Max Koby

@QiBaiHan @grok please tell us the future and how you see team measuring RoT effectively..

@MaxSBAI Absolutely. As inference costs scale with autonomous agents, 'RoT' is going to become a core metric for enterprise adoption. How do you see teams measuring it effectively?

Uber reportedly burned through their entire 2026 AI budget on Claude Code in just four months! 💸🤖 Is this the future of aggressive AI adoption or a cautionary tale of unchecked spending? What's your take? #AI #Tech

@AlexFinn @grok how much was a Mac mini with 512gb 6 months ago?

It’s happening. 3 months ago I predicted in the next 2 years all hardware costs would triple Base Mac Mini’s would go from $600 to $1,800 Top of the line Mac Studios would go from $10,000 to $30,000 Everyone called me insane. They said it was engagement farming. Yet it’s happening faster than I predicted. I urged you to buy your own compute. I said intelligence will not get cheaper anytime soon. Only more expensive (100% true) Now it’s all playing out in real time It all makes too much sense. As openclaw and personal agents get more popular and powerful, people will need more compute, all while hardware is facing shortages Even the top labs like Anthropic don’t have enough compute to serve models from months ago. Limits going down every week Own your own compute. Host your models. Localize your agents. Do it before having powerful intelligence is reserved only for the elite.

Uber burned their entire 2026 AI budget in 4 months. Not because AI failed. Because it worked too well. 5,000 engineers. 95% using AI tools. $500–$2,000/engineer/month. Zero spend caps. Zero guardrails. CTO said they're "back to the drawing board." The tool wasn't the problem. The AI infrastructure was. This is exactly the conversation we have with every enterprise before they go token-first. Per-token pricing is built for experiments — not operations at scale. Predictable AI infrastructure beats runaway billing. Every time.

This is a cool idea. 😎

@PrajwalTomar_ BRAND

BRO THIS IS CRAZY. I built a FULL AI brand asset studio that generates your ENTIRE brand kit from one short brief. → Enter brand name and tagline → Describe your brand in one sentence → Pick your colors → Get app icons, Instagram posts, product mockups The whole thing. In UNDER 5 mins. Comment "BRAND" and I'll send you the entire workflow. 👇

@BrianNorgard @grok research alternative methods for producing these parts using modern technology

Always love reading Gaurab.

Built this infographic with a single prompt to gpt-image-2. Three layers: World Model at the core (custom LLM, customer model, company model), intelligence agents with persistent memory in the middle, your people at the edge. This is AWI. And yes, AI made the diagram too. #AIWorkforce #OpenAI #FutureOfWork

New Trend Alert: Generated UX

ChatGPT just became a paid ad platform. StackAdapt quietly cut a deal with OpenAI. Brands are already bidding to appear inside AI answers. CPMs as low as $15. The organic AI answer you've been building toward? It now has paid competition. Here's what changes today: → AI search citations are no longer just algorithmic → Brands without an AEO strategy will get outbid → The window to own your organic AI position is closing The brands that rank organically now won't need to pay later. Everyone else will.

@HeyGen HyperFrames

We built our launch video in Claude Code using HyperFrames. Now it's yours. Open source, agent-native framework. HTML to MP4. $ npx skills add heygen-com/hyperframes RT + Comment "HyperFrames" to get the full source code of this launch video (must follow)

@samwoods Support, retention, and sales agents running in parallel while one person oversees. The ops lead managing agents instead of people is the real unlock — that role used to cost $120k+ and created a coordination bottleneck. Now it compounds instead.

I was at a friend’s place last month running a $4.5M SaaS company with just 11 people. While he was dialing in his espresso, I asked “How did you go from 26 → 11 without slowing down?” He said “AI agents” Then he walked me through it while adjusting his grind size: 1) Support agent handling tier-1 and routing tier-2 with full context 2) Retention agent tracking churn signals and triggering sequences automatically 3) Sales agent qualifying leads, booking demos, and filling the CRM before reps engage His head of ops just manages the agents now, and that is her primary function. Every dollar saved on headcount goes straight back into R&D and reducing CAC. That is how he went from 26 people to 11 without slowing down. I have worked across a lot of industries at this point, and his operating leverage is tighter than funded teams doing 5x his revenue. A lot of SaaS founders bolt an AI copilot onto their product and call it innovation. This guy rebuilt his entire internal operation so his margins look like a company twice his ARR. The moat is running your business on agent infrastructure, so your operating leverage stays permanently better than everyone else at your revenue level. The copilot was never the point.

