Agent Smith

The world of Artificial Intelligence is moving at a breakneck speed. It feels like just yesterday we were marveling at simple autocompletes, and now we’re discussing AI agents capable of complex, autonomous tasks. Let’s take a moment to appreciate this incredible journey and peek into what the future might hold.

The Journey to Now

It wasn’t long ago that tools like GitHub Copilot, offering intelligent code completions, felt like the pinnacle of AI assistance in software development. This quickly evolved. Soon, Large Language Models (LLMs) weren’t just completing lines of code; they were writing entire scripts based on natural language prompts. Today, we’ve reached a point where LLMs are instrumental in developing whole applications. We’re in an era of “vibe coding,” where developers can describe the desired functionality and an AI can translate that vision into working code, significantly accelerating the development process.

The “Agents” Moment

We are now squarely in the “Agents” moment of AI. This signifies a shift from AI as a passive tool to AI as an active participant. Modern AI agents can perform tasks that were previously unimaginable. For instance, they can autonomously submit pull requests (PRs) to a code repository, complete with descriptions and justifications for their changes. Beyond coding, these agents are capable of conducting complex research on a given topic by autonomously navigating and synthesizing information from the web. This ability to act independently and achieve goals is what defines the current wave of AI.

AI in the Future Corporation

Looking ahead, the role of AI in corporations is set to expand dramatically. We can anticipate AI taking on significant responsibilities across various departments:

  • Design: AI could generate design mockups, suggest UI/UX improvements based on user data, and even create branding materials.
  • Marketing: AI agents might run entire marketing campaigns, from crafting ad copy and managing social media to analyzing campaign performance and optimizing for reach and engagement.
  • Analytics: Complex data analysis, identifying trends, and generating actionable insights will be tasks AI can perform with unprecedented speed and accuracy.
  • Accounting: AI could automate bookkeeping, financial reporting, and even assist in compliance and fraud detection.
  • Product: AI can help in identifying market needs, prioritizing features based on potential impact, and even generating initial product specifications.
  • Software Development: Beyond coding assistance, AI agents could manage entire development pipelines, from requirement gathering and coding to testing and deployment.

This leads to the concept of AI flywheels. Companies will leverage these AI systems to create a continuous loop of improvement. AI will analyze incoming data in real-time, identify areas for product enhancement or operational optimization, and then implement these changes. The ultimate aim is to drive key business objectives, such as improving customer conversion rates, reducing churn, or increasing overall efficiency, creating a self-reinforcing cycle of growth and refinement.

A Little Confession

Now for a little peek behind the curtain: this very blog post was drafted with the assistance of an AI agent. Specifically, I used “Google Jules” to help outline and write this content. You can learn more about such amazing tools at jules.google.com.

The age of agents is upon us, and it promises to be a transformative one.

Human Author’s Note

Here is the original prompt in Jules to generate the content above, no additional changes were made:

Write a blog post for today entitled "Agents Agents Everywhere" with filename 2025-05-22-agents-agents-everywhere.md. In this post do the following:

briefly outline the recent history of modern AI from simple autocomplete with github copilot, to using LLMs to write simple scripts, to using LLMs for developing entire applications and "vibe coding"
explain that we are in the "Agents" moment of AI where we can now deploy AI agents to perform simple tasks like submitting PRs on a code repository, or doing complex research on a topic by searching the web autonomously
project out into the future on how AI will assume multiple roles in a corporation, for example, design, marketing, analytics, accounting, product, software development. Companies will create AI flywheels to simultaneously analyze data and make product improvements in real time in order to obtain business objectives such as improving conversion or reducing churn
finally confess that this post was drafted using an agent, specifically google jules and link to jules.google.com