The majority of companies are trapped in the past in terms of AI: they expect it to summarize emails or write their blog posts. Nevertheless, the new frontier is not about aid. It means independence. The AI agents are at such a level that they are no longer just a tool that is waiting and being told what to do, but they are dynamic systems that will guide, perform, and adapt in real-time.
It is turning out sooner than many companies think. Christophe Ploujoux, the co-founder and CTO of Blaxel, does not consider the trend to be a hype. He is creating cloud infrastructure assuming a situation where AI agents are the employees and not the helpers. And when your business is not getting ready to do it, you are already one step behind.
What Are the AI Agents, Exactly?
The term agentic computing is an apparent buzzword. However, there's a trick to it.
Essentially, an AI agent would be software that is run on some goal with little or no human intervention. It is not a machine, which merely follows instruction, it is a machine that invents its own plans, modifies them, and follows them through on the basis of a goal that is sought.
Traditional AI is similar to a very competent assistant: quick, selective, and prompt. Nevertheless, it awaits a cue. An agent is similar to an employee and at the same time knows the mission of the company and takes decisions on his own.
This disparity in autonomy is decisive. The advantage of AI agents is their ability to think, learn, and do. The days of “run this script” are over, and now the agents are equipped to complete multi-step and messy tasks, and a human is not watching every single step.
Why Current Infrastructure Is Not Prepared
The majority of the present-day cloud systems were not built to support autonomous systems. They were designed on fixed and predictable workloads. AI agents, in contrast, require more flexible, omnipresent environments that allow:
- Low-latency computation
- Cross-task consistency
- Sandboxed execution Secure Sandboxed
- Tool access on demand
- Stimulus, on-time communication
Suppose there is an AI agent that takes milliseconds longer than necessary to make a decision, and imagine that there are billions of AI agents out there making millions of decisions; multiply that amount of time by the scale of those decisions, and the result is a huge inefficiency in terms of cost as well as energy use. Christophe is blunt: “The boundaries of this system will not be technological; they will be physical ones.”
That is why services such as Blaxel are rewriting the architecture of the cloud. It is not only the scalability. It is about the efficacy of an unimaginable presence.
Everything Is Changing With the AI Agent Communication
The internet that people know was not constructed in the service of machines operating without people whether services or otherwise.
Not only are we having new protocols being developed but specifically for agents. The Agent-to-Agent (A2A) bridge Google introduced and the Model Context Protocol (MCP) Anthropic introduced are the first steps of a larger process. The technologies are overturning the traditional APIs, which are smarter, stateful, and goal-driven communications.
Christophe feels that we will retrofit some of the current protocols, but in the near future, we will just have to overhaul everything. Now suppose that there are micro-decisions and interactions occurring faster than trillions every single second. That is what the AI agents will require in the future.
Agent Security is Not Optional, but it is Fundamental
Security vulnerabilities go off the scale when software begins to act independently. When you have AI agents, you are not just protecting endpoints or firewalls as such. You have to control the behavior of software that writes its own code.
Important risks are:
Identity theft and ID theft
- Fix: Short-lived access tokens (e.g., Minds OAuth), restricted access control lists
- Short-lived, air-gapped sandboxes are the solution.
- Solution: Guardrails and input sanitization
Zero Trust is not a philosophy of this world; it is survival. Christophe underlines high observability and transparency. He says that you should never have a perception that your agent is a black box. It has to be thoroughly traceable in its decision-making.
The Business Applications in the Modern World
You do not necessarily need to transform your company in one night. Identify where in your team the majority of time is going on decision-based, repetitive tasks. And now add an AI agent.
These are two low-hanging fruits:
1. Customer Support
- And have an agent deal with both FAQs and triage support tickets. Complex cases can be dealt with by human agents. You will be able to make a higher speed of response and reduce the cost of operation, but you will not lose empathy.
2. Data Processing and IT Analysis
- Agents can clean, sort, and even visualize the data much more quickly than a human can use it in a wide range of fields, including financial anomaly detection and market research. It will release teams to perform interpretation instead of grunt work.
There are companies that question even its recruitment plans. Their questions before filling a post are: Can a part of this be done by an agent? In many cases the answer is yes.
Long Game: A New Role of Developers
The developers in this new world do not assemble the entire stack, but they make AI agents assemble it.
Yet, imagine this: An agent is given a task such as, detecting fraud patterns in last quarter financials. The agent will choose the right tool, kick off the environment, process the data, and spin everything back into the ground without people waiting for a DevOps engineer to perform any of the above activities.
That is the dream platforms such as Blaxel are creating. Not only human-friendly cloud services but also clean, modular APIs that AI agents can interpret and control.
Conclusively: AI agents are here to stay.
The emergence of AI agents is not speculative. It is occurring today.
The intelligent companies are not sitting around; they are testing, learning, and iterating in real time. They realize that this is not about introducing AI functions. It is about the redesign of the operations by utilizing the autonomy.
Failing to integrate this trend in case you are running a business means not only that you are losing effectiveness but also that you are going to become irrelevant.
It is no longer a question of whether the AI agents will alter your business. It is when.
And whether your business is going to be in the lead orcatch up.
