automation
automation on Beyond Market Intelligence: a running collection of 163 stories we have gathered and hand-picked because they are worth your time. Every post here touches on automation in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around automation, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Monday.com lays off hundreds to focus on AI
Monday.com is strategically streamlining its operations, announcing a 20% workforce reduction—approximately 630 employees—to prioritize its emerging AI Work Platform. This shift signifies a move toward a leaner, more focused structure, reflecting the company’s commitment to AI-driven data management. This realignment underscores a broader industry trend toward AI integration. For deeper insight into the future of AI agents, explore "Presentation: From Copy-Paste to Composition," which details the evolution of agent architectures.
Build an LLM Agent That Can Write and Run Code
Unlock the potential of AI-powered code generation and execution. This hands-on walkthrough guides you through building an LLM agent using the OpenAI Agents SDK and Docker. Learn to empower your workflows by seamlessly integrating code writing and running capabilities. We’ll demonstrate a practical approach to leveraging these tools, offering a future-focused solution for data professionals. For those interested in a deeper dive into LLM runtimes, explore "How To Build Your Own LLM Runtime From Scratch" for a comprehensive understanding of the underlying infrastructure.
Evals are the new PRD, Expedia’s AI chief tells VB Transform 2026
Expedia’s chief AI and data officer, Xavi Amatriain, is redefining product development, asserting that "evals are the new PRD." This shift prioritizes embedding security and design principles directly within evaluation processes, even before coding begins, leveraging AI-assisted code generation. Amatriain advocates for risk-calibrated governance layers, minimizing restrictive guardrails to maintain feedback loops and user agency, particularly emphasizing that users should retain the final click for transactions.
GitLab Brings Carbon Awareness to CI/CD to Measure the Environmental Cost of Software Delivery
GitLab is pioneering a new era of Green DevOps with the introduction of carbon awareness within its CI/CD pipelines. Now, software engineering teams can directly measure the environmental cost associated with their delivery processes, fostering more sustainable development practices. This innovative approach allows for data-driven optimization, minimizing emissions without sacrificing speed or efficiency. Explore how GitLab empowers you to build responsibly – a critical step toward a future-focused approach to software development, as further detailed in our recent article, "GitLab 19.
GitLab 19.2 Puts AI Agents to Work on the Security Backlog
GitLab 19.2 introduces agentic automation to tackle the growing security and review backlog resulting from AI-assisted coding. This release directly addresses the challenge of maintaining code quality as AI tools accelerate development. Key features include Dependency Scanning Auto-Remediation, a streamlined Security Review Flow, and the GitLab Duo CLI, all designed to empower teams. Notably, Custom Flows enter public beta, offering unprecedented flexibility. For those exploring broader AI model management strategies, consider "Yelp Unifies ML Model Training with Training Orchestrator" for additional insights.
Yelp Unifies ML Model Training with Training Orchestrator
Yelp has streamlined its machine learning model training process with the launch of Training Orchestrator, a new internal framework designed to enhance efficiency and consistency. Replacing disparate team scripts, this configuration-driven system utilizes a DAG-based execution model for improved control and scalability. This shift empowers data scientists to focus on model development, not infrastructure management. For further insight into the complexities of AI agent evaluation, explore our recent article on the challenges of ensuring a perfect conversation, as discussed at VB Transform 2026.
Gritt exits stealth with $34 million for robots to build solar plants—then, everything else
Gritt emerges from stealth with $34 million in funding, poised to transform construction through automation. The company’s initial focus: deploying robots to build solar plants, tackling some of the industry's most challenging tasks. This investment underscores a broader vision—to automate demanding processes across a range of construction sites. Gritt’s arrival signals a progressive shift in how we approach infrastructure development. For those interested in exploring the future of AI-powered workflows, see our related article, "How to Run Claude Code Agents for 24+ Hours."
How to Run Claude Code Agents for 24+ Hours
Unlock sustained coding productivity with Claude Code Agents running continuously – even for 24+ hours. This guide explores how to leverage these powerful AI assistants to streamline your engineering workflows and tackle complex projects with unprecedented efficiency. Discover practical techniques for maintaining and optimizing long-running agents, transforming your coding process. For a foundational understanding of setup and configuration, see "A Beginner’s Guide to Setting Up Claude Code for High Performance Agentic Programming" and elevate your agentic programming skills.
A Beginner’s Guide to Setting Up Claude Code for High Performance Agentic Programming
Unlock the full potential of Claude Code for agentic programming with this practical guide. We detail the essential configuration—permissions, hooks, and command habits—that distinguish a functional installation from a robust, production-ready setup designed for sustained agentic workflows. This isn’t theory; it’s a step-by-step walkthrough to optimize performance. For those seeking broader context on the evolving AI landscape, consider our recent discussion, "Am I focusing on the wrong skills as a CS student in the AI era?", to ensure you're building a future-focused skillset.
