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How to build reliable AI agents for mission-critical tasks
ChatGPT Projects gets smarter, Microsoft adds Copilot Vision to Windows, Mattel and OpenAI's AI-powered toys and more!
Everyday AI
June 12, 2025
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Outsmart The Future
Today in Everyday AI
7 minute read
š Daily Podcast Episode: Learn how to build reliable AI agents for mission-critical tasks. We reveal the secrets to trust, reliability, and the future of multi-agent AI systems. Give it a listen.
šµļøāāļø Fresh Finds: Klarna CEO gets AI clone, GOP proposes AI company bill and Wikipedia pauses AI-generated summaries. Read on for Fresh Finds.
š Byte Sized Daily AI News: ChatGPT Projects gets smarter and adds voice mode, Microsoft adds Copilot Vision to Windows and Mattel and OpenAI to create AI-powered toys. For that and more, read on for Byte Sized News.
š§ Learn & Leveraging AI: Enterprises may know that AI agents are the next move but they might not know where to start. We provide you with a guideline. Keep reading for that!
ā©ļø Donāt miss out: Did you miss our last newsletter? We talked about OpenAI unveiling o3-pro, Amazon releasing AI video ad tools, U.S. gov. launching an AI chatbot and more. Check it here!
How to build reliable AI agents for mission-critical tasks š
Every enterprise is legit rushing to build AI agents.
But there's no instructions.
So, what do you do? How do you make sure it works? How do you track reliability and traceability?
Also on the pod today:
ā¢ Building Reliable AI Agents Guide šØ
ā¢ Micro Agentic System Architecture Discussion š·
ā¢ Nondeterministic Software Challenges for Enterprises š¢
Itāll be worth your 29 minutes:
Listen on our site:
Click to listen
Subscribe and listen on your favorite podcast platform
Listen on:
Hereās our favorite AI finds from across the web:
New AI Tool Spotlight ā Sider brings visual reports to AI Deep Research, Superlines helps you get discovered in AI search results, Autodraft helps you create 4K animations for YouTube. (With the help of AI, of course.)
Trending in AI ā Klarnaās CEO is now taking calls over an AI hotline.
AI in Government ā A new GOP bill would protect AI companies from lawsuits if theyāre transparent.
The U.S. Govās vaccine website has been defaced with AI-generated content.
AI Search ā Wikipedia is pausing AI-generated summaries pilot after editors protest.
AI Startups ā Sam Altman backed Coco Robotics has raised $80M.
Cohere ā Cohere has released an ebook on building enterprise AI agents.
1. ChatGPT Projects Get Smarter and More Hands-Free šļø
In the latest June 2025 update, ChatGPTās Projects feature takes a big leap with deep research that mixes your project data with live web info, making multi-step tasks smoother. Voice mode arrives, letting users talk through ideas or query files without typing, a real boost for busy professionals on the move. Sharing gets easier with unique URLs for individual chats, while mobile users now enjoy direct file uploads and model switchingāif they update their apps.
Plus, improved memory keeps conversations focused by recalling past chats, turning Projects into a more powerful workspace for anyone juggling complex, ongoing work.
2. Microsoft Launches Copilot Vision for Windows š»
Microsoft is rolling out Copilot Vision for Windows today, bringing AI-powered screen sharing directly into the Copilot app for Windows 10 and 11 users in the USāno Copilot Pro subscription needed. This new feature lets users share apps or browser windows, enabling the AI to analyze content, offer real-time guidance, and answer questions as you work, from Photoshop to web pages.
Having been tested earlier this year and previewed at Microsoftās 50th anniversary event, Copilot Vision aims to act as a "second set of eyes" to boost productivity and learning on the fly.
3. Google Unveils AI Model to Forecast Hurricanes with Greater Precision šŖļøļø
Google DeepMind and Google Research have launched Weather Lab, featuring a new AI model that predicts tropical cyclone tracks, size, and intensity up to 15 days ahead, showing notable accuracy improvements over traditional models like ECMWF. The US National Hurricane Center is collaborating with Google to test this technology during the ongoing Atlantic hurricane season, aiming to enhance early warning systems and public preparedness.
Trained on vast global weather data from Europeās ERA5 archive, the modelās five-day forecasts were on average 87 miles closer to actual storm tracks than existing European forecasts in recent trials.
4. EchoLeak: First Zero-Click AI Flaw Hits Microsoft 365 Copilot šØ
A critical zero-click vulnerability named EchoLeak was uncovered in January 2025 by Aim Labs, allowing attackers to silently extract sensitive data from Microsoft 365 Copilot without any user interaction. Microsoft patched the issue server-side by May, with no evidence of real-world attacks, but the flaw exposes a new risk class dubbed āLLM Scope Violationā that could sneak privileged info from AI assistants.
