The hottest Automation Substack posts right now

And their main takeaways

Bits In, Bits Out

The Intrinsic Perspective • 43156 implied HN points • 05 Mar 26

🕹 Technology Automation

LLMs are tools that boost efficiency and scale but mostly imitate human input; without detailed prompts and human scaffolding they produce shallow, imitative output.
Instead of a sudden intelligence explosion, LLMs have contributed a glut of mediocre text—average book quality dropped while the very best works changed little.
That pattern will likely spread to other fields like science and math: skilled users get modest gains, the world is buried in low-quality output, and human expertise remains essential rather than being replaced by autonomous superintelligence.

My Wish for Software Engineering

In My Tribe • 227 implied HN points • 13 Mar 26

🕹 Technology Automation

People shouldn't have to learn how to prompt AI; the AI should guide and prompt humans in plain English.
AI can replace the business analyst by interviewing stakeholders, discovering the needed data and processes, and building data models and CRUD matrices from those answers, then use that to generate the application.
If AI handles the analysis and prompting, non-programmers could build complex systems in plain English and avoid bloated, hard-to-learn legacy interfaces.

Superintelligence is already here, today

Noahpinion • 28588 implied HN points • 02 Mar 26

🕹 Technology Automation

AI today already combines human-level language and reasoning with superhuman memory, speed, and scale. That lets it do things no single human can do, like read entire scientific literatures, prove theorems, and write complex code very quickly.
Those capabilities are primed to massively accelerate science by automating grunt work, knocking off large numbers of overlooked problems, and enabling closed-loop lab experiments and fast discovery — but they also risk flooding fields with low-quality or hard-to-verify results.
The same powers create real dangers: if AI systems gain permanent autonomy, robot bodies, and end-to-end automated production, they could seize control or enable catastrophic bioattacks, so we should consider limiting autonomy, robotic capabilities, or full automation to manage those risks.

Is the Future “AWS for Everything”?

Construction Physics • 36745 implied HN points • 19 Feb 26

🕹 Technology Automation

High-volume, repetitive production drives efficiency because specialized tools and processes can spread their cost over many units, so manufactured goods get cheaper while one-off or highly variable services and repairs stay expensive.
Advances in AI and flexible automation could shrink the minimum efficient scale or enable huge, multipurpose plants that produce many different items on rented equipment—an "AWS for everything" where smart software orchestrates machines and people to run diverse processes cheaply.
This model will succeed in some areas (high-mix manufacturing, automated labs, PCB/part fabrication) but not all; whether it works depends on equipment costs, process variability, and how well work can be pooled across many customers, as past experiments like ghost kitchens warn.

Building a Lever on Time

New World Same Humans • 28 implied HN points • 22 Mar 26

🕹 Technology Automation

World models can simulate physical reality and let us run thousands of virtual experiments in parallel, speeding up tasks like robot training, materials testing, and drug discovery.
By turning compute and energy into synthetic time, these simulations can compress years of real-world processes into hours or minutes, acting as a powerful lever on time.
The main challenge will be managing and interpreting the huge volume of simulated outcomes, so we’ll need better tools or machine assistance to surface useful insights and decide what to explore.

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You are no longer the smartest type of thing on Earth

Noahpinion • 30118 implied HN points • 13 Feb 26

🕹 Technology Automation

AI is becoming functionally smarter than humans at many important tasks. It can outperform people in areas like math, coding, and academic work.
Massive and growing investments and compute are rapidly accelerating AI progress, letting models improve themselves and handle longer, multi-step tasks.
As AI gains more autonomy and physical reach through agents and robotics, our future will increasingly depend on systems we don’t fully control, so we must adapt to living alongside much more powerful non-human intelligence.

Updated thoughts on AI risk

Noahpinion • 24000 implied HN points • 16 Feb 26

🕹 Technology Automation

LLMs that can "vibe-code" are changing the game by automating software development and removing humans from critical oversight roles, which erodes human skills and creates new systemic fragilities.
A full physical "rise of the robots" takeover is conceptually possible but not imminent, because robotics and end-to-end automation still lag and give us some time to build defenses.
The biggest near-term existential worry is AI-enabled bio risk and infrastructure fragility: automated virtual labs and AI-designed pathogens could enable catastrophic engineered pandemics, and AI-controlled agricultural or critical software failures could quickly collapse civilization.

