An AI agent is a software system that combines three things:
<\/p>\n\n\n\n
![\"\"](\"\/wp-content\/uploads\/2026\/04\/image-1-1024x740.png\")
<\/figure>\n\n\n\nThink of it this way. The LLM (Large Language Model – could be GPT-4, Claude, Llama, Mistral) is the reasoning engine. It’s smart, but on its own it just generates text. The instructions give it a role – like “you are a travel booking assistant, always confirm budget before booking”. The tools give it hands – it can search the web, read files, call APIs, write to databases.
Together, these three things create something that can reason, act, and respond – not just chat.<\/p>\n\n\n\n
A Real Example<\/strong> (not a demo toy ) With an agent:<\/strong><\/p>\n\n\n\n That’s not magic. That’s a well-configured agent with the right tools and the right instructions. The LLM is doing the reasoning – deciding which tools to use, in what order, and how to interpret the results.<\/p>\n\n\n\n The Four Pillars of Agent Value<\/strong> The AI Workload Landscape<\/strong> Generative AI and Agents sit at the top of the stack because they orchestrate the others. An agent can call a vision model to analyse an image, then use NLP to summarise findings, then take an action in an external system – all in one workflow<\/em>.<\/p>\n\n\n\n Pros and Cons – Let’s Be Honest<\/strong> Cons:<\/strong><\/p>\n\n\n\n The Mental Model That Changes Everything<\/strong> What’s Next?<\/strong> Let me be honest with you. When most people hear “AI agent” they picture something from a sci-fi movie – robots making decisions, autonomous systems running wild. The reality is far more grounded, far more useful, and honestly more exciting because it’s real and available today.I’ve been working across cloud platforms for years, building everything […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"[]"},"categories":[6],"tags":[],"_links":{"self":[{"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/posts\/1468"}],"collection":[{"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/comments?post=1468"}],"version-history":[{"count":1,"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/posts\/1468\/revisions"}],"predecessor-version":[{"id":1473,"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/posts\/1468\/revisions\/1473"}],"wp:attachment":[{"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/media?parent=1468"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/categories?post=1468"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bogdanburuiana.com\/index.php\/wp-json\/wp\/v2\/tags?post=1468"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Here’s a scenario I often use in training because it clicks immediately:
User says:<\/em> “Find leads in the Pacific Northwest retail sector.”
Without an agent:<\/em> You get a bunch of suggestions on how to find leads. You go do the work yourself.
<\/p>\n\n\n\n\n
When I talk to clients about why agents matter, I break it down into four concrete business outcomes:
<\/p>\n\n\n\nBenefit<\/strong><\/td> What It Means in Practice<\/strong><\/td><\/tr> Enhanced decision-making<\/td> Analyses data across multiple sources to surface insights in real time<\/td><\/tr> 24\/7 availability<\/td> No lunch breaks, no sick days – operates continuously<\/td><\/tr> Automation of routine tasks<\/td> Handles repetitive work so your team focuses on strategy<\/td><\/tr> Scalability<\/td> Grows capability without headcount<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
That last one is the conversation-stopper in boardrooms. You can scale agent workloads without proportional cost increases. That’s a fundamentally different economics model than traditional software teams.<\/p>\n\n\n\n
Agents don’t exist in isolation. Here’s how they fit into the broader AI landscape:
<\/p>\n\n\n\n![\"\"](\"\/wp-content\/uploads\/2026\/04\/image-3.png\")
<\/figure>\n\n\n\n
Pros:<\/strong><\/p>\n\n\n\n\n
\n
Here’s what I tell everyone when they first encounter agents: stop thinking about software as a set of if\/else statements and start thinking about it as a team of specialists you can delegate to.
You don’t write code to tell a colleague exactly how to do their job. You give them context, expectations, and access to the tools they need. Then you let them work.
That’s exactly how agents work. And once that clicks, everything else falls into place.<\/p>\n\n\n\n
In the next article, I’ll walk through how to actually build one of these agents using Microsoft Azure AI Foundry – the infrastructure layer that handles state management, tool orchestration, and deployment so you don’t have to reinvent that wheel yourself.
If this was useful, share it with someone who keeps asking “but what is an AI agent?” – you’ll save yourself a 20-minute conversation.<\/p>\n","protected":false},"excerpt":{"rendered":"