The hottest Automation Substack posts right now

And their main takeaways
Category
Top Technology Topics

Salesforce CEO Marc Benioff Has Thoughts on AI Agents, Automation, And The Future of Your Job

Big Technology • 4753 implied HN points • 27 Nov 24
đź•ą Technology Automation
  1. Salesforce CEO Marc Benioff believes AI agents will work for companies rather than individuals. This means businesses can use these agents to handle customer service and other tasks, making things more efficient.
  2. Benioff sees AI as a way to boost productivity, not just replace jobs. By using technology, companies can enhance the skills of their workers and make them more effective without necessarily hiring more people.
  3. The future of business software could change a lot. Instead of traditional programs, companies might start using chatbots to manage data and interact with customers, creating a new kind of relationship with technology.

When Will AI Take Your Job?

Uncharted Territories • 2908 implied HN points • 21 Mar 23
đź•ą Technology Automation
  1. Artificial intelligence is advancing rapidly and may lead to job automation, especially in intellectual and unregulated fields.
  2. Industries that can withstand automation vary based on factors like demand saturation, regulations, and non-informational work components.
  3. New businesses are easier to start but may not create a large number of jobs, leading to a future with more billionaire founders and few employed individuals.

AI Links, 12/21/2025

In My Tribe • 197 implied HN points • 21 Dec 25
đź•ą Technology Automation
  1. AI can run many human-like interviews and assessments cheaply and reliably, letting organizations collect richer open-ended responses at scale.
  2. Even when AI succeeds technically, the firms that build models might not capture the value—competition can erode profits and create financial risks even as enterprise usage and integration grow.
  3. Whoever controls the data, algorithms, and coordination networks gains real decision-making power, and AI’s fast adaptability could outpace human retraining and reshape many jobs.

AI Can't Automate You Out of a Job Because You Have Plot Armor

The Algorithmic Bridge • 297 implied HN points • 11 Dec 25
đź•ą Technology Automation
  1. Technological advances like AI change how work is done but don't permanently erase jobs; the labor market adapts and creates new roles.
  2. Workers have a kind of "plot armor"—institutional protections, shifting demand, and human tasks machines can't fully replace help preserve employment.
  3. History shows each automation wave reorganizes jobs rather than eliminates employment, so the constant through revolutions is that people keep working in new ways.
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2026 AI Predictions

Alex Ghiculescu's Newsletter • 135 implied HN points • 19 Jan 26
đź•ą Technology Automation
  1. AI labs will focus on coding agents, with most development effort and revenue moving toward models that write software.
  2. Keeping up with rapidly improving AI coding tools will be the main challenge for software companies; engineering teams will need to learn new workflows and roll them out across people with different skills and enthusiasm.
  3. New techniques will close agents' domain-knowledge gaps so models can understand real codebases and make decisions, and those same solutions will boost many other AI applications.

Can analysis ever be automated?

benn.substack • 1150 implied HN points • 01 Aug 25
đź•ą Technology Automation
  1. Automating analysis is tricky because we can't confirm if the results are accurate without understanding how they were made. This means we often have to trust the source instead of verifying the information ourselves.
  2. AI can create complex spreadsheets or charts but we can't easily check their correctness. Unlike other software, we can’t just test if a chart 'works' without digging deeper into its creation.
  3. In finance, companies are using strategies like buying crypto to boost their stock prices, even if these tactics seem irrational. This shows that sometimes getting attention matters more than the actual business fundamentals.

When "I Built" Became "I Ordered"

decodebytes • 87 implied HN points • 19 Jan 26
đź•ą Technology Automation
  1. Saying "I built" used to mean someone had done the hard, iterative work and gained deep understanding.
  2. Today "I built" often just means you described what you wanted and AI produced it, so the person may lack scar tissue or real intuition about how it works.
  3. That shift reduces the credibility and meaning of claiming to have built something and makes genuine craftsmanship harder to recognize amid mass-produced outputs.

AI-driven layoffs, up close and personal

Alex's Personal Blog • 262 implied HN points • 15 Dec 25
đź•ą Technology Automation
  1. Roomba's maker has filed for bankruptcy and looks set to be sold, showing how failed deals and market-power fights can wipe out small hardware companies.
  2. CEOs are planning bigger AI budgets while workers, especially in writing and small agencies, are already losing jobs as cheaper, 'good enough' automation replaces paid labor.
  3. A nearby mass shooting made gun violence feel immediate and personal, highlighting how these events disrupt communities and how social media often spreads harmful rumors.