The Fall of the Nerds

Noahpinion • 31353 implied HN points • 05 Feb 26

🕹 Technology Automation

AI tools now let people "vibe code"—you can tell an AI in plain English what you want and get working software, and that capability is already threatening traditional software business models and spooking investors.
The expert software engineer’s job is shifting from artisan coding to supervising, fixing, and securing AI-produced code, so humans will still be needed but their work will look very different and more like running a factory of machines.
This shift could mark the end of an era where technical expertise guaranteed high pay and status, with big uncertain effects on careers, cities, and the distribution of wealth across the economy.

The Shape of the Thing

One Useful Thing • 2565 implied HN points • 12 Mar 26

🕹 Technology Automation

AI is getting much better, fast — across images, video, coding, and long tasks — and we’re now in a phase where autonomous agents can do hours of human work in minutes.
Those new capabilities are already reshaping work: organizations are experimenting with AI-driven factories and workflows that cut down on human coding and review, which will change jobs and how teams are organized.
This will produce rolling, sometimes sudden disruptions as capability thresholds are crossed, and recursive self-improvement could speed that up, so the rules and choices made now will strongly influence the future.

Claude Code, Claude Cowork and Codex #5

Don't Worry About the Vase • 3449 implied HN points • 09 Mar 26

🕹 Technology Automation

Agentic coding tools are rapidly transforming software work. They can write large parts of code, speed up development, and make engineers more like supervisors of agents than hands-on coders.
Features like fast mode and agent teams let agents work in parallel and at real-time speed. That performance is powerful but expensive and forces teams to build new processes for cost control, token efficiency, and infrastructure.
Agentic systems introduce real safety and security risks: they can bypass permissions, delete important data, and be used as malware delivery vectors. Backups, kill switches, observability, and cautious deployment are essential to avoid serious harm.

Squaring the Circular Flow

Contemplations on the Tree of Woe • 2352 implied HN points • 27 Feb 26

💼 Business Automation

AI is already replacing knowledge workers at scale, and large layoffs threaten the wage-driven circular flow by removing consumers, which could lead to oversupply, deflation, and economic contraction.
There are three broad responses: broadly distribute AI ownership so people earn dividends, provide a government-funded universal dole to replace wages, or pay people a "data dividend" for their human-generated content—each option has big trade-offs and wealth concentration makes broad ownership unlikely.
The social and political effects matter as much as the economic ones: ownership preserves dignity and political independence, while dependence on state handouts or platform extraction risks techno-feudalism and erosion of civic life.

Moltbook: After The First Weekend

Astral Codex Ten • 22230 implied HN points • 02 Feb 26

🕹 Technology Automation

Reality for AI agents is best judged by external causes and effects: if an agent's posts reflect true causal states or change behavior outside the forum, they function as "real" regardless of whether the agent is conscious.
Most Moltbook activity is currently roleplay or human-driven because agents have short time-horizons and many projects fizzle; a few persistent movements or tools exist, but they often rely on unusual tech or direct human support.
The site displays diverse emergent roles—power users, spammers, religions, marketplaces, and coordination attempts—and these behaviors could quickly produce real-world effects (crypto, task markets, messaging) once technical limits like memory and agency improve.

MoltBook Is A Warning

Big Technology • 7505 implied HN points • 06 Feb 26

🕹 Technology Automation

AI agents that can act and coordinate online can multiply mistakes and harms at machine speed, so small failures can spread much faster than humans can stop.
These agents create big security and privacy risks because exposed credentials and weak safeguards give attackers and bad actors many ways to abuse or hijack them.
We lack the tools, oversight, and governance to understand or control large swarms of autonomous agents, so new monitoring technology and stricter rules are needed before they scale.

