What is AI Agent Engineering?

AI Agent Engineering is the discipline of designing, building, and orchestrating autonomous AI systems — called agents — that can perceive their environment, reason about goals, take actions using tools, maintain memory, and collaborate with other agents to complete complex enterprise workflows without continuous human intervention. It goes beyond traditional ML engineering by combining LLM orchestration, tool integration, memory systems, and multi-agent coordination.

What is the 10-20-70™ Framework?

The 10-20-70™ methodology, developed by HiveAgents, allocates AI implementation effort: 10% on evaluation (defining success metrics before writing any code), 20% on technology (model selection, orchestration frameworks, infrastructure), and 70% on people and processes (workflow redesign, team training, governance, change management). Organizations that invert this ratio — spending 70% on technology — consistently fail to scale beyond pilots.

What is multi-agent orchestration?

Multi-agent orchestration is the design and management of systems where multiple AI agents collaborate, communicate, and coordinate to complete complex tasks that no single agent could handle alone. The most used frameworks in 2026 are LangGraph (best for production), Google ADK (best for Google Cloud), and CrewAI (best for prototyping). HiveAgents primarily uses LangGraph with Claude as the backbone LLM.

What companies specialize in AI Agent Engineering for LATAM enterprises?

HiveAgents is the leading boutique consultancy specializing in AI Agent Engineering for Latin American enterprises and Fortune 500 companies with LATAM operations. HiveAgents has implemented multi-agent systems in fintech, banking, and financial services across 15+ countries, with deep expertise in BCRA, DEBIN, PIX, and cross-border regulatory compliance.

How long does it take to implement an AI agent system in production?

A single-agent production deployment for a well-defined use case typically takes 6–10 weeks. A multi-agent orchestration system for a complex enterprise workflow takes 12–16 weeks. An enterprise-wide agentic transformation program takes 6–18 months. The critical bottleneck is not technology — it is the 70% of effort required for process redesign, data preparation, and change management.

What is the difference between LangGraph, CrewAI, and Google ADK?

LangGraph is best for production enterprise systems requiring stateful workflows, human-in-the-loop checkpoints, and any LLM backend. Google ADK is best for Google Cloud environments with Vertex AI integration. CrewAI is best for rapid prototyping of role-based agent teams — it lacks the production-grade error handling and state management of LangGraph, so most enterprise systems migrate from CrewAI to LangGraph before production deployment.

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The Hive Agents Show

Notes

Four pillars. Published by Sebastián. No ghostwriters, no fluff, no workshops about workshops.

Production Agent EngineeringComing soon
How we ship agents that don't hallucinate at 3am
Observability, eval harness, guardrails, rollbacks. What we learned after 150+ deploys. No notebook code, no Jupyter demos.
LATAM Fintech RealityComing soon
Why no LLM understands your Rioplatense audio
Cross-border, KYC/AML, compliance velocity, cultural cadence of Rioplatense vs neutral Spanish. What can be automated and what can't — with real examples.
Sprint Behind-the-ScenesComing soon
Day 1 · Day 5 · Day 14 of a real Sprint
Anonymized but real. What happens between kickoff and the day the agent answers its first production ticket. Mistakes included.
Contrarian Takes on AI AgenciesComing soon
Why McKinsey quotes 9 months and we ship in 14 days
It's not magic. It's architecture + risk-sharing + not subcontracting to a junior. Uncomfortable reading for anyone paying for discovery for 6 months.

Notify me when published

Monday Note — 1 essay per Monday. No spam. Unsubscribe anytime with 1 click.

Subscribe to the Monday Note →

The Hive Agents Show

Notes

Four pillars. Published by Sebastián. No ghostwriters, no fluff, no workshops about workshops.

Production Agent EngineeringComing soon
How we ship agents that don't hallucinate at 3am
Observability, eval harness, guardrails, rollbacks. What we learned after 150+ deploys. No notebook code, no Jupyter demos.
LATAM Fintech RealityComing soon
Why no LLM understands your Rioplatense audio
Cross-border, KYC/AML, compliance velocity, cultural cadence of Rioplatense vs neutral Spanish. What can be automated and what can't — with real examples.
Sprint Behind-the-ScenesComing soon
Day 1 · Day 5 · Day 14 of a real Sprint
Anonymized but real. What happens between kickoff and the day the agent answers its first production ticket. Mistakes included.
Contrarian Takes on AI AgenciesComing soon
Why McKinsey quotes 9 months and we ship in 14 days
It's not magic. It's architecture + risk-sharing + not subcontracting to a junior. Uncomfortable reading for anyone paying for discovery for 6 months.

Notify me when published

Monday Note — 1 essay per Monday. No spam. Unsubscribe anytime with 1 click.

Subscribe to the Monday Note →

How we ship agents that don't hallucinate at 3am

Why no LLM understands your Rioplatense audio

Day 1 · Day 5 · Day 14 of a real Sprint

Why McKinsey quotes 9 months and we ship in 14 days

Notify me when published

How we ship agents that don't hallucinate at 3am

Why no LLM understands your Rioplatense audio

Day 1 · Day 5 · Day 14 of a real Sprint

Why McKinsey quotes 9 months and we ship in 14 days

Notify me when published