A practical guide from someone who's spent hundreds of hours pushing AI to its limits
AI (Artificial Intelligence) refers to computer systems that can perform tasks that typically require human intelligence. The AI tools most people use today are Large Language Models (LLMs) - systems trained on massive amounts of text to understand and generate human-like responses.
Think of it like this: AI isn't magic, and it's not sentient. It's pattern recognition at scale. It's seen millions of examples of how humans write, reason, and solve problems, and it uses those patterns to help you with your tasks.
What AI can do well: Writing, analysis, brainstorming, research synthesis, explaining concepts, coding assistance, and strategic thinking.
What AI struggles with: Visual design (often looks dated), consistent creative prose, understanding brand subtleties, and anything requiring true originality rather than pattern-matching.
Different AI tools have different strengths. Here's how to think about the major players:
Best for: Writing, brainstorming, daily casual work. Has memory across conversations. Great for social posts, emails, blog content, and creative ideation. Feels like your everyday coworker.
Best for: Building things, coding, complex documents, detailed analysis. Excellent at creating files, websites, spreadsheets, presentations. Your technical specialist for when you need to make something.
Best for: Quick lookups, fast reference, Google workspace integration. Good for speed when you need a quick answer or Google Docs/Sheets help.
Best for: Research with citations. Gets real-time web info and cites sources. Use when you need current, credible information with attribution.
Best for: AI image generation. Create custom visuals, mockups, artwork from text prompts. Quality improving constantly.
Best for: Coding in your IDE. Autocompletes code, suggests functions, helps debug. Essential for developers.
Best for: Workspace integration. Write and brainstorm directly in Notion without leaving your workspace.
Don't just stick to one tool. Use ChatGPT for writing and daily brainstorms, Claude for building websites and complex documents, Gemini for quick Google lookups. Add specialized tools like Perplexity (research), Midjourney (images), or Copilot (coding) as needed.
The quality of AI output depends heavily on the quality of your input. Here's what actually works:
"Write something about productivity"
"Write a 500-word LinkedIn post about productivity tips for product managers, focusing on stakeholder management"
Show AI what you want. If you're asking for content in a specific style, paste an example. If you want analysis in a certain format, show the structure.
Don't make AI guess. Tell it who you are, what you're trying to accomplish, and any relevant background. This is why the context template works so well.
First drafts from AI are rarely perfect. Ask for revisions: "Make it more concise," "Add more data," "Change the tone to be more casual."
Upload a context document at the start of conversations. Include your background, goals, working style, and current projects. AI quality improves dramatically when it has this foundation.
Want more prompt examples?
Ever notice AI conversations sometimes hit a wall? That's because of tokens and memory limits.
Tokens are how AI processes text. Roughly speaking, 1 token ≈ 0.75 words. Every message you send and every response AI generates uses tokens. Most AI tools have limits on how many tokens can be in a conversation at once.
Long conversations eventually hit a breaking point. Push too hard in one session and AI starts forgetting context, making mistakes, or degrading in quality.
AI has a breaking point. If you notice responses getting worse, quality declining, or AI "forgetting" things you discussed, it's time to start fresh. Save your context and begin a new chat.
RAG sounds technical, but it's simple: it's how AI accesses information beyond what it was trained on.
AI models are trained on data up to a certain date (their "knowledge cutoff"). They don't know what happened after that, and they can't access your company's internal docs, your personal files, or current web information - unless you give it to them.
RAG lets AI pull in additional information when answering questions:
Context management isn't just a personal productivity hack - it's essential business infrastructure. Companies that figure out how to systematically provide AI with the right information will win. Those that just buy AI tools without managing context will struggle.
Example: Instead of asking AI "What are our Q3 sales numbers?" and having it guess, upload your Q3 report first. Now AI can reference actual data.
Strategy, analysis, professional writing, learning new concepts - these are AI's sweet spots. Use it for synthesizing information, exploring ideas, and producing first drafts.
Visual design often looks stuck in 2005. Creative writing quality is inconsistent - it's great at structure and plotting but can be terrible at actual prose. Instagram-ready content? Not yet.
Just like you wouldn't ask your designer to write SQL queries, don't expect every AI to excel at everything. Learn which tool is best for which task, and switch between them strategically.
AI doesn't magically know your company's history, your product details, or your communication style. You have to provide it. Systematically. With structure. The better your context management, the better your results.
Having an AI "coworker" available anytime for brainstorming, feedback, and problem-solving changes how you work. You think bigger because you can process ideas faster. You're less stuck because you always have someone to bounce ideas off.
AI isn't about replacing human work - it's about augmenting it. Use it to think faster, draft better, and explore more options. But know its limits, manage context carefully, and always bring your human judgment to final decisions.
Download the context template to maintain continuity across AI sessions.
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