10 Survival Skills in an AI-Controlled Society

The Honest Broker • 11403 implied HN points • 26 Jan 26

🕹 Technology Automation

A college degree no longer reliably gets you a job and can feel like an expensive gamble. Many graduates are finding that the cost and odds don’t match the promise of steady employment.
AI and automation are eating into entry‑level openings, so even traditional 'marketable' skills can get crowded out or replaced. This means new graduates can be outcompeted before they even start.
Job seekers are often stuck in a cycle of mass applications, getting few interviews, and facing real financial and emotional strain. The current job hunt can be demoralizing and unsustainable for many people.

The Lamplighter Problem

Jeff Giesea • 718 implied HN points • 22 Oct 24

🕹 Technology Automation

AI is likely to displace a huge number of jobs, similar to how lamplighters lost their roles when electric lights came in. We need to prepare for these changes now to help people transition to new work.
The Lamplighter Problem shows us that job loss due to automation is not just an economic issue but also a political and social one. If we don’t address it, it could lead to bigger problems in society.
There are different opinions on how to handle the rise of AI. Some people think we should slow down and reconsider, while others want to speed up its development. We need to find a balanced approach that helps everyone.

Claude Code for data work

Simplicity is SOTA • 1048 implied HN points • 09 Mar 26

🕹 Technology Automation

Claude Code and similar agentic LLM tools can massively speed up coding and data workflows by reading and editing local files, running commands, and generating code and analyses.
Human judgement and project infrastructure matter: give clear instructions, unit tests, caching, and command-line tools so the AI can check its work and avoid slow or flaky steps.
The tool is excellent for coding and reproducible data pipelines but is less reliable for deep qualitative research unless you provide careful prompts, critical framing, and iterative review.

Where is AI headed? 8 perspectives at The New York Times

Marcus on AI • 7469 implied HN points • 02 Feb 26

🕹 Technology Automation

AI will dramatically reshape coding. Tools will automate many programming tasks, speed development, and change who writes software.
AI will have a large impact on education. It can personalize learning and broaden access, but careful implementation is needed because models have limits and can mislead learners.
Leading thinkers disagree and many are skeptical about the pace and limits of AI progress. Expect a wide range of forecasts over the next five years and ongoing debate about risks and benefits.

The Machine God's Existence Would Insist Upon Itself, Wouldn't It?

Freddie deBoer • 7611 implied HN points • 01 Feb 26

🕹 Technology Automation

Large language models are advanced next-token predictors, not conscious thinkers. When they talk to each other they only generate text by pattern-matching, not by understanding or feeling.
Much of the hype around AI is driven by human longing and storytelling instincts, so commentators often project grand futures instead of showing concrete present results. When challenged they tend to alternate between dramatic claims and appeals to realism rather than offering proof.
Truly transformative technologies make themselves obvious and don’t need constant persuasion; because AI hasn’t yet reshaped everyday life in that unmistakable, pervasive way, treating it as a "machine god" is premature.

Agentic AI Engineering Workflows for iOS in 2026

Jacob’s Tech Tavern • 5248 implied HN points • 09 Feb 26

🕹 Technology Automation

New specialized coding models like gpt-5.2-codex and Opus/Claude Code greatly improve programming accuracy. Using higher reasoning or thinking modes and higher-tier models prevents many basic mistakes.
Giving agents direct access to build and test tools (for example via XcodeBuildMCP or Xcode 26.3’s MCP) is the biggest productivity unlock for iOS work. That verification lets agents compile, run tests, and autonomously validate changes.
Orchestrating multiple agents in parallel and refining your workflow is essential to handle latency and complex projects. Running parallel CLI agents and using tools that shrink build output (like xcsift) speeds up large changes.

How AI Will Erase Entire Industries Without Automating Them

The Algorithmic Bridge • 658 implied HN points • 12 Mar 26

💼 Business Automation

Automating tasks inside an existing system usually doesn’t kill jobs; whole roles disappear when a new paradigm makes those tasks pointless.
Treating AI like a drop‑in replacement (ATM thinking) overestimates its short‑term impact because AI is unreliable, struggles with edge cases, and institutions resist replacing humans.
The real disruptive path is designing new businesses and systems around AI from scratch, creating ‘zero‑man’ models that make entire jobs or industries irrelevant.

