I just red a study I had to share with you guys. Eight months ago, the best AI agent in the world could only complete 2.5% of real freelance projects to a client-acceptable standard. Today that number is 16.1%. The Remote Labor Index tests AI agents on actual commissioned work (3D/CAD, architecture, video, web dev, and more), with every deliverable judged by human evaluators against a professional's paid output, not a benchmark score. The new leader is Anthropic's Fable 5, roughly double Opus 4.8 (8.3%) and well ahead of GPT-5.5 (6.3%). Here's the part I find reassuring: the researchers also tried replacing human evaluators with an AI judge. It overestimated the newest models' performance by up to 3x. Turns out we can't yet trust an AI to reliably judge another AI's work, human evaluation is still doing the heavy lifting. So no, humans aren't out of the loop yet. But going from 2.5% to 16.1% in under 8 months is the kind of curve that should have people paying attention, regardless of industry. Curious how others here read this: signal of what's coming, or still early enough not to worry? Source: https://safe.ai/blog/significant-increase-in-digital-labor-automation

I'm sure many of us have been looking for new roles over the past several years. The "how to find a job" searches all recommend using AI to do various things from searching, to customizing each resume and cover letter, to automatically applying for you. All well and good for the job hunter. I'm currently experiencing this from the other side of things. I am looking for a few software engineers. I spent time building out a job description, improving my team's interview cycle to account for AI tooling, and generally had high hopes to bring on a few new team members. But we had problems almost immediately. 1. The absolute volume of applications. In the first hour we had 231 candidates apply. Roughly 1/3 of those had a perfectly written resume and cover letter attached. 2. After narrowing it down through brute force and amazing work from my technical recruiting team, we started the interview cycle. Nothing unusual - and introduction to the hiring manager, a panel interview, and for the staff level roles a conversation with their immediate director and a peer team they'd work with daily. All used AI tooling to a degree, but some obviously depended on it for everything. Those interviews turned into "interviewing the LLM" 3. After we made decisions on who to extend offers to, we got ready to welcome the new team members. Within days of starting we suspected 1 wasn't who we actually talked to and within a month 2 more raised similar flags. In total 3 out of 7 of the newly onboarded members were terminated because they weren't who they said they were. All three passed background checks. That's the problem. We haven't come up with a solution yet. How are hiring managers and teams handling the ability of AI to mask what a person can do? How are you handling identity verification when someone can easily clone another person and have their LLM fabricate a convincing story?

What are your tips for using AI safely? I have created and tested plenty of custom Skills, Routines and custom Claude setups, but I'm really curious on what your practices are, on every level. How do you protect your data?

Let's get to know each other! Comment below sharing where you are in the world, a career goal you have, and something you like to do for fun. 😊

With how powerful Claude Code is, are we still building automations for clients using n8n, or is everything now being handled directly in Claude Code? What approach are you all taking?