Guides

Practical AI build guides, updated for 2026.

End-to-end implementation guides for the AI systems teams are actually shipping: architecture decisions, the reference stack, evals, monitoring, rollout, the team you need, and the internal business case to get it approved.

Agents 64 min read

Agentic Workflow Automation in 2026: A Practical Implementation Guide

A working blueprint for automating multi-step business workflows with AI agents: the deterministic-vs-agentic boundary, orchestration and state, human checkpoints, evals, monitoring, rollout, the team, and the business case to get it approved.

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Coding 71 min read

AI Coding Agents in 2026: A Practical Implementation Guide

A working blueprint for deploying autonomous coding agents in a real engineering org: the agent loop, tool design, repo context, sandboxed execution, test-driven verification, guardrails, CI/CD, evals, and the business case.

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Document AI 68 min read

Intelligent Document Processing in 2026: A Practical Implementation Guide

A working blueprint for production IDP: the reference architecture, the stack decisions, classification and extraction, confidence thresholds and human-in-the-loop, the straight-through-processing rate, evals, monitoring, rollout, the team you need, and the business case to get it approved.

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HR 66 min read

How to Build an AI Recruiting Agent in 2026: A Practical Implementation Guide

A working blueprint for an AI recruiting agent in production: sourcing, resume parsing, matching and ranking, the agent loop, ATS integration, plus the bias, fairness, and compliance controls that high-risk hiring demands.

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RAG 51 min read

How to Build a RAG System in 2026: A Practical Implementation Guide

A working blueprint for retrieval-augmented generation in production: the reference architecture, the stack decisions, evals, monitoring, rollout, the team you need, and the business case to get it approved.

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Sales 66 min read

How to Build an AI Sales Agent in 2026: A Practical Implementation Guide

A working blueprint for an AI SDR in production: the agent loop, tool use over CRM and email, grounding in product truth, the autonomy and approval design, guardrails, evals, rollout, and the business case to get it approved.

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