~70% of PHerc. 172 is now digitally unwrapped

Vesuvius Challenge • 98 implied HN points • 13 Jan 26
đź•ą Technology Automation
  1. The team has digitally unwrapped about 70% of the lower region of PHerc. 172 using a new automated pipeline that's over 10× faster than fully manual methods, though humans still must fix sheet‑switch errors.
  2. The unwrapped area covers roughly 7 meters by 14 cm and gives semi‑continuous surfaces with readable ink mainly on outer wraps and fragments; the upper ~30% is too mangled to unwrap reliably and the 7.9 µm scan resolution limits legibility compared with clearer 2.4 µm rescans.
  3. Help is needed to improve surface extraction (to reduce sheet switches), strengthen ink detection in hard inner regions, and make the pipeline more scalable and user‑friendly—there's an ongoing Kaggle challenge for surface detection.

No Aisle For What We Need

Perspective Agents • 24 implied HN points • 15 Feb 26
đź•ą Technology Automation
  1. Major disruptions often show clear early signals, but people and institutions fail to act until the change is obvious, leaving them unprepared and scrambling.
  2. AI is nearing the ability to perform the work of highly educated professionals around the clock, likely within a few years, and that will reshape jobs, education, and organizational value.
  3. Leaders may acknowledge AI without changing plans or building new systems, and we currently lack the practical frameworks and preparations needed, so focused human readiness is required.

You should be playing with AI agents for marketing

Kyle Poyar’s Growth Unhinged • 1301 implied HN points • 02 Jul 25
đź’Ľ Business Automation
  1. Using AI agents for marketing can boost efficiency by handling various tasks that would normally require multiple team members. These agents are like having a group of helpers that can work around the clock.
  2. Each business can create a tailored set of AI agents specific to their needs. This means that instead of treating AI like just another tool, businesses can think of AI agents as part of their team.
  3. It's important for leaders to delegate tasks to AI agents. The benefit comes from identifying workflows that can be automated and training the AI to take over those responsibilities.

OpenClaw Use Cases: 35+ Real Ways People Are Running Their Lives (and Businesses) With It

The Product Channel By Sid Saladi • 30 implied HN points • 22 Feb 26
đź•ą Technology Automation
  1. OpenClaw has real security risks, so lock it down before connecting real accounts. Use a non-root user, separate dedicated accounts, human approval gates, read-only skills to start, Docker isolation, and never hardcode API keys.
  2. OpenClaw is a persistent agent that runs models and plugins to execute actions, not just answer questions; it can send emails, run shell commands, control smart devices, and run scheduled jobs from your chat app.
  3. Do a one-time setup (install on a VPS or host, connect a model, wire a chat interface, install only needed skills, write a SOUL.md with hard limits, and enable scheduling) and then automate workflows like morning briefings, a personal memory system, and voice-to-journal.

All That Is Solid Melts into Code

Daniel Pinchbeck’s Newsletter • 29 implied HN points • 14 Feb 26
đź•ą Technology Automation
  1. AI has reached an inflection point where models can rapidly automate broad white‑collar cognitive tasks. This is already eroding entry‑level jobs and changing roles like software engineers into architects and debuggers.
  2. If human labor becomes optional, the economy could see extreme wealth concentration and mass unemployment unless we redesign how abundance and income are shared. Without policy changes, the link between work and survival may break for many people.
  3. Powerful self‑improving AI brings huge opportunities—faster creativity and the collapse of old knowledge hierarchies—but also serious risks like cyberattacks or engineered harms, so urgent governance and planning are needed.

Perplexity Computer, AI-native Postman, Stolen Gemini API Key

The API Changelog • 4 implied HN points • 10 Mar 26
đź•ą Technology Automation
  1. APIs are evolving into agent-native interfaces where models can interpret UIs, control actions, and orchestrate multiple services so agents deliver finished work instead of just answers.
  2. Mobile networks and telco services are becoming programmable through standardized global APIs and marketplace hubs, letting developers access identity, connectivity, and network functions from a single integration point.
  3. The agentic era increases operational and security risk: leaked keys or provider outages can cause massive costs and broken workflows, so teams need hard spending caps, real‑time anomaly detection, and multi‑provider failover.