Am I focusing on the wrong skills as a CS student in the AI era? (Need brutally honest advice) [D]
The AI landscape is rapidly evolving, prompting a critical question for aspiring Computer Scientists: are current skill priorities still relevant? Your concerns about balancing traditional software engineering fundamentals—architecture, system design, and debugging—with the rise of AI are valid. While AI-powered code generation tools are advancing, a deep understanding of underlying principles remains paramount.
Your AI Agent Passed Every Eval. Finance Still Killed It.
A recent evaluation revealed a surprising paradox: an AI agent flawlessly passed every metric in our published harness, demonstrating impressive capabilities. However, the finance department ultimately halted its deployment. While the agent resolved issues effectively, the cost of those resolutions exceeded the expense of human counterparts—a critical factor in practical application. This highlights a crucial consideration for AI adoption, as explored further in "Kimi: Threat or menace?" Demonstrating technical success doesn’t guarantee financial viability.
Loop Engineering with Adaptive PDF Parsing: Start Cheap, Pay for a Heavier Parser Only When the Page Needs It
Loop Engineering’s adaptive PDF parsing offers a transformative approach to document intelligence. Start with a cost-effective parser and only escalate to heavier processing when a page demands it—ensuring you pay only for what you need. This innovative system incorporates an escalation cascade and deterministic checks, proactively flagging parse failures *before* incurring deeper processing costs. Discover how this model delivers efficiency and predictability for enterprise document workflows, as explored in detail in our Enterprise Document Intelligence series.
Newsletter platform Beehiiv now lets subscribers chat with each other, adds AI
Beehiiv is evolving, empowering publishers with enhanced community building and intelligent growth tools. Subscribers can now directly engage with each other through a new chat feature, fostering deeper connections within your audience. Simultaneously, we’re introducing AI Copilot, designed to streamline user growth strategies and provide actionable analytics insights. This represents a significant step toward a future-focused approach to newsletter management. For a broader perspective on AI’s evolving role in productivity, explore our article, "The real problem with AI."
Google’s AI Mode now lets you link and interact with select apps
Google’s AI Mode is evolving beyond simple question answering, now offering the ability to link and interact with select apps to complete tasks. This significant update expands AI Mode’s capabilities, streamlining workflows by connecting your frequently used applications. Discover a more integrated and efficient experience as AI assists with cross-app actions. For deeper insights into the broader landscape of AI agents and productivity tools, explore our related article on "The real problem with AI." This marks a progressive step toward a future-focused data management ecosystem.
Yes, you can now order DoorDash from the command line
DoorDash is expanding its accessibility, launching a limited beta of dd-cli, a command-line tool designed for developers and AI agents. This innovative tool empowers users to search stores, build carts, and place orders directly from the terminal. Representing a significant step toward software optimized for AI workflows, dd-cli opens new possibilities for automation and integration. Interested in the broader trend of AI-powered tools? Explore how Google’s AI Mode is now linking and interacting with select apps, further blurring the lines between human and machine interaction.
Prepare These 5 Assets Before Your AI Agents Take On More Work
Ready to empower your AI agents to handle more work? Success hinges on thoughtful preparation. Before scaling AI adoption, prioritize defining recurring tasks, providing the right contextual data, and establishing clear benchmarks for high-quality output. Critically, determine where human judgment remains essential. These five assets are foundational. As Amazon’s AGI director recently highlighted, reliability—not just capability—is key to enterprise AI deployment; explore deeper insights on this challenge in "Amazon AGI director says AI agent reliability…”.
Don’t Let Claude Grade Its Own Homework
Self-reviewing AI models—like asking Claude to grade its own homework—introduces inherent bias. Our latest post explores a more reliable approach: cross-provider PR review using Codex within GitHub Actions. A second opinion from a different lab consistently delivers more objective and insightful evaluations than internal assessments. This method ensures rigorous quality control and identifies potential blind spots. As Anthropic and Blackstone recently highlighted, successful AI implementation demands more than just powerful models; it requires robust validation—and that starts with impartial review.
A SpaceX vet raised $65M to pull wire harnesses out of the Cold War era
A former SpaceX engineer is tackling a surprisingly persistent challenge: the archaic process of wiring rockets, missiles, and satellites. Having secured $65 million in funding, this innovator is focused on streamlining the bundling of these complex wire harnesses, a task rooted in Cold War-era practices. This addresses a critical inefficiency in aerospace engineering. For context, similar efforts to reimagine established systems are underway elsewhere – as seen with Overtone, a new AI dating service focused on voice interaction.
You can build your AI's memory just by talking. Here's the catch. #AI #aiagents #AImemory
Unlock your AI agent's potential with a surprisingly simple approach: conversational memory. You can build it just by talking. The catch? Scaling this memory effectively reveals underlying architectural complexities that can slow development. Prioritizing a robust context store, as explored in our article "Comprehension at AI Speed," is crucial for maintaining agility and preventing hidden bottlenecks. #AI #aiagents #AImemory