0:00 AI models "substantially smarter than almost all humans at almost all tasks" are on track for 2026 or 2027.0:07 That’s the claim from a thread by user ForsloffLk that landed just thirteen hours ago, and it's re-framing the entire conversation.0:15 Yesterday we were talking about personal AI going mainstream...0:19 today the debate just rocketed past 'personal' and straight into 'post-human' territory.0:25 This isn't a forecast for 2030 anymore.0:28 This is a prediction for NEXT year.0:30 So, the platform is vibrating with this idea of imminent, powerful intelligence.0:35 But that's just the lead.0:37 Here’s what else is moving today, July fifteenth, 2026.0:40 First, the practical counterpoint to that massive prediction.0:44 A user named Dami-Defi just dropped what they’re calling "THE BEST AI AUTOMATION STACK TO LEARN IN 2026." The core message is simple: stop chasing shiny new AI wrappers.0:56 The real value, the real money, is in building reliable, scalable production systems.1:01 It’s a full-stack blueprint, and it’s getting massive traction from engineers who are tired of the hype.1:08 We’re going to break that down.1:10 Next, the economic angle.1:12 A thread from ChainMinded is connecting the dots between three huge forces: AI, what they call "agentic payments," and the blockchain.1:20 Their argument is that this convergence isn't just another tech trend.1:25 It's a fundamental rewiring of how value moves across the entire global economy.1:30 Think AI agents, with their own wallets, executing transactions on-chain.1:35 It’s a big idea about where the money flows next.1:38 Then there's the meta-conversation.1:41 Joe Weisenthal highlighted a post from Zvi Mowshowitz about how to navigate Twitter's own algorithms right now.1:48 As the platform's feed changes, the strategies for finding signal in the noise have to change, too.1:54 It’s a reminder that the very ground we're standing on is shifting, and the power users are the first to map the new landscape.2:03 You're not just imagining it...2:05 your feed IS different, and here's how people are adapting.2:09 And finally, a dose of reality.2:11 A thread is making the rounds showing fresh workplace data for this month, for July 2026.2:17 It claims companies are hitting a massive wall with AI adoption.2:21 And here’s the turn.2:22 It's not because the technology is failing.2:25 It's because employees are quietly resisting or struggling to integrate these new tools into their workflows.2:32 So while the tech world talks about superintelligence, the corporate world is stuck on step one.2:38 That friction is a story in itself.2:41 So what does it all add up to?2:43 You have this top layer of conversation about god-like AI arriving next year.2:48 And right underneath it, a much more grounded, much more practical conversation about the plumbing required to make ANY of it work, and the human barriers slowing it all down.2:59 Okay, let's go deep on the two threads that define this moment.3:03 The prediction, and the blueprint.3:06 First, that prediction from ForsloffLk.3:08 Let’s be very, very clear about what’s being said.3:11 The quote is "substantially smarter than ALMOST ALL humans at ALMOST ALL tasks." This is not the old, tired debate about Artificial General Intelligence, or AGI.3:22 This isn't about a machine having a soul or consciousness.3:26 That's a distraction.3:27 This is a capabilities forecast.3:29 It's a claim about performance.3:31 That by 2026, or 2027 at the latest, you will be able to prompt an AI and get a result that is better than what 99 percent of human experts in that field could produce.3:42 Legal analysis.3:43 Financial modeling.3:45 Code generation.3:46 Scientific research.3:47 Strategic planning.3:48 The claim is that across nearly every white-collar domain, the AI will outperform the human.3:54 Now, for years, the pushback was always "sure, but it can't be creative," or "it can't have true understanding." This thread argues that distinction is about to become meaningless.4:06 When a model can synthesize all existing knowledge and generate novel, effective solutions at a superhuman level...4:14 whether it "understands" in the human sense is an academic question.4:18 The practical reality is that it solves the problem.4:21 It wins the contract.4:23 It finds the cure.4:24 And the timeline is the weapon here.4:26 2026.4:27 Not 2035.4:27 That means the strategic plans you are making for your career, for your business, for your investments...4:34 they might be based on a foundational assumption about human cognitive superiority that is set to expire in the next 18 months.4:43 That is the earthquake happening on Twitter today.4:46 It forces a question on you: what is your plan