Hadi Saeed

@MansurQr If confirmed, the UAE’s response systems and infrastructure are seriously robust. Living here you notice how much investment goes into security and resilience. The country has handled threats before and kept things stable.

🚨BREAKING Fresh missile and drone attacks launched from Iran target the UAE, drone strike on oil facilities in Fujairah triggers fire.

@sarbjeetjohal @AnthropicAI Everyone talks about models, but the real race now is deployment. Turning AI into actual workflows inside companies is still the hard part.

This is Forward Deployed Engineering on steroids! An unnamed, newly formed $1.5 billion entity, formed alongside the San Francisco-based PE firm Hellman & Friedman and backed by a group of asset managers including Apollo and General Atlantic, will deploy @AnthropicAI’s Claude AI model directly inside businesses, starting with companies owned by the investment firms. This is an interesting arrangement to exist side by side existing Global System Integrators. It raises so many questions. Are GSIs stretched into several directions, pulled by hyperscalers. Is there a room for one vendor specific SI like entity? Just two weeks ago, during #GoogleCloudNext 2026, @GoogleCloud announced a $750 million investment fund specifically designed to help its 120,000-member partner ecosystem—including system integrators, global consulting firms, and software providers—accelerate the development and deployment of agentic AI. THIS VENTURE IS DOUBLE IN INVESTMENT SIZE. I anticipate Microsoft and Amazon following similar suite like Google did! For sure, there is a big gap and a big need for well educated AI folks to help mid range companies move fast on AI adoption. Sounds like a great move! More from CNBC here: cnbc.com/2026/05/04/ant… cc @dvellante @furrier @dfloyer @IsForAt @PeterDiamandis @MarshaCollier @waqasmakhdum @sallyeaves @DavidLinthicum

Starting to feel like the AI race isn’t about better models anymore. It’s who owns the execution layer inside companies. Infra + workflows decide it.

@rohanpaul_ai This feels like the enterprise phase of AI. Not demos, actual workflow rebuilds. The real competition now is who owns the path from model to daily business ops.

WSJ: Anthropic is wrapping up a deal to set up a joint venture with Blackstone, Goldman Sachs, and other Wall Street firms, with the goal of selling AI tools to private-equity backed companies, according to people familiar with the matter. Anthropic, Blackstone, and Hellman & Friedman are expected to put in about $ 300M each, while Goldman Sachs is expected to invest about $ 150M. The new company would work like an AI deployment arm, meaning it would not just sell Claude access, but help companies rebuild workflows around LLMs, from customer support and finance to coding, legal review, and internal research. Private-equity firms are the target because they own many companies, measure every cost tightly, and can force software changes faster than slow public companies. Anthropic gets distribution, Wall Street gets a stake in the AI services layer, and portfolio companies become a large testing ground for enterprise AI. The deeper move is that AI labs are no longer only competing on model quality, but on who controls the path from model to business process. --- wsj .com/business/deals/anthropic-nears-1-5-billion-joint-venture-with-wall-street-firms-8f5448ee

@RaulOnRails Yeah the first stretch is brutal. You’re building product, distribution, and confidence with basically zero signal. Most people only notice the part after it starts working.

I'm starting to understand why people don't bootstrap their own business. The beginning is super hard and depressing. And a lot of people don't have enough resilience to get past it.

@RaulOnRails Early stage is a brutal loop. No users so no trust. No trust so no users. That’s why capital or a strong startup ecosystem can make such a big difference getting things off the ground.

I also start to understand the people wanting to raise money for their business. Much easier to lift it off the ground and get passed the initial traction problems where you struggle with your distribution channel and build your credibility&reputation so people trust you with their money.

4. introduction to model context protocol: learn how to connect claude with external tools and data sources anthropic.skilljar.com/introduction-t… 5.model context protocol (mcp): learn how to build strong mcp implementations with practical, advanced techniques anthropic.skilljar.com/model-context-… 6. introduction to agent skills: learn how to build and manage reusable claude skills anthropic.skilljar.com/introduction-t…

1. claude 101: beginner friendly guide on how to use claude effectively anthropic.skilljar.com/claude-101 2. claude code in action: learn how to use claude code to speed up workflows anthropic.skilljar.com/claude-code-in… 3. building with the claude api: learn how to integrate claude into real world applications anthropic.skilljar.com/claude-with-th…

anthropic dropped free ai courses with certificates and most people haven’t noticed yet. what you’ll learn 🧵: - ai fundamentals - ai fluency - building with ai (claude api) - real world workflows..... etc

