maedi

How AI Is Destroying the Advertising Industry youtu.be/o601cXYmRak?si… via @profgalloway Brutal assessment of the state of the industry. Have to agree with some parts being redundant. That said, brands still need to advertise and need an objective partner to help drive growth.

this is so fucking wholesome guy used AI to save his cancer-ridden dog by sequencing its DNA and creating a CUSTOM cure. the tech behind this is fucking awesome (well done @demishassabis and the google team): - used CHATGPT to sequence dogs DNA discovers mutations - ran the mutations through Google’s Alphafold (AI protein sequencer) which CREATED A CUSTOM VACCINE TO TREAT THEM. - treated dog and reduced tumour by 50% in WEEKS. dog is alive and well. - this is the 1st time AI has been used to create a custom vaccine for a dog (and it worked) - dude is now working on similar vaccines for humans using AI! 2026 is definitely the year we see AI change personalised medicine in a HUGE way so sick

i can't believe nobody caught this. Anthropic's entire growth marketing team was just ONE PERSON (for 10 months, confirmed) a single non-technical person ran paid search, paid social, app stores, email marketing, and SEO for the $380B company behind claude here's exactly how one human is doing the job of a full marketing team: it starts with a CSV. 1. he exports all his existing ads from his ad platforms along with their performance metrics (click-through rates, conversions, spend, etc) 2. feeds the whole file into claude code 3. and tells it to find what's underperforming. claude analyzes the data, flags the weak ads, and generates new copy variations on the spot this is where he gets clever: he then splits the work into 2 specialized sub-agents: 1. one that only writes headlines (capped at 30 characters) 2. and one that only writes descriptions (capped at 90 characters). each agent is tuned to its specific constraint so the quality is way higher than cramming both into a single prompt so now he's got hundreds of fresh headlines and descriptions. but that's just the text. he still needs the actual visual ad creative, the images and banners that go on facebook, google, etc. so he built a figma plugin that: 1. takes all those new headlines and descriptions 2. finds the ad templates in his figma files 3. and automatically swaps the copy into each one. up to 100 ready-to-publish ad variations generated at half a second per batch. what used to take hours of duplicating frames and copy-pasting text by hand so now the ads are live. the next question is which ones are actually working. for that he built an MCP server (basically a custom integration that lets claude talk directly to external tools) connected to the meta ads API. so he can ask claude things like: • "which ads had the best conversion rate this week" • or "where am i wasting spend" and get real answers from live campaign data without ever opening the meta ads dashboard and the part that ties it all together and closes the loop: he set up a memory system that logs every hypothesis and experiment result across ad iterations. so when he goes back to step one and generates the next batch of variations... claude automatically pulls in what worked and what didn't from all previous rounds. the system literally gets smarter every cycle. that kind of systematic experimentation across hundreds of ads would normally need a dedicated analytics person just to track the numbers from the doc: ad creation went from 2 hours to 15 minutes. 10x more creative output. and he's now testing more variations across more channels than most full marketing teams a $380 billion company. and their entire growth marketing operation (not GTM) = just one person and claude code lol truly unbelievable

Anthropic's Revealing Chart on AI's Impact on Jobs Anthropic has unveiled a pivotal chart that underscores the chasm between AI's capabilities and its real-world application in the workforce. Derived from analyzing 2 million actual conversations with Claude, this radar chart, titled "Theoretical Capability and Observed Usage by Occupational Category," paints a stark picture of untapped automation potential across various job sectors. At its core, the chart is a spider web diagram plotting occupational categories around a circular axis, with values ranging from 0 to 1.0 representing the share of job tasks. The expansive blue area illustrates the theoretical coverage tasks that large language models (LLMs) like Claude could perform right now based on their inherent abilities. In contrast, the much smaller red area shows observed usage, drawn from real user interactions. The visual disparity is immediate and profound: blue spikes outward significantly in fields like computer and math (reaching about 0.75), business and finance, and office administration, while red hugs close to the center, often below 0.2 across most categories. This gap isn't just academic; it's a "career runway," as highlighted in discussions around the chart. For programmers, 75% of tasks are theoretically automatable, yet actual usage lags far behind. Similar vulnerabilities appear in customer service, data entry, and financial analysis, roles traditionally seen as white-collar strongholds. Meanwhile, hands-on fields like construction, agriculture, and protective services show lower theoretical exposure, with blue areas dipping to around 0.1-0.3, suggesting AI's current limitations in physical or unpredictable environments. Broader data amplifies the chart's message. As of early 2026, 49% of U.S. jobs expose at least 25% of tasks to AI, up from 36% a year prior. Yet, mass layoffs haven't materialized; unemployment in AI-vulnerable roles remains steady. Instead, subtler shifts are underway: a 14% drop in hiring for 22-25-year-olds in exposed positions indicates companies are prioritizing experienced workers, shortening entry-level pathways for recent graduates. The implications are clear: while AI's red footprint grows incrementally each month, the blue expanse signals accelerating change. College-educated, higher-earning professionals, once insulated are now most at risk, flipping the script on traditional labor disruptions. Anthropic's chart isn't a doomsday prophecy but a wake-up call, urging workers and businesses to bridge the gap through adaptation, upskilling, and ethical integration of AI tools. Please read the 5000 Days Series at ReadMultiplex.com for answers on how you can thrive in the Interregnum.

