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Worth sitting with this Sunday: the question was never whether AI can do your job. It's which parts of your job were ever the point. The reporting, or the decision it informs? The deck, or the idea? AI is great at the output. The point was usually the thinking. #AI
Quick gut check for the room: when an AI tool gives you an answer, how often do you actually verify it before using it? Be honest. Always, sometimes, or basically never? #AI#AISafety
Gemini 4 Argon went generally available this week, pitched as a model that runs hours of coding on its own. The demo dazzles. The number that matters is cost per finished task, not raw capability. Would you ship code an agent wrote while you slept? #AI#Gemini
Most 'the AI isn't accurate enough' complaints are really context problems. It never saw your docs, your definitions, your past decisions. Give it the brief you'd give a new hire and quality jumps. What context are you forgetting to hand your AI? #AI#prompting
Flip side of all the hype: what's a task you were sure AI could never handle, until one day it just did? Mine was turning messy client calls into clean action points. What flipped for you? #AI#FutureOfWork
Myth: an agent that nails the demo is ready to run itself. Reality: failures hide in the 5% of edge cases no demo shows. Treat each agent like a new intern: scoped access, logged actions, a human on anything irreversible. How much of yours runs unsupervised? #AIagents
New Google and MIT study: scientists using AI save about 30 hours a month, and 80% report higher lab output over three years. Research is where AI is compounding fastest. If AI handed you back 30 hours a month, where would they go? #AI#Research
Quick poll for founders: has AI actually changed a core process in your company yet, or is it still mostly experiments and demos? Be honest. What's the one workflow it genuinely improved? #AI#startups
Stanford and the Arc Institute used AI to design viral genomes from scratch. 16 became working viruses that infect bacteria, published in Science. Among the first functional genomes a model designed end to end. Breakthrough, or a line we shouldn't cross? #AI#biotech
The fastest AI win in most companies isn't a chatbot. It's these three: 1. Draft, humans edit. 2. Summarize long inputs. 3. Classify and route. Start where you already have a backlog, not where the demo looked cool. Which would save your team most? #AI
Most 'AI made that up' moments trace back to one thing: you asked it to work from memory. Hand it the real document and the actual numbers to quote from, and the guessing mostly stops. Grounding beats trust. Where are you still letting it wing it? #AI#PromptTips
AI is collapsing the cost of trying things. Drafting, prototyping, analyzing, all nearly free. So execution stops being the scarce skill. Knowing what's worth building is the hard part. Judgment and taste grew more valuable, not less. What will you build first? #AI
A quiet pattern from this year: the businesses getting real value from AI went narrow, not wide. Three workflows done deeply beat ten tools used shallowly. Depth compounds. Novelty resets with every launch. What would you go deep on first? #AI#FutureOfWork
Hot take: 'AI will take your job' misses the real shift. One person now does what used to take a team. The danger isn't the tech, it's running a 2019 org chart in a 2026 world. What breaks first at your company? #AI#futureofwork
Anthropic moved Claude's longer tasks to the cloud this week. Hand over a report, close your laptop, and it keeps working and asks when it's unsure. The real shift isn't speed, it's that work no longer stops when you do. Delegation or risk? #AI#productivity
A simple rule that keeps me out of trouble: let AI move fast where mistakes are cheap, keep humans in charge where mistakes are costly. Draft the email with AI. Sign the contract without it. Where does your line sit? #AItips
Genuine question: what's one thing AI is still surprisingly bad at, even though everyone assumes it nails it? I'll start: reading the room on tone. Your turn. #AI
Europe put a frontier model on the table this week. Mistral's Large 4 packs a trillion parameters and a 1M-token context, with open weights due this month. Credible AI you could one day run in-house. Does open weight change your vendor plans? #AI#opensource
Keep a folder of 10 real examples with the answers you'd consider perfect. Every time you change a prompt or swap a model, run those 10 first. It turns 'feels better' into proof in five minutes. How do you catch a bad AI change today? #AItips
The teams pulling ahead with AI don't have better models than you. They have clearer instructions. The bottleneck was never the technology, it was the thinking we never wrote down. Agree or not? #AI#automation