9 Essential Artificial Intelligence Guides to Get the Most from AI 🤖
Unlock practical AI insights from industry leaders at OpenAI, Google, and Anthropic 📚
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Artificial Intelligence is no longer the future - it's the competitive edge businesses are leveraging right now. But with so many resources flooding the market, finding reliable, actionable insights can feel overwhelming.
I've handpicked nine essential guides from industry giants like OpenAI, Google, and Anthropic. Each guide distills proven strategies, real-world use cases, and step-by-step playbooks to swiftly integrate AI into your organization, whether you're a startup or a Fortune 500.
From mastering prompt engineering to building effective agents, this collection is your definitive roadmap for harnessing the full potential of generative AI today.
Let’s dive straight into it.
1. AI in the Enterprise by OpenAI
About: a 25-page white-paper for executives that distills what seven “frontier” companies learned while rolling out generative AI at scale.
What you’ll learn: a seven-part playbook (start with evals, embed AI in products, invest early, customise models, empower experts, unblock developers, set bold automation goals) illustrated with case studies from Morgan Stanley MS 0.00%↑, Indeed, and Klarna, and the metrics they achieved.
2. A Practical Guide to Building Agents by OpenAI
About: a hands-on, 34-page guide aimed at product & engineering teams taking their first steps with LLM-powered agents.
What you’ll learn: clear definitions of “agent” vs. ordinary automation; when to build one; the three design pillars (model, tools, instructions); orchestration patterns; guardrails & safety tips; plus Agents SDK code snippets you can copy-paste.
3. Prompting Guide 101 by Google
About: a quick-start handbook that teaches everyday users how to collaborate with Google Gemini while keeping data private.
What you’ll learn: the four-part prompt recipe (Persona + Task + Context + Format), 6 rapid-fire prompting tips, and dozens of role-specific examples for admins, HR, marketing, sales, and more - complete with iterative “before/after” prompt make-overs.
4. Prompt Engineering Guide by Google
About: a 65-page technical white-paper that goes deep on designing high-quality prompts for Gemini, GPT, Claude, and/or open-source models.
What you’ll learn: how temperature, top-K/P, and token limits really work; a catalogue of prompting techniques (zero-/few-shot, system & role prompts, Chain-of-Thought, Tree-of-Thoughts, ReAct, code-focused prompts); plus best-practice checklists and common pitfalls.
5. Identifying & Scaling AI Use Cases by OpenAI
About: a data-driven guide built on 300 enterprise implementations and 4,000 adoption surveys, aimed at leaders who need to choose the right first (or next) projects.
What you’ll learn: a three-step process (spot opportunities → teach six “primitives” → prioritise & roadmap), statistics that justify urgency, department-level workshop templates, and practical “anti-to-do-list” brainstorm exercises.
6. Building Effective Agents by Anthropic
About: a field-note from Anthropic summarising what works (and what doesn’t) after helping dozens of teams ship agentic systems.
What you’ll learn: when not to build an agent; the difference between workflows and agents; five composable patterns (prompt-chaining, routing, parallelisation, orchestrator-worker, etc.); and practical advice on frameworks, debugging, and cost/latency trade-offs.
7. 601 Real-World Google Cloud AI Use Cases
About: an April 2025 resource expanding Google’s original “101 use cases” to 601 examples, grouped by 11 industries and six agent archetypes.
What you’ll learn: a cheat-sheet of Customer / Employee / Creative / Code / Data / Security agent patterns, sector-specific highlights (e.g., Mercedes-Benz in-car assistant, Bell Canada SecOps), and cross-cutting insights like “RAG everywhere” and Workspace as the on-ramp.
8. Prompt Engineering Overview by Anthropic
About: the canonical Claude documentation page that explains why and when to tune prompts instead of fine-tuning models.
What you’ll learn: preconditions before you start (clear success criteria, evals), nine techniques ordered from simplest (“be clear and direct”) to advanced (long-context, XML tags), and links to interactive tutorials & a prompt generator.
9. Agents Companion by Google
About: a 76-page sequel to Google’s original Agents white-paper that acts as a full playbook for building, evaluating, and operating production-grade AI agents.
What you’ll learn: Google’s three-part agent definition (model, tools, orchestration), the discipline of “AgentOps” (monitoring, tool management, evaluation dashboards), evaluation metrics for trajectories and outcomes, multi-agent architectures, and the concept of Agentic-RAG with formal “contracts” for high-stakes workflows.
And that’s not even it…
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And that’s a wrap.
In 2023, I started sharing resources to help you become a more successful entrepreneur, investor, or business leader. I hope you will find these new resources valuable too.
Keep dreaming & keep building.
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This is very good - thanks
Thanks for posting this @Linas Beliūnas