Hi everyone, here is my deliverable for the Day 4 challenge: an automation for Real State Business. Because I have been already working with Make, I used this tool instead of trigger.dev. Feel free to ask for the Make scenario, of course its completely free!!! The flow automates the full property quotation process for a real estate business: the agent fills out a Google Form with the property data and three market comparables, and Make takes it from there. Claude generates the analysis — SWOT, sales strategy, price justification and average $/m² from the comparables — which gets merged into a Google Docs template along with an embedded map of the property, converted to PDF, and dropped as a Gmail draft ready to send. I think the two design decisions that matter: the email stays as a draft, not an auto-send — the agent reviews and hits send, so there's always human control over what reaches the client. And AI only does the reasoning; the document assembly and delivery are deterministic. What used to take 1–2 hours now happens in about 2 minutes. Have a nice Sunday !!!

Hi guys! Just dropping the newsletter and the WhatsApp image that I created for the first build in AIS. Context: my dad has a little restaurant in Buenos Aires, and I used this to help him with some ideas while completing the AI tasks at the same time. PS: Sorry for the Spanish, but you are more than welcome to come around if you ever visit Buenos Aires. I promise: best pizzas, milanesas and empanadas ever!!!! Have a nice Friday!

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?

AI can write messages. AI can find leads. AI can automate follow ups. But it still can't replace genuine conversations. The biggest improvement I've made in outbound wasn't a new tool it was changing how I approached people. Instead of trying to sell in the first message, I started focusing on understanding: - What they're building - What challenges they're facing - What they're currently focused on The quality of conversations improved, and so did the number of meetings. AI helps me save time. Relationships are still built by humans. 𝗪𝗵𝗮𝘁'𝘀 𝗼𝗻𝗲 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘆𝗼𝘂𝗿 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝘁𝗵𝗮𝘁 𝗔𝗜 𝗵𝗮𝘀 𝗴𝗲𝗻𝘂𝗶𝗻𝗲𝗹𝘆 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗱?