Over the previous couple of months, I’ve been neck-deep in one thing that’s altering how I take into consideration automation and workflows: Agentic AI.
This isn’t simply one other AI hype prepare. It’s an actual shift. A shift from writing code that blindly follows directions… to designing techniques that act, cause, and even improvise.
I didn’t begin with some grand AI imaginative and prescient. I simply had a workflow that saved breaking, and I needed a better strategy to repair it.
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The Drawback: My Workflows Had been Good, However Not Good Sufficient
Earlier this 12 months, I used to be automating a knowledge validation course of — one thing that ought to have been simple. We had APIs, a workflow engine, and a few threshold logic. All of it seemed good on paper.
However each time the context modified — new knowledge supply, schema drift, sudden anomaly — the system broke. And I used to be the one cleansing up the mess.
I discovered myself considering: If I have been doing this manually, I wouldn’t make these dumb errors. I’d pause, have a look at context, decide, possibly verify previous circumstances, then act. That’s when the concept hit me:
Why not construct one thing that works the best way I believe?
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Constructing My First Agent: Trial, Error, and an Surprising “Aha!”
So, I began small. I constructed a fundamental agent utilizing LangChain, added reasoning with Claude from Anthropic, and deployed it by way of AWS Bedrock.
I didn’t give it step-by-step directions. I gave it a purpose: monitor incoming knowledge, detect high quality points, and alert the appropriate staff with context.
Right here’s the wild half — it labored. Not flawlessly, however with sufficient intelligence to adapt. When a knowledge supply failed, the agent didn’t crash. It reasoned via options, tried once more, and documented its steps. It even supplied a attainable rationalization for the problem.
That was my “aha” second. This wasn’t only a script. It was a collaborator.
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From Static Workflows to Clever Brokers
Conventional workflows are like meeting traces. Clear, structured, and brittle. You make one change, and the entire line can halt.
However agentic techniques? They’re like staff members. You give them instruments, entry, and objectives — they usually determine the how.
For instance, I instructed one agent:
“If the sensor knowledge reveals an anomaly >10%, summarize it and alert the Ops staff.”
It did precisely that — cross-checked historic patterns, created a short report, and even urged a number of probably causes based mostly on related previous points. I hadn’t coded any of that explicitly.
It was weirdly satisfying.
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What I Realized Whereas Letting My Brokers Assume
Like something new, this wasn’t plug-and-play. I needed to learn to design for company as a substitute of designing for management. Listed below are a number of classes I picked up:
• Begin small. My first agent tried to do an excessive amount of and did none of it properly. A slender scope labored higher.
• Give them reminiscence. Stateless brokers are restricted. As soon as I added short-term reminiscence, efficiency improved dramatically.
• Assume like a supervisor, not a coder. I began writing directions like I’d to a junior teammate — not a script.
• Wrap with guardrails. I all the time preserve human oversight and charge limits. Simply because it will possibly act doesn’t imply it all the time ought to.
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The place This Is Headed: Brokers as Teammates
Proper now, I’m prototyping a set of role-based brokers:
• Information Steward Agent — tracks schema modifications and updates knowledge contracts
• Compliance Agent — flags dangerous knowledge utilization
• Value Optimizer Agent — screens cloud spend and suggests actions
They’re not good. However they’re bettering — quick. And what excites me is the concept someday quickly, I gained’t have to outline each rule. I’ll simply outline the intent.
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Ultimate Thought: From Automation to Autonomy
We’ve spent the final decade automating what we already perceive. Agentic AI flips that. It helps us deal with the unknown.
In case you’re constructing techniques the place context shifts, logic breaks, and handbook oversight drains your time — strive constructing an agent. Not only a workflow. Not only a script. A system that thinks slightly extra such as you.
It modified how I work. It’d do the identical for you.
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Thanks for studying! In case you’ve tried constructing agentic workflows, I’d love to listen to your story — or join and trade concepts.
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#ArtificialIntelligence #AgenticAI #WorkflowAutomation #LangChain #FutureOfWork
