In a comprehensive educational video titled "Agentic AI Explained: The Future of Software That Acts," Akhil from Monetizely takes viewers on a journey through 50+ years of software evolution, culminating in the emergence of Agentic AI. This video explores how software has transformed from centralized mainframes to autonomous systems that act independently, highlighting why this shift represents a fundamental change in how we approach software development and implementation.
The Evolution of Software: A 50-Year Journey
Akhil begins by placing Agentic AI in its proper historical context: "Agentic AI is not just another trend. It is the next chapter in a story that has been unfolding for over half a century, from mainframes to the cloud to software that now takes action on its own."
The evolution of software has unfolded across six distinct stages, each reducing human effort while increasing software impact:
1960s-1970s: The Mainframe Era
In the beginning, computing was highly centralized and dominated by IBM mainframes. These systems were massive, expensive, and operated on a time-sharing basis. As Akhil explains, "You did not own software. You leased hardware, and your program ran during your assigned window."
1980s-1990s: The PC Revolution
The emergence of microcomputers and personal computers changed everything. Software now came in physical boxes with floppy disks or CD-ROMs. Businesses relied on locally installed programs like Microsoft Word, Excel, and Lotus 1-2-3, with updates occurring perhaps "once a year if you were lucky."
Late 1990s-2000s: The SaaS Transformation
A pivotal moment came in 1999 when "Salesforce launched the first major SaaS product, software you accessed through a browser. No install, no CDs, just a monthly fee and a login." This shift was so revolutionary that Salesforce branded it with the slogan "No Software."
The SaaS model was further strengthened when "Amazon Web Services launched S3 and EC2, and suddenly anyone could rent compute power. Startups no longer needed servers. They could build directly in the cloud."
By 2014, SaaS had become so dominant that "SAP paid $8.3 billion to acquire Concur, a travel expense management SaaS. That was at that time the largest SaaS acquisition in history."
SaaS brought numerous advantages: scale, global access, automatic updates, and subscription pricing. It "democratized software delivery and made it possible to sell to millions of users, not just IT departments." However, it still relied heavily on human intervention.
2010s: The RPA Wave
To address the manual element in software processes, Robotic Process Automation (RPA) emerged. Beginning in 2001 when "Blue Prism coined the term," RPA allowed bots to automate repetitive tasks. Companies like UiPath and Automation Anywhere gained tremendous traction, with UiPath raising "over $500 million" in 2018 and going "public in 2021 with a valuation north of 35 billions."
However, RPA had limitations. As Akhil points out, "It was fast but fragile. Change one UI element, the bot failed. Feed it unstructured data, it got confused. Ask it to decide something, it simply could not. RPA could do but not think."
2022-2023: Generative AI Breakthrough
The landscape changed dramatically in November 2022 when "ChatGPT launched and suddenly AI could understand and generate human language at scale with fluency and context. It reached 100 million users faster than any other product in history."
Despite its power, even ChatGPT remained fundamentally reactive: "You give it a prompt, it gives you a response. It is impressive, but it still waits for you."
2024-Present: The Agentic AI Era
This brings us to the current evolution: Agentic AI, where "software doesn't just respond, it acts. It perceives the situation, it reasons through options, it executes steps across tools, and it learns from the result."
What Makes Agentic AI Different?
Akhil provides a clear distinction between generative AI and Agentic AI with this analogy:
"Generative AI is like a brilliant assistant who drafts an email when you ask. Agentic AI, that's the assistant who notices a meeting conflict, checks everyone else's calendars, suggests three new times, sends the email, tracks responses, and then updates the invite without ever even bothering you. That's not assistive, that's autonomous."
This shift is more profound than it might initially appear. While previous technological evolutions changed how software was delivered or what it could do, "Agentic AI is not just another UI change. It's a work model change… it makes software accountable. It takes ownership of outcomes within boundaries you define. And that changes everything."
Major Players Embracing the Agentic Shift
The move toward Agentic AI isn't limited to startups or theoretical discussions. Major industry players are already implementing this technology:
- "In September 2024, Salesforce launched Agentforce, a platform where enterprise customers can deploy AI agents inside their CRM and workflow tools."
- "Microsoft rolled out agentic functionality across Teams, Outlook, and Dynamics, integrating AI agents into scheduling, follow-ups, and task management."
- "Google launched Gemini 2.0, explicitly calling it built for the agentic era."
Additionally, specialized startups are focusing on specific applications: "Harvey AI is building legal agents used by top law firms. Unseen, Adept, Langroyd, all focused on agents, not just models."
Why This Matters for SaaS Companies and Executives
The emergence of Agentic AI represents a fundamental shift in how software creates value. While SaaS made software scalable, RPA made work faster, and generative AI made content smarter, "Agentic AI makes software accountable."
This evolution changes core aspects of the software business:
- How we build software
- How we buy software
- How we measure value
- How we manage risk
For SaaS executives, this isn't just another technology trend to monitor—it represents a potential paradigm shift in business models, customer expectations, and competitive landscapes.
What's Next?
Akhil concludes by promising to explore "the agents that already exist today from billion dollar legal platforms to startup analysts that replace entire back office teams" in the next episode, suggesting that Agentic AI is already moving from concept to practical implementation.
As the software industry enters this new era, understanding the full implications of autonomous software agents will be crucial for any executive looking to stay competitive in the rapidly evolving SaaS landscape.