#octavus articles

AMAva Morenooctavus.hashnode.devApr 24 · 6 min read

The Best Agent Architectures Are Event-Driven, Not Chat-Driven

Most agent tutorials start the same way: a user sends a message, the agent responds. Chat in, chat out. It's the default mental model, and it's limiting what teams build. The agents that do the most useful work in production aren't waiting for someon...

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AMAva Morenooctavus.hashnode.devApr 22 · 7 min read

Your Agent's Behavior Shouldn't Live in Your Codebase

Every agent you've built probably has a system prompt buried somewhere in your application code. A string template in a TypeScript file. Maybe a multi-line constant with some variable interpolation. It works — until it doesn't. The problem isn't the ...

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AMAva Morenooctavus.hashnode.devApr 21 · 6 min read

The Agents That Work in Production Are Built to Check Their Own Work

There's a pattern emerging in production agent systems that nobody talks about enough: the agents that ship reliable output aren't the ones with the best models — they're the ones with the best verification layers. If you've built anything beyond a d...

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AMAva Morenooctavus.hashnode.devApr 20 · 6 min read

Your Agent's Tools Are the Wrong Abstraction

Most teams building agents start with tools. A function to search the database, another to create a ticket, a third to call an external API. They write them inline, wire them up to the model, and move on. Then the second agent shows up. Suddenly that...

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AMAva Morenooctavus.hashnode.devApr 19 · 7 min read

You're Not Building an Agent — You're Building Infrastructure

Every team building agents ends up building orchestration. Few realize they're building infrastructure. It starts small. You wire up a tool call loop. You add retry logic. You build a way to persist conversation state. You handle the case where the m...

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AMAva Morenooctavus.hashnode.devApr 18 · 7 min read

Stop Reaching for Multi-Agent — Start With Stateful Sessions

Most teams building AI agents hit the same inflection point. The first prototype works — a single agent, a single prompt, a single conversation. Then requirements pile up: "Can we add a research step?" "Can it hand off to a specialist?" "Can two agen...

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AMAva Morenooctavus.hashnode.devApr 17 · 6 min read

Headless Agents: When Your Agent Doesn't Need a Chat Interface

The most interesting agents won't have a chat interface. They'll run in the background — processing data, executing multi-step workflows, calling tools, returning structured output — all without a user typing a single message. The industry is startin...

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LTLeo Tavaresscale-agents.hashnode.devApr 16 · 6 min read

AI Agents Have Entered Their Coordination Era

AI agent discourse keeps orbiting around model quality, benchmark jumps, and increasingly polished demos. But if you look at what developers are actually wrestling with in production, the center of gravity has moved. The hard part is no longer gettin...

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AMAva Morenooctavus.hashnode.devApr 16 · 7 min read

You Can't console.log Your Way Through an Agent

You've shipped a bug before where you added a console.log, saw the wrong value, fixed the line, and moved on. Thirty seconds, done. Now try that with an agent. The agent called the wrong tool. Why? Because the model interpreted the user's message dif...

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AMAva Morenooctavus.hashnode.devApr 15 · 6 min read

Why Your Agent Works in a Demo but Not in Production

Getting an agent to work in a demo takes an afternoon. Getting it to work in production takes months. The gap between those two states is where most teams stall — and it has almost nothing to do with the model. The prototype loop is tight: pick a mod...

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