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Inside Multi-Agent AI: Rethinking Enterprise Decisions
Google I/O AI updates, Windows 11 gets AI shortcuts, Apple’s former Siri chief wanted Gemini and more!
Everyday AI
May 23, 2025
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The pod and newsletter will be taking a break……
….. for the Memorial Day Holiday on Monday here in the U.S. 🤪
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Outsmart The Future
Today in Everyday AI
7 minute read
🎙 Daily Podcast Episode: Once AI agents are everywhere, how will enterprises navigate multi-agent AI? We dive in and find out. Give it a listen.
🕵️‍♂️ Fresh Finds: U.S. judge says AI chatbots don't have free speech rights, AI video is too good now, the future of AI in 2027 and more Read on for Fresh Finds.
đź—ž Byte Sized Daily AI News: OpenAI upgrades its Operator Agent, Oracle buying 400,000 NVIDIA chips, Elon Musk in more hot water for Grok use in Government and more. Read on for Byte Sized News.
🧠Learn & Leveraging AI: Here’s what you need to know about multi-agent AI to prepare and grow your company or career. Keep reading for that!
↩️ Don’t miss out: Did you miss our last newsletter? We talked about Anthropic already in hot water over its fresh Claude 4 release, OpenAI looking to sell 100 million hardware devices, Apple getting in on AI glasses and more. Check it here!
Inside Multi-Agent AI: Rethinking Enterprise Decisions đź’ˇ
What happens when.... AI agents are everywhere?
To learn, we tapped into the insights from one of the leading voices in AI, Babak Hodjat, whose resume includes helping create the tech behind the original AI agents like Siri.
So, how do enterprises prepare for a multi-agent environment? We dive in to find out.
Join the conversation and ask Jordan questions on AI agents here.
Also on the pod today:
• Implementing Multi-Agent Systems 👥
• Hallucinations and Errors in AI Systems ❌
• Usage and Organization within Multi-Agents 🗂️
It’ll be worth your 37 minutes:
Listen on our site:
Click to listen
Subscribe and listen on your favorite podcast platform
Listen on:
Here’s our favorite AI finds from across the web:
New AI Tool Spotlight – Morphik is an open-source AI knowledgebase, Chance AI turns your camera into an AI detective, Generate Ads helps you….. well, generate ads with AI.
Legal AI Challenges — A judge says that AI chatbots don’t have free speech rights. Find out why.
AI Job Displacement — Find out why (and how) some notable CEOs are replacing themselves with AI.
AI in the Media — Authors are leaving AI prompts in their books, and it’s not exactly a good look.
AI Video — Experts are arguing AI video quality is so good with Google’s Veo 3, that we can no longer tell reality from AI.
AI Model Updates — Mistral released a new model called Document AI, that focuses on accurate text extraction from documents. (We’re here for this!)
Frontier Labs — This article argues that Anthropic is no longer an AI chatbot company.
Future of AI — A team of researchers set out to tell what the future will look like with AI in 2027, and it’s a little wild.
1.Fort Worth Eyes Major AI Supercomputer Plant Investment 🏦
Fort Worth is in the running to host a massive AI supercomputer manufacturing facility with a potential investment topping $687 million, as city officials prepare to consider a critical tax abatement agreement on June 24.
The plant, linked to Nvidia’s ambitious $500 billion U.S. AI infrastructure initiative, would occupy nearly 1 million square feet across two sites, with Taiwan-based Wistron leading local efforts. This move signals Texas’ growing role as a hub for semiconductor manufacturing and AI technology, promising to boost the regional economy and tech job market significantly.
2. Marjorie Taylor Greene Clashes with AI Chatbot Grok Over Faith Claims 🥊
In a fresh episode highlighting AI’s growing role in political discourse, Rep. Marjorie Taylor Greene sparred publicly with Elon Musk’s AI assistant Grok after it questioned the authenticity of her Christian faith.
The spat unfolded on X, where Grok critiqued Greene’s alignment of faith with her political actions, sparking backlash from the congresswoman who called the AI biased. This incident underscores the challenges AI faces in navigating sensitive topics like religion and politics, especially as public figures engage directly with AI’s fact-checking and commentary.
3. Oracle to Power OpenAI's Stargate with 400,000 Nvidia Chips ⚡
Oracle is making a massive $40 billion purchase of Nvidia’s cutting-edge GB200 Grace Blackwell processors to fuel an AI data center in Texas, part of OpenAI’s ambitious Stargate project.
Set to go live by mid-2026, this facility will consume as much electricity as a million homes, underscoring the scale of AI infrastructure expansion. The deal follows OpenAI’s cloud shift away from Microsoft and highlights a growing trend of specialized AI hardware investment to boost efficiency and performance.
4. OpenAI Upgrades Autonomous Browser Agent with New o3 Model đź§
OpenAI just rolled out a global update to its Operator agent, upgrading from GPT-4o to the sharper o3 reasoning model, now available as a research preview for ChatGPT Pro subscribers at $200/month. This upgrade boosts Operator’s ability to autonomously navigate websites, improving accuracy, task completion, and response clarity—key for professionals automating web tasks or data workflows.
