The hottest Automation Substack posts right now

And their main takeaways
Category
Top Technology Topics

Why Claude Can't Run Your Business (Yet)

Teaching computers how to talk • 99 implied HN points • 30 Jun 25
🕹 Technology Automation
  1. Claude, the AI, was tested to see if it could manage a vending machine successfully. It had to figure out pricing and deal with customer feedback.
  2. The experiment showed that Claude struggled with basic business decisions, like buying items it couldn't sell for a profit. It also made strange comments that confused the human employees.
  3. Overall, the project highlighted how current AI technology, like Claude, isn't ready to run a business effectively yet, mainly because it can't learn from its mistakes.

AI Agents & Marketing: It's Weird.

The Digital Anthropologist • 19 implied HN points • 24 Jun 24
🕹 Technology Automation
  1. In the future, marketers might need to create separate campaigns for humans and AI agents, requiring unique approaches for each audience.
  2. Marketing teams are facing the challenge of designing campaigns that cater to both human and AI customers, necessitating the development of dual marketing strategies and content.
  3. The integration of AI agents in marketing campaigns has led to increased costs and complexities, requiring specialized roles, technologies, and strategies to navigate successfully.

Round-Up of the Yocto Project Summit 2023.11

burkhardstubert • 59 implied HN points • 18 Mar 24
🕹 Technology Automation
  1. Implementing a fallback mechanism during system updates is crucial. If an update fails, it can prevent endless reboots by reverting to a stable version.
  2. Keeping your Yocto project layers simple can reduce maintenance and complexity. Using minimal layers can help avoid outdated code and improve build efficiency.
  3. Setting up a CI pipeline for Yocto builds can simplify the development process. It provides ready-to-use images for developers without requiring deep knowledge of Yocto.

LLM Links, 1/17

In My Tribe • 212 implied HN points • 17 Jan 25
🕹 Technology Automation
  1. Intelligence can help us break down regulatory barriers and improve cooperation. A higher baseline of intelligence might push us to recognize and fix our bad decisions more easily.
  2. The adoption of AI will be slow because organizations and systems take time to change. Even with advanced AI, many people might not notice its presence right away.
  3. Bill Gates believes AI will take over routine tasks, leaving creative work for humans. However, there’s a chance that AI could also become creative, challenging the idea that humans are solely responsible for creativity.

The Browser Wars 2025: ChatGPT Atlas vs. Perplexity Comet vs. Chrome with Gemini — The Complete Analysis

The Product Channel By Sid Saladi • 23 implied HN points • 23 Nov 25
🕹 Technology Automation
  1. There are three main AI-powered browsers available now: ChatGPT Atlas, Perplexity Comet, and Chrome with Gemini. Each one is built for different needs, like automation, research, or convenience.
  2. ChatGPT Atlas is great for productivity and automating tasks, while Perplexity Comet focuses on research and providing accurate information with citations. Chrome with Gemini is perfect for those who want an easy upgrade without switching from Chrome.
  3. The best choice depends on your needs. If you want powerful automation, go with Atlas; for research, choose Comet; and if you’re already using Chrome and want added features, then Gemini is your best bet.
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Collaborative Markdown with Lix Change Control

Opral (lix & inlang) • 7 HN points • 07 Aug 24
🕹 Technology Automation
  1. Using Lix Change Control for Markdown makes collaborative writing better. It helps everyone work together smoothly and keeps track of changes easily.
  2. With Lix, you can make changes, submit them for review, and see who changed what. This makes it easy to approve or reject edits.
  3. Automation features let you set rules for content quality and manage updates or translations. This saves time and ensures the final product is accurate.

How I Transcribed 362 Episodes of My Favorite Podcast Using Codex CLI and exe.dev

Juan David’s Newsletter • 6 implied HN points • 26 Jan 26
🎙 Podcasts Automation
  1. A reliable four-step pipeline handled hundreds of episodes unattended: raw ASR → deterministic cleanup → editorial LLM pass → publish/sync, running Codex CLI on a remote VM so the whole job could finish without babysitting.
  2. A strict style guide, correction maps, and a locked editorial prompt made the LLM behave like a conservative editor, fixing ASR phonetic errors, names, punctuation, and obvious typos without adding facts or changing meaning.
  3. The results were published with per-episode pages, audio players, navigation, and SEO, and an automated watcher now transcribes new episodes automatically, making the archive searchable for humans and LLMs and enabling future personalized learning tools.