for when your smartest employee is a piece of software?4:53 So, with that chilling, stratospheric idea hanging in the air...4:57 let's get our feet back on the ground with the second major thread of the day.5:02 Because it’s the perfect antidote.5:04 It’s the HOW.5:05 User Dami-Defi posted a thread titled: "THIS IS THE BEST AI AUTOMATION STACK TO LEARN IN 2026." And it is the most practical, no-nonsense guide to actually building with this stuff that I’ve seen in months.5:19 The core argument is a direct attack on what they call "chasing random AI tools." They say the highest-value skill is NOT being a prompt engineer or a GPT-wrapper expert.5:30 The highest-value skill is being able to build a full, production-grade system that USES AI to deliver a business outcome.5:38 Businesses don't pay for "AI tools," the thread says.5:41 They pay to save time, cut costs, reduce errors, and ship reliable software.5:46 The AI is just one part of that.5:48 So here is the stack they lay out.5:51 The five layers.5:52 Layer one: Backend.5:53 They say learn Python, FastAPI, and Celery.5:56 Why?5:56 Because this combination lets you build a clean, scalable server that can handle web requests, but also manage background jobs and scheduled tasks.6:06 This is the engine room.6:07 Layer two: Database.6:08 The recommendation is Postgres, which is the rock-solid industry standard.6:13 But the key is putting Supabase on top of it.6:16 This simplifies everything—storage, user authentication, administration.6:21 It makes the database accessible and manageable.6:24 Layer three: Frontend.6:26 This is what the user sees.6:27 The stack here is React, Vite, and a UI library called shadcn/ui.6:32 This trio is all about speed and efficiency for building dashboards, admin panels, and internal tools.6:38 It’s about getting a functional interface up and running fast.6:42 Layer four: The AI Models themselves.6:45 And here, they don't pick one winner.6:47 They say OpenAI, Anthropic, Azure, AWS, GCP...6:50 use the best tool for the job.6:52 LLMs, embeddings, vision, speech.6:54 The point is, the model is a component you plug IN.6:58 It's not the whole product.7:00 And finally, Layer five: Deployment.7:02 How you ship it.7:03 Docker to package it all up, and then a platform like Railway or a classic Virtual Private Server setup.7:10 This is what takes your project from your laptop to the real world and keeps it running.7:16 Now, why does this specific stack matter?7:18 Because it represents a philosophy.7:21 It’s about moving past the magic show of AI demos and into the hard, unglamorous work of engineering.7:27 Each piece of that stack is chosen for reliability and scalability.7:32 It’s the infrastructure for the AI revolution.7:35 So you see the connection, right?7:37 ForsloffLk is describing this unbelievable explosion in cognitive power.7:42 This tidal wave of intelligence.7:44 And Dami-Defi is handing you the blueprint for building the channels and reservoirs to actually control and direct that power.7:52 One without the other is incomplete.7:54 The prediction alone is just science fiction.7:57 The blueprint alone is just code.7:59 Together...8:00 they describe the work that actually matters right now.8:04 The smartest people on the platform today are not the ones just tweeting "wow, AGI is coming." They are the ones quietly mastering this stack.8:13 They are building the systems that will harness that intelligence.8:17 They are preparing for 2026, not just talking about it.8:21 So as we close out the day, the picture is sharp.8:24 The conversation has split.8:26 On one side, you have a profound, almost terrifying, forecast about the imminent arrival of superhuman AI capabilities.8:34 It’s no longer a fringe idea; it’s a dated prediction landing in the heart of the tech conversation.8:40 It changes the strategic calculus for everyone.8:43 But on the other side, there's this deeply practical, almost gritty focus on the "how." On the engineering discipline required to build anything of value.8:54 It's a rejection of hype.8:55 It's a call to learn the full stack, to understand the plumbing, to focus on delivering outcomes, not just demos.9:03 This is the immune response of the builder community to the hype cycle.9:07 This week sets up a fundamental choice for you.9:10 Are you watching the spectacle, or are you learning the stack?9:14 Because the platform is telling us, in no uncertain terms, that the window to just watch is closing.9:21 The future isn't being built by the people retweeting predictions.9:25 It's being built by the people who know how to deploy a Docker container running a FastAPI backend connected to a Postgres database.9:34 The hype is over.9:35 The build has begun.
