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Ep 717: AI Agents in 2026 Explained: What They Are and When You Should Use Them
Google releases Gemini 3.1 Pro, ChatGPT's 'Adult Mode' closer to release, Sam Altman and Dario Amodei's viral and awkward moment and more.
Everyday AI
February 19, 2026
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Today in Everyday AI
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🎙 Daily Podcast Episode: AI agents are finally here — but most people don’t know what they actually are. In Episode 8 of our Start Here series, we break down what’s real and when to use them in 2026. Give today’s show a watch/read/listen.
🕵️♂️ Fresh Finds: OpenAI Hires Meta’s Charles Porch, NotebookLM Launches a Zillow-Powered Notebook for First-Time Homebuyers, OpenAI Releases EVMbench, and more Read on for Fresh Finds.
🗞 Byte Sized Daily AI News: Google releases Gemini 3.1 Pro, ChatGPT's 'Adult Mode' closer to release, Sam Altman and Dario Amodei's viral and awkward moment and more. Read on for Byte Sized News.
💪 Leverage AI: The last month delivered more real AI agent progress than the last three years combined. Here’s how to spot agent washing and where to actually start. Keep reading for that!
↩️ Don’t miss out: Miss our last newsletter? We covered: Former presidential candidates says AI will take 50% of jobs, NVIDIA and Meta’s blockbuster AI deal, World Labs raises $1 billion and more. Check it here!
Ep 717: AI Agents in 2026 Explained: What They Are and When You Should Use Them
AI Agents. AI Agents everywhere. 🪐
For what seems like an eternity, we've been hearing about how AI agents were going to do everything. (In a good and bad way)
But it never really happened.
Until now.
Today, AI agents are more important than ever. But... the questions are still legit plentiful.
↳ What actually is an AI agent?
↳ How do they work?
↳ And what are the best ways to implement them?
Also on the pod today:
• AI agents: not just chatbots 🤖
• Agent washing: real vs. fake 💧
• Why "human in the loop" fails 🚫
It’ll be worth your 30 minutes:
Listen on our site:
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Here’s our favorite AI finds from across the web:
New AI Tool Spotlight – Kollect lets you Generate forms with AI and collects responses through voice, Mengram is The only AI memory API with human-like architecture, Feedix refines the vast information in videos into the most elegant editorial articles.
Meta Smart Watch — Meta may launch an AI health watch, Malibu 2, this year. Could it steal wrist time from Apple and Google?
Cursor Plugins — Cursor now supports plugins for Figma, Stripe, and AWS.
ChatGPT Atlas Browser — ChatGPT Atlas can auto-organize 100+ open tabs into tidy groups. Want to see if it actually cuts clutter and RAM use?
Introducing EVMbench — EVMbench tests AI agents on 120 real smart-contract bugs. Top models exploit well, but detection and patching lag.
NotebookLM Real Estate — NotebookLM hosts Zillow’s home-buying tips in one interactive guide.
Phoenix 4 Released — Phoenix-4 renders real-time virtual humans with lifelike emotions and context-aware listening. Click to Learn More
Google CEO Statement — Google CEO Sundar Pichai told world leaders that AI is the biggest platform shift of our lifetimes and urged bold, responsible action to spread its benefits globally.
Copilot Sensitive Information Bug — Copilot read and summarized emails labeled confidential due to a sensitivity-label bug. Microsoft is rolling out a fix and investigating exposure.
Google Pomelli Photoshoot — Pomelli’s Photoshoot is being prepared to turn one product photo into ready-to-use marketing images.
New Ring Feature Controversy — Ring’s Search Party for Dogs was only step one, with founders hinting the tech could be used to “zero out crime.” Curious why that’s alarming?
OpenAI Hires Former Meta/Instagram Staff — OpenAI hired Instagram’s Charles Porch to charm Hollywood and lock down likeness deals
1. Sam Altman says AI is reshaping jobs, not always the scapegoat 👷
OpenAI CEO Sam Altman told reporters this week that artificial intelligence is displacing some jobs now, but he argued that some companies are blaming AI for layoffs they would have made regardless, making the technology an easy public explanation.
Altman’s comments come amid a broader wave of industry restructuring and intense scrutiny over AI’s workplace impact, highlighting tension between real displacement and corporate framing. The remarks are timely because companies and regulators are racing to define accountability, workforce policy, and public expectations as AI adoption accelerates.
2. AI summit photo moment underlines OpenAI‑Anthropic rivalry 🤝
At the India AI Impact Summit on Feb. 19, 2026, a stage photo with Prime Minister Narendra Modi, Sam Altman and Dario Amodei went viral after Altman and Amodei declined to hold hands, instead raising fists, a gesture quickly picked up on social media and framed as symbolic of growing competition.
The brief awkwardness followed public sparring between the two companies over ads and business strategy, and came after both CEOs gave keynote speeches stressing different priorities: Altman on societal resilience and ads experimentation, Amodei on safety and risks. The moment matters because it visually captured the real commercial and philosophical tensions between two leading AI labs racing for users, enterprise deals and influence.
3. Agents gaining ground: real-world autonomy rises as risks creep in 🧠
A new study from Anthropic finds AI agents are operating more independently in practice, with Claude Code sessions showing the longest continuous runs nearly doubling to over 45 minutes in recent months, signaling faster growth in real-world autonomy.
The report also shows experienced users grant more auto-approval but interrupt more, while the model itself asks clarification questions increasingly on harder tasks, suggesting oversight is shifting from step-by-step approval to monitoring and targeted intervention. Most agent actions remain low-risk and reversible and are concentrated in software engineering, yet emerging uses in healthcare, finance, and security hint the frontier of higher-risk, higher-autonomy deployments is expanding.
