Sweden's Lovable becomes fastest growing software company ever by skyrocketing to $100 million ARR in 8 months - EU-Startups
<a href="https://news.google.com/rss/articles/CBMi3gFBVV95cUxQdGw0dnFxNDd0SzlfMDhEMm1QY0FWTXJpQVdtZGRYdGpqLW5sdnBacEZnRWc2TnBqYUlkYnNab0RzbjdNX1NJQ09mZFhKa1lyYl8yT3F3ZHVCNExFdjhhRU8tcTVDSV9uMjNZNG1ha0FLTDZpeVhCSUN6ZTl5cUtsbUxfSTM5WjQzWGlJbE1GYkZuMjAxM0VMdG1DRmVhSE9uaFNQTnVTX1UyQnVjejdkNFJtdmo0d05NZEprUy1VZHNzTjZhcFVtT3dqWFFKU0UxcVNHTmc2VkY2LTRHdnc?oc=5" target="_blank">Sweden's Lovable becomes fastest growing software company ever by skyrocketing to $100 million ARR in 8 months</a> <font color="#6f6f6f">EU-Startups</font>
Could not retrieve the full article text.
Read on Google News AI Sweden →Sign in to highlight and annotate this article

Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
startupcompanymillion
The Ethics Theater of AI: Why Switching From ChatGPT to Claude Changes Less Than You Think
When a tech company draws a moral line, follow the money first — and ask questions later. Because the uncomfortable truth is that every major AI company today sits inside the same political and economic ecosystem — one deeply intertwined with governments, military contracts, and national security interests. Welcome to late-stage capitalism. And/or techno-feudalism. Switching chatbots may change the interface. And that uneasy feeling in your gut. It hardly changes the system. Read All

Build a Multi-Agent Data Pipeline in 50 Lines of Neam
<p>In this tutorial, you'll build a working multi-agent data pipeline using Neam, an agentic AI programming language. By the end, you'll have a DIO orchestrating five agents through a churn prediction workflow.</p> <p><strong>Step 1: Define Your Infrastructure Profile. This tells every agent where data lives and what compliance rules apply:</strong><br> </p> <div class="highlight js-code-highlight"> <pre class="highlight hcl"><code><span class="nx">infrastructure_profile</span> <span class="nx">MyInfra</span> <span class="p">{</span> <span class="nx">data_warehouse</span><span class="err">:</span> <span class="p">{</span> <span class="nx">platform</span><span class="err">:</span> <span class="s2">"postgres"</span><span class="p">,</span> <span class="nx">connection</span><span class="err">

The axios Supply Chain Attack Just Proved Why Static Analysis Matters More Than Ever
<p>On March 31, 2026, axios — one of npm's most downloaded HTTP client libraries — was hit by a supply chain attack. The lead maintainer's account was compromised, and malicious code was pushed to millions of downstream projects.</p> <p>I've been building a security scanner for AI-generated code for the past month. When I saw this news break on Zenn's trending page, my first thought wasn't "that's terrible." It was: <strong>"This is exactly the class of problem I've been losing sleep over."</strong></p> <h2> What Happened </h2> <p>An attacker hijacked the lead maintainer's npm account and published a compromised version of axios. If you ran <code>npm install</code> at the wrong time, you pulled in code that wasn't written by anyone you trust.</p> <p>This isn't theoretical. This isn't a CTF
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Products
How to Stay Employable When AI Is Coming for Your Job
Over the past few weeks, I have had a lot of conversations with people who are genuinely worried about what AI means for their careers. Not just developers, but marketers, analysts, lawyers, and others who are starting to wonder how much of their job will exist in 2-3 years. The anxiety is real and not Continue reading "How to Stay Employable When AI Is Coming for Your Job" The post How to Stay Employable When AI Is Coming for Your Job appeared first on Gradient Flow .

The Curse of Excessive Kindness and the Economics of Empathy — Why Imprecise Comfort Creates Both Fatigue and Cost
<p><a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Ffo1wz9y69ncom3apqkli.jpg" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Ffo1wz9y69ncom3apqkli.jpg" alt=" " width="800" height="446"></a></p> <p>𝟏. 𝐇𝐚𝐬 𝐊𝐢𝐧𝐝𝐞𝐫 𝐀𝐈 𝐑𝐞𝐚𝐥𝐥𝐲 𝐁𝐞𝐜𝐨𝐦𝐞 𝐁𝐞𝐭𝐭𝐞𝐫 𝐀𝐈?<br> <br> For a long time, we wanted AI to become kinder.<br> Compared to cold, mechanical replies, a system that receives our words gently and handles our emotions without bruising them felt like a more advanced form of technolog

Build a Multi-Agent Data Pipeline in 50 Lines of Neam
<p>In this tutorial, you'll build a working multi-agent data pipeline using Neam, an agentic AI programming language. By the end, you'll have a DIO orchestrating five agents through a churn prediction workflow.</p> <p><strong>Step 1: Define Your Infrastructure Profile. This tells every agent where data lives and what compliance rules apply:</strong><br> </p> <div class="highlight js-code-highlight"> <pre class="highlight hcl"><code><span class="nx">infrastructure_profile</span> <span class="nx">MyInfra</span> <span class="p">{</span> <span class="nx">data_warehouse</span><span class="err">:</span> <span class="p">{</span> <span class="nx">platform</span><span class="err">:</span> <span class="s2">"postgres"</span><span class="p">,</span> <span class="nx">connection</span><span class="err">

Claude Code subagents: how to run parallel tasks without hitting rate limits
<h1> Claude Code subagents: how to run parallel tasks without hitting rate limits </h1> <p>One of the least-documented features of Claude Code is its ability to spin up subagents — separate Claude instances that handle isolated tasks in parallel. If you've been running everything sequentially and wondering why your agent workflow feels slow, this is the missing piece.</p> <h2> What is a subagent in Claude Code? </h2> <p>When Claude Code encounters a task that can be broken into independent pieces, it can launch child processes that each have their own context window, their own tool access, and their own conversation thread. The parent agent coordinates; the subagents execute.</p> <p>This is different from just having a long conversation. Each subagent starts fresh — clean context, no accum
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!