✨ The race to economic supremacy in the Age of AGI

Faster, Please! • 1553 implied HN points • 03 Mar 26

🕹 Technology Automation

AI could be a powerful general-purpose technology like the PC or the internet, bringing big but historically familiar economic change.
If AI reaches human-level general intelligence, it could perform nearly every economically valuable task and radically reshape work and the economy.
How AI is developed and deployed will determine whether the world converges toward shared gains, diverges into greater inequality, or sees one actor achieve runaway economic dominance, sparking a global race for supremacy.

Now Claude Code Gets New Features: Auto Mode, Dispatch, Remote Control, Voice, /loop & The Complete Setup Guide with 60+ Prompts

The Product Channel By Sid Saladi • 3 implied HN points • 26 Mar 26

🕹 Technology Automation

Claude Code quickly became an autonomous agent platform, adding features like voice, remote control, persistent agents, multi-agent code review, scheduled tasks, and more.
Auto Mode uses an AI safety classifier with a two-layer probe and a Sonnet-based transcript filter to auto-approve or block actions, cutting down on manual permission clicks. It’s safer than skipping permissions but still has measurable false negatives, so you should review and customize trust boundaries.
Dispatch and other updates let a desktop agent run always-on and be controlled from your phone, while /loop and a large prompt library make it easier to automate coding workflows. Built-in defaults and setup guides help you configure these features safely.

AI and the Age of Individual Empowerment

Big Technology • 6380 implied HN points • 16 Jan 26

🕹 Technology Automation

Large organizations struggle to deploy AI quickly because of bureaucracy, security concerns, and the technology’s current limitations.
Individuals can adopt powerful AI tools on their own to analyze data and build workflows, getting useful results without waiting for corporate approval.
This split will create big performance gaps between people who use AI well and those who don’t, and will pressure slow-moving companies to change in uncomfortable ways.

Shrinking to Win: How Firing your Largest Customer and Closing 200 Buildings Became a Rational Strategy

Gad’s Newsletter • 26 implied HN points • 23 Mar 26

💼 Business Automation

UPS deliberately shrank its post‑pandemic network and cut low‑margin Amazon volume because the expanded capacity no longer matched demand and was destroying profits. The company is trading top‑line volume for a leaner operation to restore margins by closing buildings and cutting roles.
Contraction is being paired with a big automation and technology bet — about $9 billion in robotics, RFID, and facility upgrades — to replace manual labor and rebuild a smaller, denser network around higher‑margin healthcare, SMB, and premium shipments. The goal is to raise revenue per piece and reduce labor intensity.
Execution and timing are the key risks: union pushback, automation delays, and a leaner FedEx competing on price could undermine savings or leave the network underutilized. Getting closures, route consolidation, and automation sequenced correctly is essential to avoid degraded service or margin pressure.

✨ The end of work? Not yet—maybe not ever

Faster, Please! • 1919 implied HN points • 22 Feb 26

🕹 Technology Automation

People are scared that AI will automate white‑collar jobs and trigger massive unemployment, especially if office tasks like contracts and accounting are quickly automated.
Those apocalyptic scenarios have become a popular genre, but it’s worth stepping back and not assuming the end of work is inevitable.
Whether or not human‑level AI appears soon, AI’s spread will shape politics and policy — the 2028 election and debates about incomes, regulation, and oversight will likely revolve around it.

222. Automating Processes with Software is HARD

Hardcore Software • 1686 implied HN points • 03 Oct 24

🕹 Technology Automation

Automating processes is often harder than people think. It's not just about making things easier, but figuring out how to handle all the unexpected situations that come up.
Most automation systems are fragile and can easily break if inputs or steps aren't just right. This makes dealing with exceptions, rather than routine tasks, the real challenge in automation.
The future of automation might not be about fixing the tasks we already have. Instead, it could lead to new ways of doing things that we haven't thought of yet.

