The hottest Automation Substack posts right now

And their main takeaways

Why You Should Consider an EV

Kartick’s Blog • 0 implied HN points • 07 Feb 25

🕹 Technology Automation

EVs are really fun to drive because they can accelerate quickly and smoothly. This makes them feel exciting without the bumps and noise you get from regular cars.
They offer more space inside since they don't have a big engine taking up room. Some even have extra storage in the front.
Driving an EV is less tiring because they handle bumps and noise well. Long drives feel easier, and you just relax more while driving.

More things need to be made programmable

Expand Mapping with Mike Morrow • 0 implied HN points • 13 Feb 25

🕹 Technology Automation

Creating small apps has become much easier with tools that let you describe what you want in simple language, and the code appears for you.
Many everyday devices should be able to run code themselves without needing complex setups or smart home networks, like rice cookers and bread machines.
It's important for more devices to have user-friendly ways to execute scripts and do useful tasks instead of just being controlled by apps.

Tippets #195

Tippets by Taps • 0 implied HN points • 08 Jun 25

🕹 Technology Automation

AI tools help developers focus on important tasks by taking care of boring and repetitive work. This change is making how software is built much more efficient.
As AI becomes more social, people are starting to form emotional connections with these systems. This raises questions about trust and how we define relationships in our digital world.
Walmart is using AI to improve how they operate by creating personalized shopping experiences. They're focusing on tasks that make shopping easier and more enjoyable for customers.

20250629

Curious futures (KGhosh) • 0 implied HN points • 29 Jun 25

🕹 Technology Automation

AI is quickly growing, but there's a risk that future models could become less reliable. This is because they might be trained on data made by other AIs instead of real human data.
There's a mix of technology and nature emerging, like humans working closely with fungi and using AI in their daily lives. This relationship is about finding balance and thriving together, instead of competing.
Despite challenges like security threats, communities are finding new ways to come together, like planting trees and exploring creative collaborations, showing that human connections are still very important.

Integrating Multiple AI Agents

The API Changelog • 0 implied HN points • 11 Jul 25

🕹 Technology Automation

Using multiple AI agents can help achieve tasks that require different skills and specializations. This makes it easier to tackle complex problems by dividing them into smaller parts.
The Agent2Agent Protocol (A2A) simplifies how these AI agents communicate and collaborate. It helps them find and interact with each other smoothly to work as a team.
Standardizing the way agents communicate is essential for effective collaboration. This helps ensure that agents share information correctly and can produce the best results together.

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Services SoWs Are Dead. Long live the Software‑Defined SoW!

OSS.fund Newsletter • 0 implied HN points • 31 Jul 25

💼 Business Automation

Traditional Statements of Work (SoWs) are becoming less relevant because AI orchestration is streamlining processes. This means less time spent on integration work and more focus on effective solutions.
The rise of software-defined SoWs allows for programmable and automated contracts, replacing old static agreements. This shift opens new opportunities for consulting firms to innovate and adapt.
While the automation of tasks may seem threatening, history shows that new technology tends to create fresh job roles focusing on oversight and design, shifting the workforce toward higher-value activities.

Machine-Oriented Use-Case Documentation

The API Changelog • 0 implied HN points • 22 Aug 25

🕹 Technology Automation

It's important for API documentation to be clear and follow established standards so that machines can easily understand how to use them. When the documentation is done right, it helps machines know what to do with the data.
Documenting how different API operations fit together is crucial for allowing users to create their own workflows. This means explaining how to connect operations and what each step does.
Choosing the right names for input and output variables in APIs is key to avoiding confusion for machines. If names or data types don't match up, it can lead to errors or unexpected results in workflows.

20250803

Curious futures (KGhosh) • 0 implied HN points • 03 Aug 25

🕹 Technology Automation

Automation is changing jobs by cutting down staff and lowering wages. This means workers need to adapt to new tools and technologies.
AI is playing a bigger role in our lives, but many projects might not make it past the next few years. It's important to be cautious about how we use it.
A focus on creativity and risk-taking in coding is becoming more valuable. This shift encourages programmers to think outside the box and find innovative solutions.

How AI Gave Me My Time Back

Crypto Good • 0 implied HN points • 13 Nov 25

🕹 Technology Automation

AI can save you a lot of time on tasks that usually take forever, like grant writing. It can turn hours of work into just a few minutes.
You don’t need to be a tech expert to use AI; it’s designed to be user-friendly. The technology can understand your needs without requiring deep knowledge.
AI tools are becoming essential for many people. They help free up time so you can focus more on your real goals and dreams instead of just routine tasks.

