AI Expert

Guided reading library

Articles

Read the clearest practical guides without browsing everything at once. Pick a path, then move from concept to workflow to safer decisions.

Foundation

Build confidence with AI basics, prompting, privacy, hallucinations, and everyday use.
20 articles125 min total
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  1. 1What AI actually is (and isn't): a no-hype primer6 min read
  2. 2Your first hour with ChatGPT: a click-by-click walkthrough6 min read
  3. 3The seven things you can ask ChatGPT on day one6 min read
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Practitioner

Learn workflows for meetings, writing, research, no-code tools, and repeatable business tasks.
22 articles169 min total
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  1. 1The anatomy of a prompt: role, context, task, constraints, format8 min read
  2. 2Stop prompting once: the iterative conversation method8 min read
  3. 3Picking the right model for the job: a 2026 decision cheat sheet7 min read
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Builder

Go deeper into agents, RAG, MCP, structured outputs, evals, APIs, and local AI.
43 articles483 min total
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  1. 1Building reusable prompt libraries: from snippets to shared templates11 min read
  2. 2Multi-tool workflows: combining ChatGPT, Claude, Perplexity, and Notion11 min read
  3. 3Chain-of-thought, self-critique, tree-of-thoughts — when to use each10 min read
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Strategic

Cover governance, EU AI Act readiness, build-vs-buy decisions, ROI, and private AI choices.
11 articles109 min total
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  1. 1Designing a team AI adoption playbook11 min read
  2. 2The AI marketing stack: content, SEO, social on autopilot10 min read
  3. 3The AI sales stack: lead enrichment, personalization, follow-up at scale11 min read
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10 min read

Evals for non-engineers: know if your AI workflow is getting better or worse

Evals — systematic measurement of AI output quality — are usually treated as an engineering concern. But every team running AI workflows needs them, and the basics are accessible without code. The how-to.

Measure whether an AI workflow is improving by using examples, rubrics, and regression checks.

IntermediateAI for Business
11 min read

Designing a team AI adoption playbook

Most teams fail at AI adoption not because the technology doesn't work, but because the rollout doesn't. A practical playbook: how to pick use cases, train people, set policy, measure impact, and avoid the common failures.

Create a team adoption plan that covers use cases, training, governance, measurement, and rollout risk.

IntermediateAI for Business

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