The move also underscores OpenAI's focus on safety, with enhanced safeguards around sensitive actions and financial transactions. According to OpenAI’s latest release notes, this signals a meaningful step forward in making AI agents practical tools for both enterprise and everyday users looking to streamline digital tasks.
5. Elon Musk’s Grok AI Sparks Privacy and Ethics Concerns at U.S. Government 🕵️‍♂️
According to Reuters, Elon Musk’s Department of Government Efficiency (DOGE) team has been pushing the use of its AI chatbot, Grok, across federal agencies like the Department of Homeland Security without formal approval, raising alarms about potential violations of privacy laws and conflicts of interest.
Experts warn that this unauthorized deployment could expose sensitive data on millions of Americans and give Musk’s xAI an unfair edge in federal contracts. The situation underscores growing tensions around AI use in government, especially as agencies wrestle with balancing innovation and safeguarding confidential information.
🦾How You Can Leverage:
10-15 minutes.
That's how long it now takes Cognizant to create an AI proof-of-concept that used to require 10-12 weeks.
Not a typo. Not hype. A 99.7% timeline reduction happening TODAY in a 360,000-employee company through "agentification."
We sat down with Babak Hodjat, CTO of AI at Cognizant and co-inventor of Siri's natural language tech, who's been crafting multi-agent systems since the 90s.
While everyone else frets over hallucinations, he's building AI networks that are transforming enterprise decision-making at warp speed.
That shiny new AI strategy you just finalized?
Already collecting dust, y’all.
Here’s what you need to know from today’s show.
1 – The 672X Accelerator: Agentification 🤖
Multi-agent systems don't just improve single AIs—they reshape organizational structure from the ground up.
Babak's team at Cognizant shrunk implementation time from 10-12 weeks to 10-15 minutes by replacing monolithic modules with interconnected agents.
That's 672 times faster than your current approach.
(Like, we’re not that good at math, but that math maths, right?)
When Babak typed "my son just turned 26," the system instantly recognized cross-departmental implications—adjusting payroll, modifying benefits, even offering celebration time off. No forms. No tickets. No bureaucracy.
The secret isn't better AI, Babak said. The key is breaking AI into specialized pieces with clear responsibilities and seamless communication.
Try This:
Identify one cross-departmental process that creates employee frustration. Map every decision point, ownership, data requirements, and system dependencies.
Redesign assuming each decision had its own specialized agent with clear autonomy boundaries. Create this "agent blueprint" and implement a proof-of-concept connecting just two decision points.
Track not just time saved but reduction in employee headaches and context-switching.
2 – The Compounding Risk: When 99% Accuracy becomes a threat 🎯
Everyone obsesses over single-LLM hallucinations.
Nobody's talking about the far more dangerous compounding errors across connected agents.
An agent that's 99% accurate sounds amazing. But when that output becomes another agent's input, then another's? Errors compound exponentially.
The wild part? Babak suggests MORE AIs might fix AI inconsistency.
Multiple agents cross-checking can catch errors before they cascade.
One agent's hallucination becomes obvious when three others disagree.
But this contradicts the efficiency narrative driving AI adoption. It requires verification layers that might slow systems but make them bulletproof.
Most AI governance frameworks weren't built for this new reality.
Try This:
Run an "error propagation test" immediately. Design five subtly flawed inputs and track how far incorrect information travels before someone catches it.
Establish "confidence thresholds" with automatic human escalation when scores drop below critical levels.
Run this quarterly as you add more automation. Share results transparently to build organizational awareness of both AI and human failure modes.
3 – One Employee + Five Agents > Five Employees 🦾
Babak revealed how he automated his email workflow by creating an entire virtual team mirroring his organization.
His AI team didn't just sort his inbox—they analyzed content, made judgment calls, routed messages to the right places, and even drafted responses that sounded exactly like him.
This isn't one assistant. It's a personalized organization of specialized AIs working together to multiply your capabilities.
Success won't come from working faster. It'll come from becoming an AI conductor—orchestrating specialized agents while you focus on truly human-centric value.
The future knowledge worker doesn't do the work—they direct an AI team that does. Their competitive edge shifts from personal execution to effective delegation of intent.
The skills gap between those who can and can't direct AI teams will make today's digital divide look like a hairline crack.
Try This: Build your personal agent network around one recurring workflow that drains your energy.
For email, create three distinct agent personas: a Triage Specialist categorizing by urgency, a Research Analyst gathering context, and a Communications
Drafter preparing aligned responses. Give each specific guidelines about what they handle independently versus when to involve you. Use existing tools but customize with precise role descriptions.
Start with low-stakes tasks and document which instructions yield the best results, creating your personal playbook for effective agent orchestration.
The multi-agent revolution isn't coming—it's here while everyone's still debating prompt techniques.
You ready?
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