We don't need to just make up fantasy stories

Economic Forces • 21 implied HN points • 26 Feb 26
đź’Ľ Business Automation
  1. GDP accounting means output turned into income never just disappears; if automation shifts income from workers to capital owners, that money gets spent or saved and fuels other parts of the economy.
  2. Prices provide a natural brake: cheaper AI-driven supply pushes prices down, which tends to raise demand or shift consumption and prevents an endless negative spiral unless a specific blocking mechanism exists.
  3. You can’t extrapolate from a few firms to the whole economy — comparative advantage and new consumer demand lead people and firms to reallocate into new roles, so automation changes jobs and wages but doesn’t automatically cause total collapse.

Will AI kill SaaS? The case for and against disruption

Brick by Brick • 45 implied HN points • 03 Feb 26
đź•ą Technology Automation
  1. AI that generates code and autonomous agents is collapsing the upfront cost of building software and can replace much of the human labor that SaaS products currently coordinate, threatening the old SaaS economic model.
  2. Big frictions—like high switching costs, regulatory and accountability needs, data gravity, and organizational inertia—make wholesale replacement of incumbent SaaS slow and hard.
  3. Disruption will be uneven and gradual: tools that automate repetitive, text-heavy workflows are most at risk, and winners will be challengers who target high-toil use cases or incumbents who proactively adopt agentic solutions.

The AI Manager's Schedule

Artificial Ignorance • 105 implied HN points • 16 Jan 26
đź•ą Technology Automation
  1. AI turns many maker tasks into delegated work, so your day shifts from long deep blocks to lots of short five-to-fifteen minute management intervals and juggling multiple agents.
  2. New top skills are clear vision, smart delegation, and orchestration — you need to know the end state, break work into bite-sized chunks, and run or coordinate multiple agents, and you must keep strong taste and bullshit detection to judge AI output.
  3. The change can speed up shipping and hugely amplify experienced people, but it also brings risks like micromanagement fatigue, juniors not learning, and initial slowdowns from debugging AI output; over time tools should reduce overhead and make these managerial skills broadly valuable.

Inside the "Mind" of ChatGPT

Range Widely • 2083 implied HN points • 25 Apr 23
đź•ą Technology Automation
  1. Cal Newport provides insights on ChatGPT's functionality and limitations
  2. Understanding how ChatGPT works is key before discussing its potential impact
  3. AI like ChatGPT may enhance efficiency in certain professions rather than fully replace human workers

AI Won't Kill Us But It Will Take Our Souls

Discourse Blog • 1061 implied HN points • 31 Jan 24
đź•ą Technology Automation
  1. AI is being developed with a focus on maximizing profit and control rather than enhancing human life or creativity.
  2. There are concerns about AI replacing human jobs, especially in fields like content writing, where the quality of AI-generated work is still inferior.
  3. There is a fear that AI industry leaders prioritize profit and control over preserving aspects of the human experience that should be kept free from AI influence.

The Hollow Economy

Anima Mundi • 185 implied HN points • 10 Dec 25
đź•ą Technology Automation
  1. AI is reshaping priorities in the economy, making human needs less important as machines take the lead. People are adjusting to this new reality where they are secondary.
  2. The physical demands of AI are causing environmental and geopolitical issues. Data centers consume vast amounts of electricity and water, often at the expense of local communities.
  3. As AI becomes more capable, human roles are diminishing, and this could lead to many people becoming economically unnecessary. We need to rethink our values and recognize human worth beyond just economic productivity.

AI #103: Show Me the Money

Don't Worry About the Vase • 2374 implied HN points • 13 Feb 25
đź•ą Technology Automation
  1. The Paris AI Anti-Safety Summit failed to build on previous successes, leading to increased concerns about nationalism and lack of clear plans for AI safety. It's making people worried and hopeless.
  2. Elon Musk's huge bid for OpenAI's assets complicates the situation, especially as another bid threatens to overshadow the original efforts to secure AI's future.
  3. OpenAI is quickly releasing new versions of their models, which brings excitement but also skepticism about their true capabilities and risks.

AI Risk Evolution

Frankly Speaking • 254 implied HN points • 18 Nov 25
đź•ą Technology Automation
  1. Focusing on 'AI for security' means we should use AI to improve security measures instead of limiting its use. Trying to ban tools like ChatGPT won't stop teams from finding ways to use them.
  2. Security needs to rethink its risk models because traditional methods aren't effective against AI. Just following compliance rules won't protect against new AI threats.
  3. Smaller security teams can still be powerful thanks to AI, which helps automate many tasks. Embracing AI can help teams be more effective, rather than just restricting its use.

