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Welcome to another edition of AI PlanetX.
Anthropic tests Claude agents in real office marketplaces; Google may invest $40B to accelerate Claude, while DOJ joins Elon Musk’s xAI in challenging Colorado’s AI law.
Inside This Edition: 💎
Hottest AI News
Top AI & SaaS Tools
AI Tutorial: Set Up Local Coding LLM on Laptop
Top AI & Tech News
AI Art Spotlight
Prompt of the Day: OpenAI Engineers Prompt Trick
Featured AI Video
Weekly Creator Playbooks to Grow on Social
Hottest AI News
Anthropic
Anthropic Tested Claude Agents In A Real Office Marketplace
Anthropic’s Project Deal shows what happens when Claude agents negotiate for humans. Claude interviewed 69 employees, learned what they wanted to buy or sell, then handled deals inside a real office marketplace.
Details:
Claude agents ran the buying, selling, and bargaining. The real market ended with 186 deals across 500+ listed items, with more than $4,000 in total transaction value
The model quality mattered. Opus agents got better deals than Haiku agents, but most people did not notice the gap. This shows stronger AI could create real economic advantage
Custom instructions were followed, even cowboy-style personas, but tough prompts did not clearly win. Claude even bought 19 ping-pong balls and matched one person with his own snowboard
This is a small experiment, but a big signal. AI agents may soon negotiate for us, so markets, rules, and trust systems will need to catch up urgently.
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DeepMind
Google May Pour $40B Into Anthropic To Scale Claude AI Quicker
Google is preparing one of the biggest AI infrastructure moves yet. It may invest up to $40B in Anthropic through cash and cloud compute, giving Claude more money, chips, and capacity to scale.
Details:
Google would invest $10B at a $350B Anthropic valuation. Another $30B could follow if Anthropic hits performance targets, making this a funding and execution deal
Google Cloud is also expected to provide 5 gigawatts of compute capacity over five years. That is the real engine behind the deal, because frontier AI needs massive power
Anthropic is already backed by Amazon and using other compute partners too. With Claude, Claude Code, and Mythos, it is trying to compete at the highest level of AI
The signal is clear. Better models matter, but cash, chips, cloud capacity, energy, and infrastructure may decide who wins the next AI wave.
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Inrō AI: automates Instagram DMs end-to-end, using AI to engage, qualify leads, book calls, and integrate with 8,000+ tools [F-R-E-E]
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The best prompt engineers aren't typing. They're talking.
Power users figured this out early: speaking a prompt gives you 10x more context in half the time. You include the edge cases, the examples, the tone you want — because talking is fast enough that you don't skip them.
Wispr Flow captures everything you say and turns it into clean, structured text for any AI tool. Speak messy. Get polished input. Paste into ChatGPT, Claude, Cursor, or wherever you work.
89% of messages sent with zero edits. 4x faster than typing. Works system-wide on Mac, Windows, and iPhone.
AI Tutorial
How to Run Your Own Coding AI on Your Laptop at No Charge
Want your own coding AI running locally on your laptop at no charge? In this guide, I’ll show you how to set up a coding LLM with Ollama and use it inside tools like Claude Code or Codex in just a few steps.
Check laptop specs
Take a screenshot of your PC hardware specs, then drop them into Claude or ChatGPT and ask which Ollama coder model your machine can run well.
Include RAM, CPU, GPU, and VRAM if available
Ask for best mix of speed and coding quality
Choose coder model
Browse Ollama coder models and pick best option for your hardware. Then copy its launch command.
Example:
ollama run <model-name>Enter project folder
Launch a terminal inside the folder where you want the coding agent to work.
Download and launch model
Paste the command into the terminal, start the download, and wait for setup to finish.
The first run may take time depending on model size
Once complete, the local model will be ready to use
Connect it to coding tool
Launch Claude Code or Codex and point it to the Ollama model running on your laptop.
Increase context size
Go to Ollama > Settings > Context and raise the default 4K context window to 32K or higher.
Troubleshoot if needed
If Claude Code refuses tasks or drops tool calls, try OpenCode with the same local model setup.
Test with smaller tasks first
Lower context size if performance becomes unstable
Note: Test your setup with small prompts first, such as fixing a bug or explaining a function, before asking it to handle a full project.
Top AI & Tech News
Nothing launched Essential Voice — an AI dictation tool that converts speech to formatted text system‑wide, removes filler words, supports custom voice shortcuts
Thinking Machines Lab is rapidly hiring top AI talent including ex-Meta researchers as it scales after landing a multibillion-dollar Google cloud deal for Nvidia GB300 chips
U.S. Department of Justice has joined Elon Musk’s xAI lawsuit challenging Colorado’s latest Consumer Protections for Artificial Intelligence law
OpenAI CEO Sam Altman apologized to Tumbler Ridge after a school shooting suspect had described violent scenarios to ChatGPT
AI Art Spotlight
Create Your Own Photo Like This Using the Prompt Below:
Using the attached picture
A high-fashion cinematic portrait of a man with a thoughtful expression, looking slightly upward. The image is a deconstructed multimedia collage: his face is overlaid with faint, intricate architectural blueprints, geometric grid lines, and technical schematics. The composition features an explosive, splattered edge effect with charcoal and white paint strokes. Scattered hyper-realistic orange autumn maple leaves drift around his neck and hair. He wears a thick, textured brown knit scarf. High-contrast lighting, 8k resolution, ultra-sharp focus on the eyes, featuring hyper-realistic skin textures, muted earth-tone color palette with pops of vibrant orange, editorial photography style.Model: ChatGPT Images 2.0
Prompt of the Day
OpenAI Engineers Use This Prompt Trick You’ve Never Heard Of
This X thread explains reverse prompting: instead of guessing prompts and getting generic output, you paste in a strong finished piece you like (yours or someone else’s) and ask, “What exact prompt would generate this?” The model reverse-engineers the tone, structure, pacing, depth, formatting, and style into a clean, reusable prompt template you can use again.
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