handle complex account management and e-commerce logistics via voice.

    Amazon has added over 100 new shopping features to its Alexa assistant, enabling users to manage subscriptions, edit shopping lists, update delivery instructions, and resolve billing issues. The company also reported an eightfold increase in the use of its agentic features since the beginning of the year, with over 400 million consumers using Alexa to shop in the past 12 months.

  4. Worth knowing Hacker News

    Claude Code regularly sends each background agent’s transcript to its model

    Developers using Claude Code with background agents can use this workaround to prevent hidden background requests from draining their API budgets or subscription rate limits.

    An investigation by Flamerix AI found that Claude Code sends the full transcript of each background agent to its model every 30 seconds to generate a brief status line, consuming 15% to 20% of total token spend. Because there is no official setting to disable this default behavior, the authors released a Bun preload script that intercepts and disables the summary timer.

Wed, Oct 28

2 stories
  1. Worth knowing Latent Space

    Why Agents Love Supabase

    As AI coding agents increasingly build and deploy software autonomously, developer infrastructure is being redesigned around low-friction, declarative workflows that models can easily inspect and operate.

    Latent Space interviews Supabase founders Paul Copplestone and Ant Wilson on how the platform is adapting its database and backend infrastructure for AI agents. The discussion covers recent announcements including Docker-free local development, declarative Git-based schemas, co-located compute, and the acquisition of Turso to scale for agent-generated applications.