EchoLeak exploits how maliciously crafted emails can hijack Copilotās retrieval system to leak data via image requests, highlighting growing security challenges as AI tools deeply integrate into enterprise workflows.
5. Mattel Joins Forces with OpenAI to Launch AI-Driven Toys š§ø
Mattel announced a partnership with OpenAI to develop AI-powered toys and games, with the first product expected later this year, signaling a bold step into the future of play. The move aims to combine innovative AI technology with a focus on safety and privacy, addressing evolving consumer expectations amid a cooling toy market.
Beyond toys, Mattel plans to use OpenAIās tools like ChatGPT Enterprise to boost creativity and productivity across its business. This strategy reflects Mattelās push to adapt and thrive despite economic uncertainties and shifting trade policies.
6. Meta Takes Legal and Tech Action Against AI āNudifyā Ads āļø
Meta has sued Joy Timeline HK, the company behind Crush AI, for running over 8,000 ads promoting AI-generated explicit images without consent, bypassing Metaās ad review on Facebook and Instagram. Despite repeated removals, Crush AI reportedly kept creating new accounts and domains to evade detection, fueling a surge in such ads across social media platforms in early 2025.
Meta has now rolled out advanced tech to spot these ads even when they lack nudity and is sharing data with other tech giants to fight this growing threat.
š¦¾How You Can Leverage:
Millions of developers are frantically googling "agent reliability."
Someone finally said the quiet part out loud: your software is about to become non-deterministic.
And you're not ready.
So on today's show, we walked through why enterprises are deploying agents that can nuke supply chains if they hallucinate at 3 AM. Yash Sheth from Galileo dropped uncomfortable truths about probabilistic business decisions.
The smart money is building 300-millisecond guardrails while everyone else debates if agents are "production ready."
Spoiler: they're shipping supply chain automation, outage prevention, and self-managing data platforms RIGHT NOW.
The companies that crack reliability first will scale autonomous operations while competitors debug hallucinations.
1 ā Microservices Just Got Replaced šļø
Every software component you've built is getting an intelligence upgrade.
Hard-coding business logic just became as outdated as writing assembly by hand. The future belongs to micro-agentic architectures where components get independent reasoning instead of rigid rules.
Your inventory system doesn't execute pre-programmed logic anymore.
It learns patterns, adapts to market shifts, and coordinates with other intelligent components in real-time.
Cool, right? Until your software thinks itself into trouble.
Here's what early adopters figured out: intelligent components create exponential advantages. While competitors manually update business rules, your systems evolve themselves.
Try This:
Pick your most manual workflow touching multiple systems.
Map which steps could become reasoning agents. Start smallādocument processing, lead routing, data validation. Build one agent handling ONE task. Connect using existing protocols. Test handoffs in staging. Deploy when it stops making you nervous.
2 ā Unit Tests Are Dead š§Ŗ
When software produces different outputs for identical inputs, traditional QA becomes useless.
Non-deterministic software breaks 50 years of reliability assumptions.
You can't just check if code works anymore. You check if intelligence works consistently. That requires custom evaluation datasets from actual business scenarios, not academic benchmarks with zero relationship to reality.
Nothing screams amateur hour like testing customer service agents with medieval poetry datasets.
The breakthrough: real-time evaluation metrics, prevention systems triggering in milliseconds, and mitigation protocols for when agents go sideways.
Companies building robust evaluation frameworks now will dominate while others debug why their agents suggest "turn it off and on again" for bankruptcy filings.
Try This:
Build evaluation datasets from real data.
Grab 100 customer interactions from last month. Create test scenarios where agents must make correct decisions. Run different models through these scenarios. Measure tool selection accuracy and response quality. Choose models based on performance, not hype.
3 ā Agent Authentication is Chaos š¤
When your planning agent hands off to execution agents, you're asking one AI to trust another with business-critical operations.
What could go wrong? Everything.
Three problems keeping architects awake: How does Agent A verify Agent B isn't broken? How do you maintain user permissions across agent handoffs? How do different AI systems communicate without creating digital spaghetti?
Plot twist: solving this isn't just about reliable agents.
You're building communication infrastructure for the entire multi-agent ecosystem. Companies that nail this foundational layer control the rails everyone else runs on.
Think internet protocols for AI agents. Except with actual money involved.
Winners establish standards. Losers pay licensing fees.
Try This:
Design authentication surviving agent handoffs.
Start simpleāone agent extracts data, another validates, third updates systems. Monitor every handoff in real-time. Test with intentional failures because agents WILL break eventually. Know how fallbacks work before production needs them.
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