I was in Cambridge yesterday and can confirm very loud boom!

this is why you can't just automate your <insert business function here> by downloading workflows from the internet or asking Claude Code to just build something you know nothing about - critical thinking, human judgement and expertise are still very much needed.

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

I spent 1 1/2 hours yesterday with a client recording a webinar (not including prep and post processing work) and I found myself reevaluating @HeyGen and @ElevenLabs at the end of the day. Wondering how commonly these tools are being used for tech B2B marketing?

I’ve locked in 50 B2B influencers over the next 3 weeks to promote GojiberryAI. So far, the results are looking very strong. Next step: I’ll use our own software to run warm outreach, reaching out with ultra-personalized messages based on what they do and real buying signals. If you want the full list of 200 B2B influencers I’ve curated, share this post and comment “LIST”. I’ll send it straight to your inbox.

Andrej Karpathy: "90% of your AI coding bill is paying for context you didn't need to send" Here are 10 things senior AI engineers stopped wasting tokens on: 1. Auto-context loading 50 files for a 30-line fix: $1.20/turn for tokens you'll never read. 80% input waste, every session 2. Running Opus on lint, format, and rename tasks: $0.60 for what Haiku nails at $0.02. 30x overpay on the cleanup tier 3. Tool call loops that re-send the full repo on every retry: 5x context cost per agentic flow. fixing these alone cuts 30-50% of bills 4. Sonnet as the default model: Kimi 2.6 matches its quality on most coding tasks at 1/6 the cost. defaulting to Sonnet in 2026 is leaving 60-70% on the table 5. Streaming responses on stable-prefix workflows: kills your prompt cache. you pay 10x for tokens that should have cost cents 6. "Just in case" file includes: 80,000-token prompts that should be 3,000. context bloat is the silent budget killer 7. Per-session knowledge rebuilding: 10 min writing a SKILL.md once vs paying agents to re-figure out your environment every run. $4 vs $0.30 per execution 8. Single-model setups: premium tier on every task is the most expensive mistake in AI coding right now 9. Asking 10 small questions one at a time: 10 separate input prefix charges vs one batched call. 70-90% savings on routine workflows 10. Buying Claude Pro ChatGPT Plus Cursor Pro: you seriously use one. the other two are habit, not utility what actually compounds instead: - context discipline (grep before fetching, always) - prompt caching on every stable prefix - multi-model routing (Kimi 2.6 default, Opus for the 10%) - graduated skills via SKILL.md files - profiling tool calls before optimizing prompts - the routing mindset (right model for right task) in 12 months, the gap between developers shipping on $200/month and $4,000/month budgets won't be skill it'll be how well they route study this.

I've come to the conclusion (or maybe frustration is a better word) that AI is not yet good at making professional branded presentations (ppt, google slides). Please change my mind if you have a workflow that works!

In less than a year, we managed to get more than 13M organic views on Reddit. It brought over 100,000 people to our website without spending a cent. We put together a Reddit Strategy Playbook that gets me 1M organic impressions/month… and makes my posts show up consistently inside AI outputs (ChatGPT, Gemini, etc.). Here’s what’s inside the playbook: 😈 How We grow my SAAS gojiberryAI with Reddit 🔥 The 3 1 post formats that always go viral 🚫 How to get traffic from 100 subs → without getting banned 🔎 Our Reddit SEO method to rank in AI-generated answers ⚡ The automation flows we use to convert views into demos 🏴‍☠️ A little bonus just for you Want the full 1M Views/Month Reddit Strategy (100% Organic)? Here’s how to get it: ✅ Repost this post ✅ Comment “REDDIT” I’ll send it straight to you.

hmmm is Claude.ai is down or is it me?

You must try this. GPT Image-2 can do PALM reading and I’m so here for it. Full prompt below ⤵️

yeah, that agent was reckless (and sassy!), and Railway's design was that friend giving your drunk friend the shots. note to self: backup my Railway. but not in Railway.

9 out of 10! wow.

2012: "i'd love to try this random app, but i'm nervous about giving it access to my friends list on Facebook" 2026: "i'd love to try this random app, of course i'll give it access to read all text on all screens on my computer and upload it to a third party LLM company"

5.5 hour drive back home from a board game convention. passenger seat. my phone. built: •6 brand voice files •n8n automation pipeline •4 notion databases •human approval workflow •blotato publishing workflow Built with my favorite coworker Claude 🤩

ok but why is nobody talking about AI as an ADHD tool?? i get a random idea mid-task, hand it to Claude, go back to what i was doing. come back later and it's half-built. my brain has never had someone that could keep up with it never mind doing more than I even considered 🤯

counterintuitive take: a well-curated human guide will teach you AI skills faster than asking claude/chatgpt to teach you. the prompt is only as good as your mental model. (check their free stuff first tho - lots of fluff out there) 😏

has anyone been able to get dispatch to work on Claude cowork with a Mac mini? I won’t wanna waste my time trying again if it isn’t working. if yes, how are you using it?