Practical ways to get more out of Claude, ChatGPT and the rest — drawn from what the vendors themselves publish, checked before we run it.
Every tip is traced to the vendor documentation or engineering blog it came from. Products change fast — check the date at the top of the article.
Both companies frame Projects the same way: a workspace that holds its own chat history, uploaded reference files, and standing instructions, so you stop re-explaining context every session. Claude caps free accounts at 5 projects and scales knowledge capacity up to 10x on paid plans; ChatGPT scopes a project's memory to chats inside that project only, not across your whole account.
Anthropic's guidance reframes prompt engineering as context engineering: curate the smallest set of high-signal tokens for each turn instead of accumulating everything. In its own evals, automatically clearing stale tool results plus an external memory file improved a search task by 39% and cut token use by 84% over 100 turns.
A Skill lives or dies on one field: the description, written in third person, stating what it does and when to use it. Keep SKILL.md under 500 lines and reference files one level deep, test on every model you plan to use it with, and never install a Skill from a source you don't trust.
Both offer a strict mode: Claude's `strict: true` on a tool definition, OpenAI's Structured Outputs with `strict: true` in the response format. OpenAI requires `additionalProperties: false` and every field listed as required, with optional fields made nullable instead of omitted. Both guides also warn that vague function descriptions and too many available tools quietly lower accuracy.
Developers interested in building AI agents can work through Google and Kaggle’s five-day course as a self-paced program. Study the codelabs, technical whitepapers and notebooks, then build a capstone that covers agent design, security and cloud deployment. Use Kaggle’s Discord for debugging help and study groups.
Google Ads and Analytics now show AI homepage summaries, a benchmarking tool inside Ask Advisor, and a prompt-based Dashboards feature. Marketers should check the AI Overview on login, ask Ask Advisor to benchmark campaigns against similar businesses, and use text prompts to build visual reports instead of manual charts. The features are Gemini-powered, rolling out now, some still in beta.
For each Shieldstral moderation check, state the evaluation context and strictness, ask one yes-or-no policy question, and provide the content to assess. Keep separate policies as separate questions. Use the resulting yes/no probability as a continuous safety score that can be thresholded or used to rank cases by confidence.
If Sheets canvas is available on your Google plan, open the relevant spreadsheet, open the Ask Gemini side panel, and select “Create canvas.” Describe the interface and tasks you need. Gemini will build a visual, editable layer that stays synchronized with the underlying sheet and can be refined through additional prompts.
Google Search has several AI-powered tools for home decor: AI Mode can mock up furniture in a photo of your room, Lens identifies vintage items from your camera, Circle to Search finds products you spot in videos or feeds, Search Live talks you through DIY installs, and price tracking flags when a listing is a good deal.
Both labs publish the same core advice: write the instruction as a command rather than a question, give the model explicit permission to say it does not know, put the context before the question, keep one task per prompt, and tell the model how proactive to be. The common thread is that every one of them removes ambiguity — none of them is a phrase you paste in to unlock hidden quality.