4. Anthropic boss warns: AI heading past most human thinkers 🤖
Anthropic CEO Dario Amodei told reporters this week that advanced AI models are on track to exceed the cognitive capabilities of most humans within the next few years, a claim that raises fresh urgency around safety and governance.
The timing matters because if these tools outstrip typical human reasoning soon, regulators, companies, and researchers will need faster, clearer rules to manage risks and deployment. Amodei framed the prediction as a call to invest in robust safeguards and verification methods rather than a tech inevitability, stressing that choices now will shape outcomes.
5. Google Launches Gemini 3.1 Pro with Breakthrough Reasoning Power ⚙️
Google has just released Gemini 3.1 Pro, the latest upgrade to its AI lineup, now available in preview across developer and consumer platforms. This model doubles the reasoning performance of its predecessor, hitting a 77.1% verified score on the challenging ARC-AGI-2 benchmark that tests new logic patterns.
Designed for complex problem-solving, Gemini 3.1 Pro targets tasks that require advanced synthesis and explanation beyond simple answers. The release signals Google’s ongoing push to bring smarter, more capable AI into practical use while gathering feedback ahead of a wider rollout.
6. “Citron Mode” surfaces as possible adult-only setting in ChatGPT chatter 🗣️
A spike of posts this week reveal a new "Citron Mode Enabled" label and warnings about "sensitive content" and 18+ verification when sharing citron-only chats, prompting questions about whether this is an explicit-content toggle or a more general reduced-filter mode.
Users and developers are debating use cases from adult content to enterprise needs like processing explicit HR incidents, while others argue a looser filter could improve nuance and capability at the cost of safety controls. The discussion also raised age-check and moderation challenges, with people pointing out verification friction and potential spoofing problems for platforms.
Three-ish years of being promised "this is the year of the AI agent" and it never was.
Then the last month happened and delivered more agent breakthroughs than the previous 2.9 years combined.
(And sorry…. if you've been tuning out the agent noise, you prolly just missed the gnarliest shift in AI since ChatGPT dropped.)
Every major player moved at once. Anthropic shipped multi-agent teams, OpenAI scooped up the creator of OpenClaw, Meta bought Manus for $2 billion, and Google has been shipping agents by default in like a dozen of their products.
But Gartner looked at thousands of vendors selling you "AI agents" and found only 130 are actually real. The rest? Rebranded chatbots wearing a fancy hat.
We broke all of this down on volume 8 of the Everyday AI Start Here Series, the essential series that's already helped over a thousand people go from AI basics to AI fluency. Today we laid out how to spot agent washing before it eats your budget and how to safely pilot your first agent this week.
If your competitors nail this before you do, that gap ain't closing.
Time to capitalize shorties.
1. Most AI Agents Are Straight Up Fake 🔥
Gartner coined a beautiful term for this. Agent washing.
It's vendors out there slapping the word "agent" on chatbots and RPA tools like they're stuffing buzzwords into a pitch deck and straight up hoping nobody checks under the hood. Less than five percent are legit.
A real agent is like sitting an entry-level employee down at a computer with access to everything. It plans, calls tools you didn't know it had, self-corrects, and retries down a completely different path.
If it can't do that, it's automation in a costume.
Even your daily software is in on the rebrand. ClickUp, Salesforce, HubSpot, Slack. Features that used to just be features are now magically "agents."
Meanwhile 88% of executives are investing in agentic AI and most can't tell what's real from what's marketing.
Wild.
Try This
Open your company's software spend tracker this Monday. Flag every tool that claims to be an "agent" and test it against one filter. Can it plan multi-step tasks and adapt when something breaks without a human pushing buttons?
Bring that list to your next leadership sync. You'll prolly find six figures in annual spend going to glorified chatbots.
2. Agents On Broken Processes Compound Chaos ⚡
And the biggest reason ain't the tech.
It's that companies are treating agents like duct tape for processes already falling apart. They see something humans are struggling with and think an agent will magically fix it.
Think of it like giving a three-year-old a task. Hey kiddo, go put this toy away. Did it get put away? Sure. Did they knock over a lamp and smear marker all over the new couch? Prolly.
(Real talk….. that's EXACTLY what your agent is gonna do to a broken workflow. At machine speed.)
You gotta apply agents only to processes that are already smooth, documented with SOPs, and measurable. And you don't just upgrade the workflow. You deconstruct it and rebuild agentic-first from scratch.
Try This
Pick your single best-documented workflow with clear SOPs and existing metrics. That's your agent candidate.
Run it through one gut check. If you removed every human from this process tomorrow, would the documentation alone be enough to train a new hire? If not, it ain't ready for an agent either.
3. Start At Suggest Only This Week 🚀
Bounded autonomy is the only safe on-ramp.
Begin at suggest only. The agent drafts, you decide. Meeting action items? Have an agent draft owners and follow-ups in your project management tool, then you approve before a single thing gets sent.
Once that's working, move to execute with approval. One-click sign-off.
Only THEN can you scale toward real autonomy with spending caps, permission rules, and audit trails.
Because the 2026 CISO AI Risk Report found 92% of organizations lack full visibility into their AI identities. Shadow AI ain't just someone sneaking onto ChatGPT anymore. It's unsanctioned agents making decisions with access to your data and nobody knows they exist.
Try This
Set up ChatGPT's agent mode or Claude to triage your inbox this week. Not to act. Just to sort, flag, and surface what matters so you can see how it thinks.
Measure time saved over two weeks. That data becomes your business case for scaling before the competition gets there first.
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