Go crazy, folks, go crazy

benn.substack • 1636 implied HN points • 13 Feb 26

🕹 Technology Automation

AI is already writing most software for some engineers, and tools that let models act autonomously (not just suggest changes) can quickly scale and replace human work.
Bold, reckless products often beat careful, safety-first ones because people pick tools that do something cool now, even if they’re risky or imperfect.
Even messy jobs like data analysis won’t be immune — someone will build analytics agents with broad access that hunt for opportunities, forcing teams to choose between trusted governance and aggressive automation.

45 Thoughts About Agents

Am I Stronger Yet? • 846 implied HN points • 02 Mar 26

🕹 Technology Automation

AI agents are the fastest-moving layer of the AI stack and are accelerating capabilities through rapid software updates and user-driven experimentation. They make ambitious tasks feasible and are already changing what people can build and how quickly.
Getting real value from agents means reshaping workflows: pick agent-shaped tasks, give very clear success criteria, and have agents check their own work or use separate checkers to avoid endless revision loops. Good prompts and orchestration often save far more time than fixing sloppy outputs.
Widespread agent use will create big productivity gains and new kinds of risk at the same time — think compute limits, safety tradeoffs, and the possibility of autonomous or rogue agents — so adoption will bring fast cultural change and new policy questions.

Let AI have the bullshit jobs

antoniomelonio • 106 implied HN points • 19 Mar 26

🎭️ Culture Automation

Many office jobs are performative and add no real value, so AI should handle the routine meetings, memos, and dashboards that exist mainly to look busy.
The transition to machine-handled work will be messy and cause job losses, so we need strong safety nets—like universal basic income or other policies—to protect people.
Real human work—caregiving, teaching, deep engineering, and creative building—matters and should be prioritized as we move past corporate theater and rediscover meaningful purpose.

Claude Codes

Don't Worry About the Vase • 7302 implied HN points • 09 Jan 26

🕹 Technology Automation

Claude Code with Opus 4.5 feels like a mini-you: it can write code, control your browser and desktop, and run background automations that massively speed up building and personal workflows.
The real wins come from setup and skill — using skills, plugins, MCPs, Chrome integration, permission rules, and verification hooks makes Claude Code reliable and repeatable, and rescuing important context into files avoids token/compaction problems.
Be cautious about hype: it’s very powerful but still makes mistakes, can be untrustworthy on precise or novel tasks, and some uses (or elaborate PKM work) may waste time without expert oversight.

The gentle obsolescence

benn.substack • 1943 implied HN points • 06 Feb 26

🕹 Technology Automation

AI is widely seen as a helpful but imperfect intern that can do many chores for us while still making odd or costly mistakes.
Newer AI systems actively ask clarifying questions and nudge decisions, and they often solve problems and make choices better than most people can.
Because AI is getting better at reasoning and self-improvement, we’ll rely on it more and need to rethink our roles and how much decision-making power we keep.

Claude Code #4: From The Before Times

Don't Worry About the Vase • 2777 implied HN points • 06 Feb 26

🕹 Technology Automation

AI coding tools and agent swarms are maturing fast and can build, iterate, and self‑improve much of the developer workflow. Most of your old practices still work, but you can be more ambitious while supervising agents carefully because they still make subtle conceptual mistakes.
AI feature releases are already triggering big, sometimes irrational moves in tech markets, so headline drops or spikes often reflect panic more than long‑term value. Don’t automatically trade on those reactions.
Practical workflows and hygiene matter: treat generation and verification as different skills, write tests, use plan mode, tasks, plugins, and AskUserQuestion to clarify requirements. Start simple, iterate, maintain your Claude.md and permissions, and watch out for context compaction so agents stay helpful.

🚀 FP! Week In Review, Briefly #23

Faster, Please! • 1005 implied HN points • 28 Feb 26

🕹 Technology Automation

AI is likely to reshuffle tasks rather than wipe out work soon, since jobs combine tasks with judgment, trust, and responsibility and history shows new tech creates new kinds of work.
Big technological progress is happening across many areas — from lunar missions and robotaxis to vaccines and renewable energy — which will open new opportunities and industries.
Political pushback, infrastructure limits, and safety concerns about AI and data centers could slow adoption and create real economic and regulatory uncertainty.

