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The end of SaaS? How Agentic AI is changing the game
AI coding tools slow experienced developers & get top 3 AI tools
Aljin Vijayan
July 11, 2025
👋 Hey there, Welcome back: There’s a big change happening in tech, and it looks like the SaaS (software tools) we use every day might soon be replaced.
Instead of jumping between 20+ apps, Agentic AI can now take care of your tools, data, and tasks, all by itself.
While traditional automation just follows commands, agentic AI can think, decide, and act across tools like a real assistant.
In today’s edition of NeuralDrop, you’ll learn
- What agentic AI is (in simple words)
- Why it’s becoming popular right now
- And how it might replace apps completely in the future
📦 In Today’s AI drop
- Why SaaS might be dead, and AI Agents are taking over
- Latest trending AI news you should know
- 3 Remote AI Job Opportunities
🧰 Remote AI Job Opportunities
🎮 That’s No Moon - Senior AI Engineer
💼 Coinbase - Product Manager II - AI Platform
☁️ Believe Solutions - AI Engineer (Cloud & Generative AI)
🤯 This Week in AI
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🌏 Huawei pushes AI chips in Middle East & Southeast Asia: Huawei is offering its Ascend 910B AI chips to countries like UAE, Saudi Arabia, and Thailand. Meanwhile, it's promoting cloud-based CloudMatrix 384 systems. No firm deals yet, but the move aims to compete with U.S. semiconductor giants like Nvidia. Know more
📹 YouTube updates monetization policy for AI content: YouTube will crack down on mass‑produced, repetitive, low‑quality AI-generated content , with clarifications to prevent demonetizing creators who use AI responsibly. Know More
🚀 SaaS is Going Away
Image Source: TechCrunch
Dave Park, CEO of Narada AI, told TechCrunch’s Equity podcast:
SaaS is going away… the typical knowledge worker today deals with anywhere from 17 to 25 different SaaS tools… wasting two and a half hours just manually looking up or updating these systems.
He predicts AI agents will soon handle your data across apps automatically with no human intermediaries.
🧠 What is Agentic AI?
Agentic AI can think, adapt, and work across different tools on its own, but traditional automation just follows strict rules in one app.
Agentic AI can think through problems, make decisions, and complete multi-step tasks across different software, even if those tools don’t officially work together.
This is possible because of something Narada AI calls large action models. Instead of just generating text like ChatGPT, these models understand how tasks and workflows work out in real-life jobs.
⏳ Why Now?
We’re reaching a breaking point in how we use digital tools at work.
Most knowledge workers deal with anywhere from 17 to 25 different SaaS apps every day, which consumes around two and a half hours of productivity, just switching between them, logging in, updating data, and searching for the right information.
This is why many are now looking to agentic AI as a better solution, and the interest is growing fast.
In fact, Y Combinator’s(a startup accelerator program) latest batch featured over 70 startups building AI agents. Big companies aren’t ignoring it either.
Platforms like Grammarly are already shifting, and adding layers of AI technology through partnerships and acquisitions to prepare for a more agent-powered future.
The message is clear: we’re moving toward a new kind of software experience.
🛠️ Real-World Impact
Agentic AI can change how any team, big or small, gets work done.
In large enterprises, one AI agent could handle everything from logging into apps, to transferring files, to creating reports, replacing dozens of repetitive manual tasks.
For small teams and even solo founders, the benefits are just as big. Narada AI is building its system to be accessible for everyone, not just enterprise clients.
So, in the future, we may not even need to use apps at all. You simply tell your AI agent what you want, and it will take care of the rest, without you ever needing to open a single dashboard.
📋 What to Watch
As this technology grows, one major misunderstanding is already rising that many people are confusing agentic AI with basic automation.
But the two are very different. Automation does what it’s told, agentic AI figures things out on its own. That makes them much harder to build and use at scale.
Successfully rolling out agentic AI also means rethinking how companies manage data and permissions. These agents need access, but with guardrails.
Guardrails means, it will make sure AI doesn’t say or do something harmful, protect sensitive data, and keep systems following the right rules.
Guardrails help build trust and make sure AI is safe, fair, and works as expected.
And then there’s the question of user experience:
If agents are doing all the work behind the scenes, will we even need traditional software interfaces anymore?
Narada’s team believes the future will be one where data and tasks stay in the background, and AI agents will handle everything on their own.
🚀 Today’s Trending AI Tools
Got a favorite AI tools, or anything useful?
Hit reply and share it with us, we might feature it in the next newsletter!
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