Hey {{first_name | there}},

Yep, an open-source AI assistant is suddenly all over X, Reddit, and dev circles. So I went down the rabbit hole to see what the hype was about.

At the same time, Google is out here closing AI deals like crazy.

Claude is turning into a work hub, and companies are being pushed to prove AI is actually making them money.

There is a clear shift happening.

Let’s get into all of that. But first, here are some tool recs for today:

Clawdbot is an open-source, self-hosted AI assistant you run on your own computer.

You talk to it through apps you already use like Slack, Telegram, Discord, or WhatsApp/iMessage, but instead of just replying with text, it can actually take action for you.

It can manage your emails and calendar, send you reminders, summarize meetings, organize files, browse the web for you, and even run commands on your computer. 

Some people are using it to monitor servers or control smart home devices. You are not just asking questions. You are giving it ongoing responsibilities.

That is why people are calling it the closest thing yet to a real “Jarvis” style assistant.

The hype is real too. The project has racked up tens of thousands of GitHub stars in a short time, and social feeds are full of screenshots of people showing off their setups and the tasks they have automated. 

That’s also where the risk comes in.

Giving an AI deep access to your system means it can read files, run commands, and interact with apps. Even the creator says there is no perfectly secure setup. It is powerful, but it is not risk-free.

If you want to experiment with it or understand the setup process, you can check this guide here.

Even if you never install it, I think Clawdbot is worth watching. It shows where expectations are heading. People want AI that works in the background and takes real tasks off their plate, not just smarter chat.

While people experiment with personal AI agents, the biggest companies in the world are racing to secure the talent needed to build their own.

Google recently acquired Common Sense Machines for 2D-to-3D conversion, critical for AR/VR and spatial computing.

They hired Hume AI's entire engineering team for emotional voice intelligence, the layer that makes AI conversations feel natural.

And they invested in Sakana AI for a strategic foothold in Japan's $63B AI market.

Three deals. One week. Unprecedented pace for Google.

This signals desperation or smart strategic positioning, depending on how you look at it. Either way, Google is racing to catch OpenAI and plugging critical gaps before competitors lock up the talent.

Think about what that means. The expertise to build emotional voice AI or 3D generation tools takes years to develop. You can't just hire a bunch of engineers and expect them to figure it out. You need teams who've already solved the hard problems.

For founders: this shows niche AI expertise beats general-purpose tools. Google didn't buy a chatbot wrapper. They bought teams solving specific, defensible problems.

On the other side, Anthropic launched interactive Claude apps that embed Slack, Figma, Canva, Asana, and other workplace tools directly inside the Claude interface.

You can draft Slack messages, edit Canva designs, and update Asana tasks without leaving the chatbot.

Claude uses MCP (Model Context Protocol) for deeper integration versus the plugin architecture that mostly failed for ChatGPT. This matters because switching costs just got real. Once your workflow lives inside Claude, leaving becomes painful.

The app integration war is heating up. While ChatGPT focused on plugins, Claude went deeper. Available to Claude Pro and Enterprise users first:

This shifts AI from "answer provider" to "workflow orchestrator."

According to Kyndryl's 2025 Readiness Report surveying 3,700 senior leaders, 61% feel mounting pressure to prove AI ROI. Meanwhile, 84% of enterprises plan to increase AI agent investments in 2026.

The honeymoon phase is over.

After two years of "AI everything" hype, CFOs are asking the hard question: where's the money? This creates a survival filter. AI projects that don't show measurable business impact will get cut.

Here's what's working: early adopters report 4.3x ROI within 12 months, but only when deployed for specific tasks. Not "AI for innovation." AI for automation.

The gap between pilot projects and production is where companies die. Companies that treated AI as a science experiment will struggle. Those that approached it as operational infrastructure, automating specific workflows rather than "exploring possibilities," will win.

Audit your AI spend RIGHT NOW. Ask: "What specific process does this replace, and what's the time/cost savings?" If you can't answer in a minute, kill the project. Focus on narrow, measurable wins over broad "transformation."

All of this points to the same shift. AI is maturing from novelty to infrastructure. The winners will be those who execute on narrow, measurable use cases rather than chasing broad "transformation."

Google's panic acquisition mode shows they're plugging gaps. Claude's workflow orchestration shows AI is moving from chat interfaces to embedded systems. The ROI pressure forces companies to prove value or die. And Stanford's data confirms the "open science" era is over.

So where does that leave you?

Focus on building niche expertise that big companies want to acquire. Choose your AI workflow hub now before switching costs lock you in. Audit every AI project for measurable ROI. And stop waiting for research breakthroughs, focus on application.

The question is no longer "will AI change things?" It's "how quickly can you adapt?"

PS: I'm curious what you think about Clawdbot and which AI are you betting on as your workflow hub? Hit reply and let me know.

– Aashish

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