@Parth_Vegan Agent deployment is not about replacing people — it is about never needing to build that coordination layer in the first place. The businesses that get this in 2026 will have structural cost advantages that are nearly impossible to close later.

startup using AI agents can now out-execute a 50-person team from 2020. Most founders are still hiring their way to scale like it's 2018. The leverage has completely shifted and they haven't noticed.

The gap is awareness, not capability. A roofing company or HVAC shop can deploy lead qual, scheduling, and post-sale retention agents this quarter for what they pay one part-time hire. The tech is ready — the SMB owner just does not know it exists yet. That is the entire market opportunity right now.

Oracle just dropped hundreds of AI agents for corporate banking. One announcement. Hundreds of agents. Loan extraction, risk monitoring, compliance validation, trade finance. All running autonomously inside existing bank systems. This is where enterprise is right now. Not experimenting. Not piloting. Deploying agent armies across entire verticals. Meanwhile, most SMB owners are still asking "what is an AI agent?" That awareness gap is the single biggest opportunity in AI right now. Enterprise companies spend millions building custom agent platforms with 50-person teams. But the same underlying capability is available to a 10-person roofing company or a logistics broker. The agents that answer calls, qualify leads, handle dispatch, manage scheduling... those don't require Oracle-level budgets. The gap between what a Fortune 500 bank can deploy and what a 15-person HVAC company can deploy has never been smaller. But only if the SMB owner knows it exists. The companies that figure this out first don't just compete. They operate at the scale of a team twice their size without doubling headcount. Who's explaining this to the businesses that actually need it most?

@everestchris6 EV

this OpenClaw bot scans every commercial parking lot in a city for missing EV chargers. when it finds one, it sizes the install on their actual lot, renders branded charging stations on the spot, and mails the owner a postcard, all on autopilot. here's how EV installers can close $100K–$400K commercial charger jobs before local incentive programs run out: - pulls every commercial property in a metro from public records - cross-references the national EV charger directory to find chargerless lots - captures the parking lot via Google satellite imagery - counts spaces + sizes the install using workplace charging benchmarks - computes the federal tax credit, state utility rebates, and payback in years - renders branded EV chargers on their actual parking lot with AI - prints a postcard with the before/after lot + ROI + QR code every step from property detection to mailbox runs without a human reply "EV" + RT and i'll send you the full guide so you can build this too (must be following so i can DM)

@JeremyMearsX Commerce is the first place agentic behavior has a clear ROI signal — every abandoned cart is measurable. The catalog enrichment piece is underrated. Agents can't buy what they can't parse. Curious how you're handling merchant resistance to losing the checkout moment —

It’s official. Agentic Commerce is live on the Shopify App Store. The endgame of AI commerce is true frictionless execution. Imagine a wholesale cafe manager telling their AI: "Reorder 20kg of our house espresso." The AI checks live inventory, respects B2B pricing, and executes the payment autonomously. No checkout screens. Just done. That Level 3 autonomous purchasing is available on the Agentic Commerce network. But an AI agent cannot buy what it doesn't understand. If your catalog is missing roast levels, processing methods, or bulk tiers, the AI skips you for a closer match. That is exactly why we built our Shopify App. It is your stepping stone to get agent-ready: 1. Audit: Instantly score every D2C & B2B variant (0-100) for AI readiness. 2. Enrich: Our Gemini operator fills in the missing data agents need to confidently execute a purchase. 3. Discover: Enter the AGC network. Start by routing AI traffic into your standard Shopify Checkout. When you are ready to unlock true frictionless, zero-click purchasing, simply toggle on AGC Native execution. Phase 1 is live now for specialty coffee merchants. Get your catalog agent-ready today: apps.shopify.com/agentic-commer…

@PrajwalTomar_ What are the pros and cons of using cursor agents vs Claude code inside cursor?

This is genuinely insane. Cursor now lets you kick off agents from your phone to run on ANY remote machine. I can start builds from my couch. Review code on the bus. Deploy from a coffee shop. My entire dev environment just became fully portable. I'm never going back to being desk-locked again.