If no one builds it, you're never born.

Artificial General Ideas • 0 implied HN points • 08 Dec 25

🕹 Technology Automation

Not building AGI could leave humanity unprepared for future challenges, just like past advancements have helped us overcome difficulties. We need innovation to face problems that might threaten our existence.
Scaling current AI methods won’t create AGI but will lead to powerful AI systems. Making AI safe is just as crucial as making it useful, and we should focus on both.
AGI has the potential to improve our ability to respond to disasters, enhance health care, and promote sustainable agriculture, helping humanity survive and thrive in various areas.

Going Bananas 🍌

Digital Native • 0 implied HN points • 26 Nov 25

🕹 Technology Automation

Powerful new creative models sharply lower the cost and skill needed to make high-quality images, videos, and content, triggering a surge of creators and shifting value toward discovery and curation platforms.
AI is evolving from assistant to executor, so most knowledge workers will become middle managers who direct suites of automated agents, reshaping hiring, pricing, and organizational structure.
Models enable extreme hyper-personalization—bespoke apps, ads, and synthetic people tailored to individual tastes—which will change marketing and media while also amplifying social backlash, inequality, and regulatory pressure.

Edition 1: AI for Offense Is Here. Defenders Aren’t Ready.

Boring AppSec • 0 implied HN points • 17 Dec 25

🕹 Technology Automation

AI-orchestrated offensive campaigns are real and practical: coding agents, sub-agents and MCP can automate most of the cyber kill chain and run multi-day operations with minimal human input.
Defenders are behind and must upskill quickly — learn to use AI defensively, run safe agent experiments in staging, assign dedicated AI-operator roles, and build human-in-the-loop checkpoints.
AI tools bring new failure modes and risks: hallucinations mean you need verifier components, simple structured markdown can serve as a useful memory layer, and tight sandboxing plus MCP observability are critical to limit abuse.

Generating an API README with AI

The API Changelog • 0 implied HN points • 19 Dec 25

🕹 Technology Automation

A clear, high-quality README is essential because a bad one can damage your API's reputation; it's better to have no README than a poor one.
AI can generate good overview and getting-started sections from a complete machine-readable API spec like OpenAPI, but the spec must include onboarding details (auth, credentials) and starter operations should be tagged.
Tag important operations by use case so AI can find and document them, and always review and manually approve any AI-generated README updates rather than fully automating the process.

Using MCP Tools Inside Workflows

The API Changelog • 0 implied HN points • 28 Nov 25

🕹 Technology Automation

MCP is a standardized way to expose capabilities using JSON-RPC, so it talks about operations (not resources) and is easier to discover and consume than vague REST APIs.
You can call MCP tools from workflows by making JSON-RPC requests, initializing a session to get the mcp-session-id, and mapping each tool's inputSchema to workflow inputs; outputs may be structured or unstructured and might need parsing.
Putting MCP tools into workflows gives predictable, traceable, and more secure execution with easier debugging and reliability, though adapting unstructured tool outputs to procedural steps has some implementation cost.

Stop Working Like Machines: Deep Dive with Gemini

Crypto Good • 0 implied HN points • 27 Dec 25

🕹 Technology Automation

AI is making cognitive work extremely cheap, which will drive down prices across goods and services and shift scarcity away from smarts toward human connection and visionary roles.
People will need to stop doing first drafts and rote work and instead orchestrate AI — auditing outputs, connecting adjacent skills, and deciding why things get built.
Education and social systems must change: teach inquiry, systems thinking, ethics, empathy, and negotiation, and provide safety nets while shifting identity from task-based utility to imagination and vision.

Tippets #200

Tippets by Taps • 0 implied HN points • 28 Dec 25

🕹 Technology Automation

AI agents that hold and use decision history and surrounding context (a "context graph") will become the primary interface and could act as a new system of record on top of existing tools.
AI is this generation’s foundational material—like steel—so when integrated deeply it can let organizations be redesigned rather than just having chatbots tacked onto old processes.
Making knowledge work much cheaper will likely increase demand rather than reduce it, enabling small teams to tackle work that used to require big firms and creating new jobs and projects.

20260111

Curious futures (KGhosh) • 0 implied HN points • 11 Jan 26

🕹 Technology Automation

AI often produces imaginative but unreliable outputs that can be misleading or false, and those hallucinations can trigger real-world confusion and disruption.
Organizations need human-led guardrails like futures literacy, workshops, and pragmatic labs to turn AI creativity into useful work and to prevent chaotic or harmful decisions.
AI is already reshaping jobs, business models, and culture, prompting investor attention and community responses like repurposing spaces and experimenting with new social practices.