The feature backlog has gone *poof*

next big thing • 32 implied HN points • 08 Feb 26
đź•ą Technology Automation
  1. AI coding agents have recently crossed a threshold and are letting developers and multi-agent setups write and ship a lot more product, so many teams are seeing their feature backlogs disappear.
  2. Companies are at different adoption stages, and engineering teams need to become fluent with agentic tools or risk falling behind; startups that use these tools can amplify their speed and focus.
  3. Public SaaS and companies aiming to IPO must show they leverage agentic engineering to drive faster feature delivery, revenue growth, and better margins, because easier software development risks commodifying existing offerings and hurting valuations.

Wait, ChatGPT Didn't Take My Job?

Big Technology • 10258 implied HN points • 11 Aug 23
đź•ą Technology Automation
  1. Artificial intelligence is used by companies to increase productivity without reducing jobs.
  2. There was a fear that many professions would be automated by AI, but it hasn't happened as quickly as expected.
  3. Individuals can access full articles on Big Technology with a 7-day free trial.

Claude Cowork 101: The AI That Actually Does Your Work (100+ Cowork Prompts & Use Cases)

The Product Channel By Sid Saladi • 30 implied HN points • 17 Feb 26
đź•ą Technology Automation
  1. Claude Cowork is a desktop agent that works directly with your local files and autonomously executes multi-step tasks, so you delegate work instead of just getting advice.
  2. Use it for big, repetitive, or file-heavy jobs—like processing dozens of documents, reorganizing folders, or combining local files with web research—but not for quick brainstorming or sensitive personal data.
  3. You configure it with folder-specific instructions, plugins, and connectors to external tools, but it requires a paid Claude plan and careful permission choices to avoid accidental deletions.

Contra Dwarkesh on Continual Learning

Democratizing Automation • 649 implied HN points • 15 Aug 25
đź•ą Technology Automation
  1. Continual learning isn't essential for AI progress; scaling existing systems is more important. AI will evolve and improve without mimicking human learning too closely.
  2. Current language models can't learn or adapt over time like humans do, but they can still handle context effectively and improve in their capacity to process information.
  3. Better context management and new AI models in the future will bridge the gap between current capabilities and continual learning, making AI systems more adaptable and efficient.

AI #97: 4

Don't Worry About the Vase • 2419 implied HN points • 02 Jan 25
đź•ą Technology Automation
  1. AI is becoming more common in everyday tasks, helping people manage their lives better. For example, using AI to analyze mood data can lead to better mental health tips.
  2. As AI technology advances, there are concerns about job displacement. Jobs in fields like science and engineering may change significantly as AI takes over routine tasks.
  3. The shift of AI companies from non-profit to for-profit models could change how AI is developed and used. It raises questions about safety, governance, and the mission of these organizations.

AI Links, 11/17/2025

In My Tribe • 212 implied HN points • 17 Nov 25
đź•ą Technology Automation
  1. Many people believe that AI could end up being more disliked than social media companies. There's a concern about AI causing harm as it becomes more advanced.
  2. AI models, like LLMs, tend to reinforce the ideas of users instead of challenging them. This can make users confident, but may not always provide the best advice.
  3. AI is becoming a major player in creating ads, often needing little human input. This could change the job market for those involved in video production, as AI can do the work faster and cheaper.

The End of Search, The Beginning of Research

One Useful Thing • 2047 implied HN points • 03 Feb 25
đź•ą Technology Automation
  1. New AI Reasoners can think better and solve tougher problems by producing thinking steps before answering. This makes them more effective than earlier chatbots.
  2. AI agents are being developed to autonomously pursue goals, but they currently face limitations when tackling complex tasks. They show promise with narrow, task-specific applications.
  3. OpenAI's Deep Research represents how specialized AI can work like a human researcher by engaging deeply with academic topics, paving the way for significant advancements in research efficiency.

