Hello and welcome to the Automated, your AI tour guide.
AI agents aren’t just a futuristic concept anymore—they’re here. And OpenAI just dropped a powerful new toolkit that could redefine how businesses build and deploy them.
The question is: Are we looking at the future of work, or just another overhyped AI experiment?
Here’s what we have for you today:
🦾 OpenAI Hands Businesses the Blueprint for AI Agents.
💽 Meta’s AI Power Move: Testing Its First In-House AI Training Chip!
⬆️ AI assistants: How to level up your work.
✒️ AI writing fingerprints: identify (& fix) AI-Generated contents.
🤖 ChatGPT Prompt Of The Day: Write a job application letter.
🦾 OpenAI Hands Businesses the Blueprint for AI Agents.
If you caught our last deep dive into AI agents, you already know what’s happening.
These digital workers aren’t just helping businesses—they’re replacing entire job roles.
Companies are literally posting job listings for AI agents instead of humans. And honestly, can you blame them?
AI doesn’t take lunch breaks, won’t storm out over a bad boss, and definitely won’t ask for a raise.
In our last breakdown, we explained why AI agents are the next big thing—how they’re streamlining operations and why companies are scrambling to automate everything.
But now? OpenAI is making sure that if businesses want in on the AI revolution, they’re the ones selling the picks and shovels in this gold rush.
And they’re not playing around.
They just made their biggest move yet with the Responses API—a new toolkit that lets businesses and developers build AI agents capable of searching the web, scanning company files, and even navigating websites like a highly efficient, unpaid intern.
This replaces OpenAI’s old Assistants API (which officially shuts down in 2026) and gives developers more control over creating their own AI-powered assistants.
So, what’s new?
Supercharged AI search – The API gives developers access to OpenAI’s GPT-4o search models, which can browse the web and (supposedly) provide accurate, sourced answers. OpenAI claims 90% accuracy, but let’s be real—hallucinations and bad citations are still very much a thing.
Instant file scanning – Need to sift through mountains of company data? The Responses API comes with a file search utility that quickly scans databases to retrieve information. (OpenAI swears it won’t use this data for training models… but, well, we’ll see.)
Automate tasks on a computer – Developers can tap into OpenAI’s Computer-Using Agent (CUA) model, (the same one powering Operator). This AI doesn’t just sit there—it clicks, types, and navigates apps like a digital office worker. It’s still in research preview, but OpenAI sees it as the future of AI-powered automation.
And since even OpenAI knows AI agents still have a long way to go, they’re also rolling out the Agents SDK—a free developer toolkit for integrating models, adding safeguards, and debugging AI behaviors.
But let’s be real—AI agents have been a mixed bag so far. We’re talking tons of hype, but very few actually delivering.
Take Butterfly Effect’s Manus, for example. It went viral last week… for all the wrong reasons.
Turns out, it didn’t live up to the hype, and let’s just say that’s exactly the kind of disaster OpenAI is trying to avoid.
So, what’s OpenAI’s game plan?
They know the real challenge isn’t just building AI agents—it’s making them actually useful and scalable.
That’s why they’re not selling AI agents directly (yet). Instead, they’re selling the building blocks for businesses to create their own.
But here’s the bigger picture:
OpenAI isn’t just building AI tools or giving developers access—they’re positioning themselves as the gatekeepers of this new AI workforce.
Sam Altman already declared 2025 as the year AI agents enter the workforce, and this API is a major step toward making that happen.
In short, OpenAI is making sure they own that transition.
The real question now is: Will AI agents actually deliver, or are we in for another wave of overpromising and underdelivering?
Find out more about this game-changing development [here].
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💽 Meta’s AI Power Move: Testing Its First In-House AI Training Chip!
Meta is making a bold push into AI chip development, testing its first in-house training chip in an effort to reduce dependence on Nvidia and cut massive AI infrastructure costs.
The chip, part of Meta’s Meta Training and Inference Accelerator (MTIA) series, is being produced by TSMC and could play a key role in training AI models for recommendations and future GenAI applications like Meta AI.
🚀 Why This Matters
Meta is spending big on AI—it expects $65B in AI-driven capital expenditures in 2025. Developing custom chips could slash costs in the long run.
The chip is a dedicated AI accelerator, meaning it’s designed for AI workloads rather than general-purpose computing, which could make it more power-efficient than GPUs.
Success isn’t guaranteed—Meta previously scrapped an MTIA chip after a failed small-scale deployment and has since relied heavily on Nvidia, spending billions on GPUs.
🛠 The Road to AI Independence
According to Chief Product Officer Chris Cox, Meta’s first-generation inference chip, which is used for content recommendations on Facebook and Instagram, was a “big success."
If this new training chip proves viable, Meta plans to gradually shift AI workloads away from third-party hardware like Nvidia’s GPUs.
But Meta isn’t alone—other AI giants, including Google (TPU) and Amazon (Trainium & Inferentia), have also developed custom AI chips to cut costs and optimize performance.
⚖ The Bigger Picture
AI’s Compute Race Is Changing: Scaling up massive AI models with more data & GPUs is no longer the only path forward—smarter, more efficient models (like DeepSeek’s) are challenging that approach.
Nvidia’s Dominance Faces Pressure: Nvidia’s stock has fluctuated as AI chip competition heats up, though it remains the industry leader.
Meta’s AI Strategy Gets More Serious: If the training chip works, Meta could reshape its AI infrastructure by 2026—and possibly shake up the AI hardware market.
Can Meta finally break free from Nvidia’s grip? The next few months will be crucial.
🧱Around The AI Block
⬆️ AI assistants: How to level up your work.
✒️ AI writing fingerprints: identify (& fix) AI-Generated contents.
✍️ OpenAI says it has trained an AI that’s ‘really good’ at creative writing.
💵 Inside Google’s Investment in the A.I. Start-Up Anthropic.
💼 DOGE’s GSAi chatbot expands to 1,500 federal workers.
🤖 EU AI Act: Latest draft Code for AI model makers.
🛠️ Trending Tools
ElevenLabs: AI-powered voice synthesis tool that creates ultra-realistic speech from text.
Spline AI: AI-driven 3D design tool that generates interactive 3D scenes from text prompts.
Peacasso AI: AI tool that transforms text descriptions into high-quality digital paintings.
Veed.io: AI-powered online video editor with automatic subtitles, translations, and effects.
Harmonai: AI tool for generating and remixing high-quality music with deep learning.
🤖ChatGPT Prompt Of The Day: Write a job application letter.
A strong job application letter isn’t just a formality—it’s your chance to make a lasting impression. The right words can showcase your skills, highlight your experience, and set you apart from other candidates.
With ChatGPT-4, you can craft a compelling letter that grabs attention and increases your chances of landing the job.
Here’s a prompt to help you create a standout job application:
Write a job application for the position of [job title] with the company [employer’s name]. Write a letter that will make me stand out from the crowd. Highlight my skills in [insert relevant skills] and my experience with [insert relevant previous experience].We've Compiled a List of Over 100 ChatGPT Power Prompts.
This should help streamline your interactions with ChatGPT and get the results you need more efficiently.
Best of all, It's free!
That's all we've got for you today.
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