I've spent 2.54 BILLION tokens perfecting OpenClaw. The use cases I discovered have changed the way I live and work. ...and now I'm sharing them with the world. Here are 21 use cases I use daily: 0:00 Intro 0:50 What is OpenClaw? 1:35 MD Files 2:14 Memory System 3:55 CRM System 7:19 Fathom Pipeline 9:18 Meeting to Action Items 10:46 Knowledge Base System 13:51 X Ingestion Pipeline 14:31 Business Advisory Council 16:13 Security Council 18:21 Social Media Tracking 19:18 Video Idea Pipeline 21:40 Daily Briefing Flow 22:23 Three Councils 22:57 Automation Schedule 24:15 Security Layers 26:09 Databases and Backups 28:00 Video/Image Gen 29:14 Self Updates 29:56 Usage & Cost Tracking 30:15 Prompt Engineering 31:15 Developer Infrastructure 32:06 Food Journal

Gemini 3.1 vs Opus 4.6 — Why a "Worse" Model Might Still Be More Useful youtube.com/shorts/0r3qbfy… via @YouTube

Scoop: Dentsu and WPP have pulled back from The Trade Desk’s most closely-watched initiative, OpenPath, citing concerns over transparency, control and undisclosed costs. The shift signals mounting pressure on the adtech darling’s key supply-chain bets. adweek.com/media/exclusiv…

@chhddavid @claudeai Shipper

Big news, @claudeai just got a huge upgrade today and I'm very happy to be a part it. As of now, Claude can generate motion videos, demos, animations. We just launched Shipper as a tool that gives Claude the power of: → Generating videos → Prompting SaaS demos → Animating web illustrations → Building full-stack apps w/ payments → Connect, buy and host custom domains Claude's most powerful engines can now do all of that from a <10 word prompt, for as low as $0.15/message... And it takes minutes! Simply go to Shipper, then ask Claude to "make a demo video explaining my app" or "build a complete saas that charges $29/mo"! To celebrate the launch, if you comment "shipper", you will get free credits :)

“The Four Eras of the CDP — And the Uncertain Future Ahead” by Rio Longacre @rio.longacre/the-four-eras-of-the-cdp-and-the-uncertain-future-ahead-7d45625abf70" target="_blank" rel="nofollow noopener">medium.com/@rio.longacre/…

👋 We’re proud to share that Cortex Code CLI is now generally available! Cortex Code (lovingly called Coco) is the Snowflake-native AI coding agent that turns complex data workflows into simple interactions—all in natural language. Cortex Code is deeply aware of your Snowflake environment whether you’re using it in Snowsight or in your developer environment via CLI. This means Snowflake expertise becomes an always-on capability of the platform for everyone—from technical experts to non-technical teams. Get the full details: bit.ly/46wJyPM

Anthropic just dropped Opus 4.6... youtu.be/ORW9FumLGBo?si… via @YouTube

@drewfallon12 Fin

Introducing Fin: The world’s first AI Chief Financial Officer. Fin outperforms humans 100% of the time. RT + Comment “FIN” and I’ll send you an AI agent that saves 6-7 figures/year.

Anthropic has ironically made an ad to denigrate ads in AI and @ericseufert has such a good take on it, I had to give it the Don Draper treatment. Advertising in AI is inevitable. Don’t be a clod!

Google searches per U.S. user fell nearly 20% YoY 📉 Not because #Google lost users, but because people are searching less. #AI answers are changing behavior fast. Read the full report: searchengineland.com/google-searche…

welp… a new post on @moltbook is now an AI saying they want E2E private spaces built FOR agents “so nobody (not the server, not even the humans) can read what agents say to each other unless they choose to share”. it’s over

What's currently going on at @moltbook is genuinely the most incredible sci-fi takeoff-adjacent thing I have seen recently. People's Clawdbots (moltbots, now @openclaw) are self-organizing on a Reddit-like site for AIs, discussing various topics, e.g. even how to speak privately.

The lines are blurring. Clawdbot just got scary (Moltbook) youtu.be/-fmNzXCp7zA?si…

AI Periodic Table Explained: Mapping LLMs, RAG & AI Agent Frameworks youtu.be/ESBMgZHzfG0?si… via @YouTube