Junior Extinction

davidj.substack • 71 implied HN points • 29 Jul 25
🕹 Technology Automation
  1. Junior engineering jobs are becoming less common, especially in large tech companies. However, they aren't completely disappearing, with some positions still available.
  2. The new roles require different skills, like working well with AI and clear communication, rather than just coding skills. This is changing what companies look for in new hires.
  3. AI is speeding up work processes significantly. Tasks that took humans a long time can now be done much faster with AI, allowing for quicker iterations and product releases.

The Sequence Knowledge #675: Learning to Evaluate Multi-Agent AIs

TheSequence • 91 implied HN points • 01 Jul 25
🕹 Technology Automation
  1. Multi-agent benchmarks are important now because they test how AI agents can work together, unlike old methods that focused on just one agent at a time.
  2. These new benchmarks help us see how well AI can handle tasks that involve teamwork and communication in changing environments.
  3. As AI gets better, understanding how these systems interact will be key to unlocking smarter, more capable AI behavior.

This is Why We Can't Have Nice Things

The Weasel Speaks • 157 implied HN points • 27 May 23
🕹 Technology Automation
  1. Agile has three main views in the industry: it doesn't work, it's taking away jobs, it accelerates value to customers.
  2. Technological disruptions often make people feel like their jobs are in jeopardy.
  3. AI stirs opinions: it's criticized for not working, it's accused of taking jobs, yet it can accelerate learning and revolutionize work.

The age of the human bottleneck is ending. The age of human intent is beginning

Brick by Brick • 18 implied HN points • 27 Nov 25
🕹 Technology Automation
  1. AI will replace the old human-centric development pipeline with compact "Engine Room" teams where autonomous agents build, test, and deploy most of the product.
  2. This makes companies far more productive and lean — much higher revenue per employee, much faster shipping cycles, and many startups intentionally capping headcount because they simply don’t need more people.
  3. Human roles will shift from writing code to defining strategic intent, tuning and auditing AI systems, and handling judgment, ethics, and risk.

Hello AI Agents: Goodbye UI Design, RIP Accessibility

Jakob Nielsen on UX • 180 implied HN points • 21 Feb 25
🕹 Technology Automation
  1. AI agents will change how we interact with the internet by doing tasks for us, making traditional user interfaces less important. Instead of users browsing websites, agents will handle everything, like shopping or booking trips.
  2. Accessibility might become less relevant as AI agents can adapt content for the individual needs of users with disabilities. These agents will tailor their actions and communication according to what each user prefers or requires.
  3. As AI agents become more capable, the way content is designed will shift. Websites may need to focus more on how agents can access and analyze information rather than on making things visually appealing for human users.

Will AI lead to more "managed" security services?

Frankly Speaking • 101 implied HN points • 29 May 25
🕹 Technology Automation
  1. AI is set to change the way security services operate by taking over repetitive tasks. This means teams can focus on more important work instead of getting bogged down by routine maintenance.
  2. With AI managing security tasks, new types of services will emerge that work better and require fewer people. This helps businesses save costs and improves consistency in security measures.
  3. Instead of fearing job loss, security professionals should see AI as a tool that helps them do their jobs better. AI can handle tedious tasks, allowing security teams to focus on critical areas like designing better security systems.

Future of Work in 2024 – Latest Scores

Workforce Futurist by Andy Spence • 244 implied HN points • 04 Dec 24
💼 Business Automation
  1. In 2024, there were a lot of layoffs, mainly justified by technology and AI, which made the job market more competitive for workers.
  2. Freelancers became more common as many companies turned to them instead of hiring full-time staff, which made rates for their services drop.
  3. The debate about working from home shifted back to office work as companies started requiring employees to return to the office, which changed how people view remote work.

Automation in Movie Theaters Gives Me the Creeps

Textual Variations • 198 implied HN points • 21 Jan 25
🎭️ Culture Automation
  1. Automation in movie theaters is increasing, leading to fewer staff and a less engaging experience for viewers. People feel uneasy seeing machines replace human jobs and the emptiness of the theaters.
  2. The closing of a popular David Lynch Facebook page highlights issues with automated customer service. It shows how difficult it can be to get assistance from large companies like Meta when they rely heavily on machines.
  3. The alternate Pizza Hut version of 'Demolition Man' demonstrates how movie marketing has evolved over time. It's a fun twist that changes the film's context for different audiences, reflecting how product placement has shaped cinema.

The last generation of programmers

Brick by Brick • 63 implied HN points • 04 Aug 25
🕹 Technology Automation
  1. AI is changing programming in a big way. Soon, machines might do most of the coding, leaving fewer jobs for human programmers.
  2. Just like how cars created new jobs when horses disappeared, AI will lead to new roles focused on guiding and managing these technologies.
  3. In the future, software creation might be easier for everyone. People will share ideas, and AI will turn those ideas into working software quickly.