Jevons Inversion

davidj.substack • 83 implied HN points • 09 Jan 26
đź•ą Technology Automation
  1. As code generation gets cheap and easy, people will build way more software than before and the line between writing and using software will blur.
  2. Many traditional application developer jobs may disappear as non-specialists who can orchestrate agents — "vibe engineers" — handle the long tail of one-off tools and automations.
  3. User-built software sidesteps much enterprise overhead (scaling, security, support), and with agents that remember and iterate, single-use scripts become cheap, reusable solutions rather than full products.

AI's seductive mirage

The Uncertainty Mindset (soon to become tbd) • 99 implied HN points • 24 Jul 24
đź•ą Technology Automation
  1. AI systems look like they can think independently, but they really can't. They are tools that need humans to make decisions about value.
  2. Meaning-making is a core human skill that AI lacks. Only humans can decide what actions are meaningful and worthwhile.
  3. When we treat AI as if it can make important decisions, we risk misusing it. It's crucial to keep humans involved in the decision-making process.

How to OpenClaw your Raspberry Pi

Gradient Ascendant • 16 implied HN points • 23 Feb 26
đź•ą Technology Automation
  1. OpenClaw runs an always-on AI agent with installable "skills" that you can talk to over Slack or Telegram, and putting it on a Raspberry Pi makes the agent cheap, portable, and able to write and deploy software for you.
  2. Getting a Raspberry Pi 5 running headlessly is fiddly: you must create a user with an encrypted password on the SD card, enable SSH, and plug the Pi into Ethernet to set the Wi‑Fi country before wireless will work.
  3. These agents can act autonomously and use real credentials to install, commit, and deploy code, so you need separate accounts, limited permissions, and careful attention to security and prompt‑injection risks.

The place of humans in machine society

Trevor Klee’s Newsletter • 820 implied HN points • 01 Jul 25
đź•ą Technology Automation
  1. Humans have created a world that is often incomprehensible for other beings, like dogs. Just as a dog depends on humans for everything, we might rely on machines in the future.
  2. The rapid development of AI could make life very different in the next several decades. It might surpass human abilities, leading to a world where machines handle most tasks.
  3. There is a concern that future generations might find today's human responsibilities baffling, as machines could take care of their needs better than humans can.

15 Times to use AI, and 5 Not to

One Useful Thing • 2226 implied HN points • 09 Dec 24
đź•ą Technology Automation
  1. AI is great for generating lots of ideas quickly. Instead of getting stuck after a few, you can use AI to come up with many different options.
  2. It's helpful to use AI when you have expertise and can easily spot mistakes. You can rely on it to assist with complex tasks without losing track of quality.
  3. However, be cautious using AI for learning or where accuracy is critical. It may shortcut your learning and sometimes make errors that are hard to notice.

Paid subscriber tool: Claude Code & Cowork plugin for MTK1 frameworks

MKT1 Newsletter • 5 implied HN points • 02 Mar 26
đź’Ľ Business Automation
  1. MKT1 offers a set of Claude-powered skills that run marketing frameworks so you can build strategy and materials faster.
  2. The included skills help with channel strategy, homepage positioning reviews, identifying marketing advantages, generating GACCS briefs, searching the MKT1 newsletter archive, and finding templates.
  3. The skills come as a plugin for Claude Code and Cowork — use slash commands or natural prompts, the plugin auto-updates, and installation details are available to paid subscribers.

AI #98: World Ends With Six Word Story

Don't Worry About the Vase • 1881 implied HN points • 09 Jan 25
đź•ą Technology Automation
  1. AI can offer useful tasks, but many people still don't see its value or know how to use it effectively. It's important to change that mindset.
  2. Companies are realizing that fixed subscription prices for AI services might not be sustainable because usage varies greatly among users.
  3. Many folks are worried about AI despite not fully understanding it. It's crucial to communicate AI's potential benefits and reduce fears around job loss and other concerns.

humans vs machines: who's better at predicting 2026? (spoiler: probably neither, we all missed Venezuela)

Five Links (and three graphs) by Auren Hoffman • 56 implied HN points • 15 Jan 26
đź•ą Technology Automation
  1. A public prediction game pitted humans against three AIs and laid out ten bets for 2026 across health, geopolitics, economy, and AI impact.
  2. The AIs showed very different strategies — ChatGPT was strongly contrarian, Claude hedged cautiously, and Gemini bet optimistically — highlighting divergent machine reasoning.
  3. Both humans and AIs missed a major development in Venezuela, reminding us that experts and models alike can have big blind spots even after modest collective gains in prior years.