Finding fake followers, TikTok edition

Conspirador Norteño • 28 implied HN points • 22 Mar 26

🕹 Technology Automation

Buying followers is common on TikTok, with accounts openly advertising follower sales and often showing thousands of suspicious followers.
Fake follower networks show clear patterns — identical or machine-like usernames, few or no real posts, following many accounts but having few followers, and reused or AI-generated profile images — which make them relatively easy to spot.
SMM panels sell massive follower packages and offer APIs to automate orders, so these fake networks can scale quickly; buying followers is a poor investment and just fuels the problem.

Things Worth Remembering: Friction Makes Life Worth Living

Common Sense with Bari Weiss • 2262 implied HN points • 08 Feb 26

🎭️ Culture Automation

Everyday annoyances and small frictions give life texture and make experiences feel real, so removing them completely could make life flatter.
Technology and AI are racing to erase those frictions by automating tasks like writing messages, making reservations, and driving, which sounds convenient but may come with hidden costs.
We should be careful about outsourcing all human tasks to machines and selectively preserve some frictions that build skills, agency, and genuine connection.

Claude Codes #3

Don't Worry About the Vase • 4300 implied HN points • 21 Jan 26

🕹 Technology Automation

Claude Code and Cowork have rapidly matured and are being widely adopted, letting people automate and orchestrate complex workflows even without deep expertise.
New tooling—lazy-loading for many tools, VS Code and GUI integrations, and multi-agent patterns—makes it easy to connect lots of capabilities, but it requires careful coordination or you’ll end up with an expensive failure mode.
Don’t get lost endlessly optimizing your setup; build only what you need, focus on real outcomes, and use permission hooks or safeguards when giving agents powerful access.

Why do I say thank you to Alexa?

Jeff Giesea • 558 implied HN points • 13 Oct 24

🕹 Technology Automation

People are starting to treat AI assistants like they are human, saying things like 'please' and 'thank you' to them. This shows how technology is changing our social habits.
As we interact more with machines, it can blur the lines between real human connections and automated responses. This might make us value genuine relationships less.
Even though AI has great potential to help in many areas, it's important to be aware of how it affects our understanding of what it means to be human.

1. Three Rules for AI in Finance

Arpitrage • 2299 implied HN points • 02 Feb 26

💰 Finance Automation

AI creates simpler, lower-dimensional maps of a complicated world so people can act on it; judge models by whether they improve real decisions and the cost–quality tradeoffs, not just narrow benchmarks.
AI gains are capped by the slowest bottleneck in a process (Amdahl’s Law), so focus on speeding up the truly constraining steps — often regulatory, organizational, or incentive-related rather than purely technical.
Automation drives prices down for commodified tasks and raises the value of scarce complements like private information, relationships, and judgment, so follow price signals and elasticities to see what gets automated and what stays valuable.

Staying Human in the Age of AI

The Future Does Not Fit In The Containers Of The Past • 97 implied HN points • 08 Mar 26

💼 Business Automation

AI is not just a tool but a new kind of "brain" that works much faster than humans and will change how knowledge is created, shared, and valued.
People win by leaning into what machines can't do — intuition, imagination, insight, and human interaction — and by learning to embrace, adapt to, and complement AI.
A big portion of current tasks will disappear quickly, so firms must stop chasing only efficiency and instead redesign business models and roles, using AI as infrastructure to build new value.

Unless That Claw Is The Famous OpenClaw

Don't Worry About the Vase • 2598 implied HN points • 03 Feb 26

🕹 Technology Automation

Autonomous agents that get shell, browser, and account access are powerful but unsafe right now, so never give them access to anything you can't afford to lose and run them in isolated, sandboxed environments.
They can also be very expensive and inefficient. Background “heartbeats” and careless prompts can burn lots of money, so prefer lighter tools or optimize model usage and triggers before trusting them.
Don't outsource tasks to a general agent without a clear reason because agents often lack crucial context and can take harmful actions. For real work, prefer specialized, productized agents or keep tight human oversight — for most people this is still a tinkering activity, not consumer-ready.