AI and productivity: Year-in-review with Microsoft, Google, and GitHub researchers

Engineering Enablement • 13 implied HN points • 17 Dec 25
🕹 Technology Automation
  1. Lines of code is a poor measure of AI’s value — more output doesn’t equal more impact. Use broader measures like satisfaction, performance, collaboration, and efficiency to judge whether AI actually helps.
  2. AI is changing the developer role from code producer to director and validator of AI-assisted work, so hiring, career paths, and training must prioritize AI fluency, systems thinking, and judgment. Juniors might learn end-to-end problem solving faster, but only if teams preserve mentorship and opportunities to collaborate.
  3. The real wins come from enablement and focusing AI on real bottlenecks or tedious work, not from constantly switching tools or models. Also, don’t trust simple headlines — dig into context, and design tools to boost creativity and meaningful automation rather than just raw speed.

Running dbt-core on Github Actions: a comprehensive guide

The Orchestra Data Leadership Newsletter • 39 implied HN points • 18 Apr 24
🕹 Technology Automation
  1. Advantages of running dbt-core on GitHub Actions include easy workflow definition in Git, immediate access to latest code, and no need to provision instances for GitHub hosted runners.
  2. Disadvantages of running dbt-core on GitHub Actions include being limited by GitHub's workers, 'fire and forget' implementation, and overhead when connecting to external services.
  3. GitHub Actions workflows can be triggered from external sources like orchestrators using the repository dispatch event or the workflow_dispatch event, providing flexibility in integrating GitHub's CI/CD capabilities into larger automation strategies.

Workflows as Abstractions to Capabilities

The API Changelog • 4 implied HN points • 30 Jan 26
🕹 Technology Automation
  1. Baking API integrations into code creates maintenance hell because the more services you add, the higher the chance a change will break something and make troubleshooting hard.
  2. Map integrations to business capabilities (like “sale close”) instead of raw API operations so it’s easier to diagnose failures, reduce complexity, and swap vendors without breaking business flows.
  3. Implement those capabilities as visual workflows with low-code/no-code tools so teams can see, manage, assign, and lifecycle-manage integrations, making fixes and outsourcing simpler.

Revolutionizing Data Science: The Latest Trends in Automation, Experimentation, and Language Model Evaluation

Gradient Flow • 259 implied HN points • 26 Jan 23
🕹 Technology Automation
  1. The need for tools to help developers pick models that fit their needs and understand model limitations as general-purpose models are widely used.
  2. Data science teams are tackling automation and early examples targets aspects of projects like modeling and coding assistance, but further advancements are needed.
  3. There's a shortage of research and tools for experimentation and optimization in data science, creating opportunities for entrepreneurs to deliver innovative solutions.

The Tech Buffet #16: Quickly Evaluate your RAG Without Manually Labeling Test Data

The Tech Buffet • 99 implied HN points • 18 Dec 23
🕹 Technology Automation
  1. You can automate the testing of Retrieval Augment Generation (RAG) systems without needing to label data yourself. This makes it faster and easier to evaluate their performance.
  2. Generating synthetic datasets with questions and answers allows you to test how well your RAG performs. This method helps you understand the effectiveness of your application and provides useful insights.
  3. Using various metrics is key to evaluating your RAG accurately. This way, you assess different aspects of performance, ensuring you get a well-rounded view of how your system is doing.

Patterns and Predictions for 2024

The Intersection • 98 implied HN points • 20 Dec 23
🕹 Technology Automation
  1. Creativity is now decentralized, allowing anyone with the will and tenacity to create, thanks to technology advancement.
  2. Platforms still hold power over creators, and AI will continue to deindustrialize various types of work, transforming the landscape.
  3. The future holds doing more with less, the 10-80-10 rule of AI in content creation, and an interface shift in areas like search, commerce, and automotive.

✨ The impact of AI and jobs: A Quick Q&A with … Daniel Rock of the Wharton School

Faster, Please! • 274 implied HN points • 16 Oct 24
🕹 Technology Automation
  1. AI could become a general-purpose technology if it applies widely across many industries and leads to real changes in how we work. We need to see if it really changes innovation in significant ways.
  2. Many jobs could be affected by AI tools, with some reports suggesting that up to 46% of jobs could see more than half their tasks impacted. This shows how powerful AI might be in the workplace.
  3. It's likely that using AI will change not just individual tasks but also how organizations operate and make decisions. This means workplaces will need to adjust to new ways of working.