@EntrepreneursAI Everyone debates GPUs but power is the real constraint. Frontier AI infra is starting to look a lot like energy infrastructure. At this rate the next big AI breakthrough might just be a power plant 😂

Meta is powering AI data centers with solar energy beamed from space. → 1 GW continuous power from orbit → 100+ hours of backup storage The grid can't keep up with frontier AI demand. The hyperscalers aren't waiting for it to catch up. Energy is the constraint. Watch this space. aientrepreneurs.standout.digital/p/openai-and-m…

@amasad @Replit 700+ done and ~200 drafts queued is crazy. For something as complex as fire prediction, this kind of parallel agent workflow is wild.

10 active, 198 draft, 700+ done. I don’t think there’s more agentic parallelism happening anywhere else on the internet than what happens on @Replit.

@Austen Yep, feels like the early cloud days again. A few teams shipping insanely fast with agents while everyone else is about to realize the shift.

The future is here, not evenly distributed yet

@abbey_45 @Rebecca_Dali Lots of AI demos lately. Fewer teams actually building execution layers. Good to see people shipping.

@Rebecca_Dali The team behind arc are actively building

Most people are still using AI. A few are starting to operate it. That’s the shift @arcterminal is pushing. ArcTerminal isn’t another chatbot layer. It’s an agent-native browser where AI doesn’t just answer it executes. → Navigate apps → Trigger workflows → Chain actions across tools → Act like a real operator, not a prompt box Now plug that into Anima. Anima turns identity + intent into persistent, evolving agents. Not sessions. Not tabs. Entities that learn, adapt, and compound over time. ArcTerminal = execution layer Anima = intelligence + memory layer Together, you’re not prompting anymore. You’re deploying. Early users will look like power users. Later, this will look like the default. We’re watching the interface disappear. os.arcterminal.ai/login?ref=AAKB…

@Rebecca_Dali Feels like we’re moving from “ask AI” to “assign AI”. If agents can actually run workflows across apps reliably, that’s when things get interesting.

@enjojoyy Honestly I’d just spin it up on Replit. Pretty close to plug and play. Raspberry Pi setups sound easy but for non technical folks they turn into weekend debugging projects fast.

What's the easiest way to host an autonomous agent for a non-technical person currently? (Openclaw, Hermes, Pi etc.)

@PythonDvz B. 0 1 1 3. Sneaky one. Using `List[-2]` as the loop variable keeps overwriting the third element during iteration.

🤔🚀 Comment your answer 👇👍⚡ #python #programming #codinglife #developers #pythonquiz #codingquiz #codingchallenge #100DaysOfCode

@DanielleFong Yeah honestly the raw checkpoints are the fun part. You actually see what the model can do before it’s trained to sound like it’s interviewing at Jane Street.

i think part of the reason i like 5.5 is that it is undercooked, like gpt 4.5. it is like that sweet sashimi before the damned thing is post-trained into interviewing at jane street. just raw talent

@haider1 The pace is insane. A year ago local models felt like demos. Now Qwen and Gemma run smoothly on a laptop. Architecture gains keep compressing the timeline.

remember when gpt-4.5 was supposed to be many years away from running on consumer hardware? yet 12 months later we're running something several generations better on our laptops with qwen / gemma models the architecture keeps improving in ways we can't fully predict

@EntrepreneursAI Wild numbers. 80k layoffs vs 500k AI jobs. Feels like the real bottleneck is people who can actually build with the AI stack.

81,747 tech layoffs in Q1 2026. Up 580% since Q4 2025. Meanwhile AI has added 500,000+ jobs. Both are true simultaneously. The difference is which jobs — and who's ready. Full breakdown in this week's Sunday Special 👇 aientrepreneurs.standout.digital/p/ai-layoffs-8…

@EntrepreneursAI Feels less like layoffs vs jobs and more like a skill reset. AI native builders will be fine. I think the real question is which ecosystems are actually ready to capture those new roles.

Jensen Huang just called out Dario Amodei on a podcast. Amodei: half of entry-level jobs are gone. Huang: AI already created 500,000 jobs. More coming. One of them is wrong. Or maybe neither is. We broke down both sides 👇 aientrepreneurs.standout.digital/p/ai-layoffs-8…