Arm Up. It's 2026

Crypto Good • 0 implied HN points • 01 Jan 26

🕹 Technology Automation

The old tools and slow methods have failed and the world’s big problems need solutions that move far faster and smarter than human speed alone.
Modern AI can massively amplify one person’s impact by automating deep research, writing, coding, media, and fundraising so work that took weeks happens in seconds.
Adopt a concrete AI toolkit—research, real-time, creative, and grant tools—and use them now to scale impact instead of relying on outdated approaches.

#43: Thought Experiment: Don't Pay The Coordination Tax

OSS.fund Newsletter • 0 implied HN points • 08 Jan 26

💼 Business Automation

Multi-layer approval chains for low-value purchases mostly exist to diffuse blame rather than improve decisions, and they add unnecessary delay.
Auditable AI agents can enforce policy, score risk, auto-approve routine buys in seconds, and keep better tamper-proof audit trails.
You’re paying a coordination tax in time and money — audit small purchases and automate rule-compliant approvals so people can focus on genuine judgment and analysis.

The buck stops here

Brave New Teams • 0 implied HN points • 25 Jan 26

🕹 Technology Automation

AI has made basic competence—drafting, summarising and producing text—cheap and abundant, so markets now reward people who deliver real results, not just plausible outputs. That shifts value toward asking the right questions and owning the consequences of decisions.
Three human scarcities remain valuable: setting ends and moral choices (and taking the blame), verifying models with fresh real-world signals, and winning acceptance through trust and relationships. These tasks require being inside institutions and doing hard fieldwork, not just producing words.
Work will shift from content production to governance: people will be paid to edit, test, decide and take responsibility while AI handles generation. The mediocre who only produce plausible text without owning outcomes will be displaced, while skilled operators who bind AI to reality, responsibility and trust will win.

AGI is probably here

davidj.substack • 0 implied HN points • 21 Jan 26

🕹 Technology Automation

Practical guidance on the must-have AI tools and skills to grow your career and business in 2026 will be a core focus.
Expect a VC-focused perspective on whether AI is a bubble and which kinds of AI startups are likely to get funded next year.
The message stresses that AI is accelerating fast and may make AGI imminent, and it looks at what's dying and what's next—AI agents, automations, prompting—using examples like AI-driven viral LinkedIn growth.

AI diffusion

Experiments with NLP and GPT-3 • 0 implied HN points • 13 Feb 26

🕹 Technology Automation

AI diffusion is the next big shift for organizations, and companies must move quickly to integrate AI across workflows or risk falling behind.
Adopting AI isn't just buying subscriptions or tools; it means redesigning processes so AI use measurably improves outcomes and lets employees do more than before.
People resist change, so leaders must set new processes to drive adoption; platforms for AI agents will help but enterprises will need stronger, purpose-built solutions and many startups will emerge to meet that need.

Using AI to Improve AI Tools

Front Left • 0 implied HN points • 17 Feb 26

🕹 Technology Automation

Use AI to build AI tools so those tools can iteratively improve themselves, removing the human as the weakest link in keeping systems up to date.
Having tools that can self-audit and regenerate parts like knowledge synthesis and skill-writing creates a strong dogfooding loop that drives steady improvement.
Be careful: large language models are stochastic, so recursive self-improvement won’t always converge and can spiral; set stopping rules and watch for diminishing returns.

Exposing Workflows as API Operations

The API Changelog • 0 implied HN points • 27 Feb 26

🕹 Technology Automation

Make workflows callable as API operations so they can be triggered remotely by webhooks or other services instead of relying on slow, wasteful polling.
Open standards like Arazzo (convertible to OpenAPI) let you describe and chain workflow steps as API operations, but the tooling is new and requires learning and setup.
You can either use built-in webhook support or ready-made workflow tools, or fully convert workflows to OpenAPI; each choice has tradeoffs in complexity, maintenance, and required technical skill or hiring.

3 AI hacks you can try today

ppdispatch • 0 implied HN points • 27 Mar 26

🕹 Technology Automation

Run multiple AI models on the same coding task with their identities hidden and vote on the outputs. This lets you discover which model actually works for your codebase instead of trusting benchmarks.
Start prompts with a line asking the AI to interview you first, for example "Before you begin, ask me any questions needed for context." Having the AI ask clarifying questions forces useful context to surface and dramatically improves results.
Prioritize context engineering over clever prompts by feeding models relevant docs, code, user history, and live API data before asking anything. Giving the model real, focused context reduces hallucinations and yields much more accurate, tailored outputs.