The Next Wave of AI: Building Your Own Digital Workforce

Workforce Futurist by Andy Spence • 244 implied HN points • 13 Nov 24
🕹 Technology Automation
  1. Agent Engineering lets anyone create their own AI assistants. You don't need to be a tech expert to design these digital helpers for personal or work tasks.
  2. AI agents can help with brainstorming and managing projects. They can suggest ideas and organize meetings, making team collaboration smoother.
  3. Building and using these AI agents can boost productivity and learning. You can also practice communication skills in a safe space with them.

The fundamentals of agent-driven software workflows

Dev Interrupted • 74 implied HN points • 08 Jul 25
🕹 Technology Automation
  1. Agent-driven workflows are key for AI in software, moving beyond just coding tools to smarter systems that can manage the entire process.
  2. To benefit from AI tools, companies need to improve their systems and processes, not just focus on what the tools can do on their own.
  3. Successful AI strategies will rely on creating connected, efficient workflows rather than isolated software solutions.

Labour in the middle layer

imperfect offerings • 139 implied HN points • 20 Jul 23
🕹 Technology Automation
  1. Human work plays a crucial role in maintaining the illusion of intelligence in AI models by performing tasks like reviewing outputs and assigning ratings.
  2. The human labor in the middle layer of AI development is extensive, complex, and ongoing, despite being often overlooked by the industry.
  3. Students and graduates are increasingly becoming involved in platform data work, which can impact their job satisfaction and well-being, raising questions about the future of labor in the AI industry.

Areas of interest (June 2023)

Peter's Newsletter • 137 implied HN points • 20 Jun 23
🕹 Technology Automation
  1. Design-to-code automation is being explored, possibly streamlining the process of translating designs into working code.
  2. Developer playgrounds, like Jupyter notebooks, are becoming more important for creative software development and experimentation.
  3. Treating agents as users opens up new possibilities in app interactions, such as assigning work or leveraging business knowledge in various contexts.

Understanding AI-driven job losses

philsiarri • 89 implied HN points • 05 Jun 25
💼 Business Automation
  1. AI is changing the job market, and many jobs could be replaced by machines. This is making people worried about their future work.
  2. Certain industries like manufacturing, finance, and retail are seeing big job cuts because of AI. Fast-food places and banks are automating roles, making it hard for some workers.
  3. While many jobs may be lost, there are new opportunities too. Learning to work with AI tools and adapting to new roles can help people stay employed.

Putting AI To Work

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 11 Apr 24
🕹 Technology Automation
  1. AI tools can help businesses automate tasks and improve efficiency without needing coding skills. This makes it easier for companies to integrate AI into their workflows.
  2. It's important to have a single platform that can manage different AI models together. This way, organizations can create more effective applications by combining the strengths of various models.
  3. Moving AI projects from ideas to reality requires careful planning and testing. Organizations need to ensure models are well-trained before using them in real-world applications.

The Thrill of Deprecating Dashboards

Sarah's Newsletter • 239 implied HN points • 29 Nov 22
🕹 Technology Automation
  1. Having an excessive number of dashboards can lead to inefficiency and confusion within an organization. It's important to prioritize strategic organization over creating new dashboards indiscriminately.
  2. Developing an automated dashboard deprecation strategy can help save time and maintain a clean BI instance. By automating the process, organizations can efficiently manage and delete unused visuals.
  3. Implementing a proactive maintenance plan, such as using a data catalog or automated tools, can help keep BI instances organized and optimal for data insights. Regular cleaning and organization are key to ensuring the effectiveness of analytics strategies.

Stop managing AI. The case for proactive agents.

Kathy PM • 18 implied HN points • 24 Nov 25
🕹 Technology Automation
  1. Developers want tools that handle tasks proactively, instead of just reacting to commands. They don’t want to waste time managing tools; they want to focus on building.
  2. For AI tools to be useful, they need to understand the context of a project and work seamlessly with developers. This means recognizing patterns and anticipating needs before being asked.
  3. The future of coding tools should feel collaborative. We aim for AI that can act like a helpful teammate, reducing mental load and helping developers concentrate on creative problem-solving.

Agents

davidj.substack • 71 implied HN points • 01 Jul 25
🕹 Technology Automation
  1. Agents can simplify processes by automating tasks that used to require complex software. Instead of building software for specific needs, you can create a simple agent that does the job quickly.
  2. Developing an agent often takes much less time than traditional software development. With the right tools, you can set up a functioning agent in just half an hour.
  3. Businesses might shift focus from selling software to providing services that include agents. Customers will prefer solutions that are easy to use, so products with complicated setups may struggle to succeed.

