LearnAI
Engineering-led writing on production AI.
Articles from AISD engineers and partners on what we've actually shipped. No 'thought leadership.' Just plain-English writing on agentic AI, agent architectures, and the workflow-automation platforms we use in production.
Topic
Industry
Pillar . 8 min read
What is agentic AI?
Agentic AI is software that uses an LLM to plan and take multi-step actions toward a goal, calling tools along the way. Definition, examples, architecture, and how it differs from generative AI.
what is agentic ai . 22k volume
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Primer . 6 min read
What is an AI agent?
An AI agent is software that uses a language model to plan and take multi-step actions toward a goal. Plain-English definition, the minimal pattern, real production examples.
what is an ai agent . 9.9k volume
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Guide . 10 min read
How to build an AI agent
Step-by-step guide to building production AI agents. Architecture patterns, tool integration, memory, evaluation, and deployment. From prototype to production.
how to build an ai agent . guide
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Explainer . 7 min read
How agentic AI works
The internals of agentic AI: planning loops, tool calling, memory, and self-correction. How agents decide what to do next and when to stop.
how agentic ai works . explainer
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Comparison . 7 min read
n8n vs Zapier vs Make
Engineering-led comparison of the three big workflow-automation platforms. Pricing, integrations, branching, AI features. Decision rules: when to pick each.
n8n vs zapier . workflow comparison
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Explainer . 6 min read
Agentic AI vs. generative AI
Generative AI produces content. Agentic AI acts - planning, calling tools, looping until a goal is met. Clear definitions, a comparison table, and when to use each.
agentic ai vs generative ai . 210 volume
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Deep dive . 8 min read
LLM orchestration patterns
Chain, router, parallel, map-reduce, and evaluator-optimizer patterns for production LLM systems. When to use each and how they compose.
llm orchestration . architecture patterns
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Comparison . 9 min read
RAG vs fine-tuning vs agents
Three ways to make LLMs useful with your data. Decision framework: when to retrieve, when to train, when to build an agent. Cost, latency, and accuracy trade-offs.
rag vs fine tuning . decision framework
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Deep dive . 7 min read
Eval harness for AI agents
How to build an evaluation harness for AI agents. Metrics, test cases, regression detection, and CI integration. The testing layer most teams skip.
ai agent evaluation . testing
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Security . 8 min read
Prompt injection defense
Attack taxonomy, defense layers, and practical mitigations for prompt injection in production AI systems. Input validation, output filtering, and architectural isolation.
prompt injection . ai security
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Hiring . 7 min read
How to hire AI engineers
What to look for, where to find them, interview structure, and comp benchmarks. Hiring guide for teams building AI products in 2026.
hire ai engineers . talent guide
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Analysis . 6 min read
Cost of building an AI agent
Real cost breakdown: LLM inference, infrastructure, engineering time, evaluation, and maintenance. Budget templates for MVP through production scale.
ai agent cost . budget planning
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Interactive tool
AI Agent ROI Calculator
Estimate the return on investment for deploying AI agents in your workflows. Input your team size, hourly cost, and task volume to get a custom projection.
ai roi calculator . interactive tool
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Deep dive . 9 min read
AI agent architectures
ReAct, plan-and-execute, multi-agent, reflexion, and tool-augmented patterns. When each works and production trade-offs.
ai agent architecture . react agent . multi-agent systems
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Deep dive . 8 min read
Agentic AI design patterns
Reflection, tool use, planning, and multi-agent collaboration. The four foundational design patterns for production AI agents with real examples.
agentic ai design patterns . reflection . planning . multi-agent
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Data-driven . 9 min read
Cost of LLM inference (2026)
Per-token pricing across Claude, GPT, Gemini, and open-weight models. The five cost levers (caching, routing, batch, output discipline, retrieval) that cut bills 60–95%. Self-host break-even math.
cost of llm inference . llm pricing . cost optimization
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Deep dive . 11 min read
Multi-agent systems in production
When multi-agent earns its complexity and when it doesn't. Five patterns that work, five anti-patterns to avoid, and the engineering discipline (typed messages, budgets, observability, end-to-end evals) that separates production from demo.
multi-agent systems . agent orchestration . production
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