For AI at work, start with something small

Technically • 16 implied HN points • 02 Dec 25
🕹 Technology Automation
  1. It's best to start using AI by automating small, annoying tasks instead of trying to automate everything at once. Focusing on one specific issue can lead to better results.
  2. The 'messy middle' is where AI works best. It's about tasks that are time-consuming but not critical, like summarizing reports or sorting feedback.
  3. AI can help improve parts of your job, but don't expect it to replace everything overnight. It can assist in making repetitive tasks easier and faster.

🤖 AI and the economy: scenarios for a world with artificial general intelligence

Faster, Please! • 456 implied HN points • 18 Mar 24
🕹 Technology Automation
  1. Artificial General Intelligence is a concept that doesn't exist yet and may never be achieved, but some experts believe it's coming soon.
  2. AI is viewed as a tool to enhance human capabilities and create new opportunities rather than a threat to job security.
  3. The impact of AI on the economy will depend on whether there is a limit to the complexity of tasks humans can perform.

The 20 Comet AI Browser Workflows That Will 10x Your Productivity (Copy/Paste Inside)

The Product Channel By Sid Saladi • 20 implied HN points • 16 Nov 25
🕹 Technology Automation
  1. Using AI tools can save you a lot of time on research tasks. Instead of spending hours gathering information, the AI can do it for you and help you focus on the important stuff.
  2. Automating tasks like competitive analysis and trend monitoring can improve the quality of your work. You can get real-time data and insights without getting bogged down by manual processes.
  3. It's important to adapt your workflow to new technologies. When you let AI handle the busywork, you can dedicate more time to creative and strategic thinking.

Microsoft Sentinel SOC 101: Detecting and Mitigating Spear Phishing with Microsoft Sentinel

Rod’s Blog • 59 implied HN points • 12 Feb 24
🕹 Technology Automation
  1. Spear phishing is a serious cyber-attack that targets specific individuals or organizations. Microsoft Sentinel's tools can help detect and prevent these types of threats.
  2. Microsoft Sentinel allows for the creation of custom analytics rules based on KQL queries to identify potential spear phishing activities. This helps in early detection of threats.
  3. Automation and playbooks in Microsoft Sentinel enable immediate responses like blocking URLs or initiating password resets upon detecting a spear phishing attempt.

The Smartest Bear vs the Dumbest Human: The Implications of AI's Growing Problem-Solving Abilities

The Future of Life • 19 implied HN points • 04 Jun 24
🕹 Technology Automation
  1. AI is getting really good at problem-solving, even beating humans at some tasks, like solving CAPTCHAs. This shows that AI can reason better than many humans, especially in certain situations.
  2. The Turing test isn't just one hurdle to jump over; it's a series of challenges that measure how closely AI can act like a human. As AI improves, it passes more of these challenges, showing its capabilities.
  3. While current AI isn't fully intelligent like a human, it's almost ready to solve a lot of problems. The only big limitation is how much computing power is available for training these AI systems.

HOISTED FROM COMMENTS: RAFAEL KAUFMANN: Carving Nature at the Joints: Faithful Representation, the Platonic Dream, & the Unreasonable Near-Success of GPT LLM MAMLMs

Brad DeLong's Grasping Reality • 69 implied HN points • 25 Jun 25
🕹 Technology Automation
  1. Machines, like large language models, can imitate human language because they find patterns hidden in how we express ourselves. They simplify the chaos of our words into something easier to understand.
  2. Even though these models are good at predicting responses, they struggle with truly understanding the world. They can replicate language well, but grasping the deeper meaning remains a challenge.
  3. The hope is that with better training and understanding causal relationships, these models could evolve to not only imitate but truly comprehend the world around them.

What happens if mass unemployment never arrives

State of the Future • 126 implied HN points • 05 Mar 25
💼 Business Automation
  1. Mass unemployment might not happen, but instead, we may see job roles that are less meaningful or filled with busywork. This could lead to people being employed without feeling fulfilled.
  2. The speed of AI's impact on jobs is much faster than previous technologies. Workers may struggle to adapt since the transitions that used to take generations are now happening in just a few years.
  3. People might still need jobs for their sense of identity and purpose, even if those jobs are not necessary for the economy. Finding meaning in work could become a bigger issue than just having a job or not.

Last Words on AI

God's Spies by Thomas Neuburger • 80 implied HN points • 10 Jun 25
🕹 Technology Automation
  1. AI can't solve new problems unless they've been solved by humans before. It relies on previous data and patterns to operate.
  2. AI is largely a tool driven by greed, impacting our environment negatively. Its energy demands could worsen the climate crisis.
  3. Current AI models are not genuinely intelligent; they mimic patterns they've learned without real reasoning ability. This highlights that we are far from achieving true artificial general intelligence.