@rubenhassid
taste knowing what to ask and what to throw away
Sentiment analysis: 70% support, 13% confront. Users favor Claude Opus for complex work; Grok for search, GPT-5.5 for images, Gemini for multilingual, Kimi for open-weight builds.
You're using the wrong AI for 80% of your tasks. Here's the 1-page map that picks the right one: 1. Claude Opus 4.7 for complex tasks. 2. Grok 4.3 to search. 3. ChatGPT (GPT-5.5) for images. 4. Gemini 3 Pro for multilingual. 5. Kimi K2.5 for open-weight builds. 1. Claude Opus 4.7 to write. ☑ Strongest reasoning available today. ☑ 1M token context (reads entire books, contracts). ☑ Cowork: reads your files, works like an employee. ☑ Start here: https://t.co/Vn60ElPZ2i Prompt: "You are my editorial partner. Read every .md file in this folder before you write a single word. Then draft a 900-word LinkedIn newsletter on [TOPIC]. Match the voice in voice .md. Use the structure in structure .md. Before writing, ask me 3 clarifying questions using AskUserQuestion. Do not start until I answer." 2. Grok 4.3 to search. ☑ Direct access to X data in real time. ☑ Lowest hallucination rate ever recorded (22%). ☑ Conversational, less corporate than other AI. ☑ Grok guide: https://t.co/77BmjbJREy Prompt: "You are a senior research analyst. I work as a [ROLE] in [INDUSTRY]. Search the web and X deeply. Give me: the 3 most important industry developments from the last 3 days, the 2 biggest threats to my role, 1 underrated opportunity most people miss. Minimum 8 diverse sources (news, X posts, reports, official sources). Cite every claim with a link." 3. ChatGPT (GPT-5.5) for images. ☑ Native 4K generation with accurate text. ☑ Handles complex multi-subject prompts. ☑ Edits existing images through prompts. Prompt (turn on Thinking first): "A cinematic 16:9 hyper-realistic shot of a laptop, slightly angled. The LinkedIn timeline on screen shows a post about [TOPIC]. Warm office lighting, coffee mug beside it, soft morning shadows. Photorealistic, no distortion, accurate text rendering on the screen." 4. Gemini 3 Pro for multilingual. ☑ Native fluency in 100+ languages. ☑ The only AI that reads YouTube links. ☑ Preserves idioms & cultural context in translation. ☑ Gemini guide: https://t.co/vgruCL3xUl Prompt: "Here is a YouTube link: [URL]. Pull the full transcript. Then give me: a 200-word summary in English, the 5 quotable lines (with timestamps) & a version of the summary translated into [LANGUAGE] that preserves idioms & cultural context (not a literal translation)." 5. Kimi K2.5 for open-weight builds. ☑ 1 trillion parameters, download and run it yourself. ☑ Coordinates up to 100 AI agents at once. ☑ 4–17x cheaper than GPT-5.4. Prompt (use Agent Swarm mode): "Act as a 5-agent research swarm for [TOPIC]. Agent 1: pull academic sources from Arxiv. Agent 2: scrape Reddit & forums for real user pain. Agent 3: competitive landscape from company blogs. Agent 4: fact-check every claim from the other 3. Agent 5: synthesize into one brief under 500 words with sources. Run in parallel." 6. Copilot? Delete it. I'll save you time. It's the worst of them all. You only use it because Microsoft forces you to.
Real-time analysis of public opinion and engagement
What the community is saying — both sides
knowing what you want doesn’t guarantee you’ll pick the right model.
many replies call the single‑tool default a habit that reduces outcomes.
even if you don’t switch models, knowing each model’s strengths improves how you frame tasks and prompts.
build a persistent constraint layer (permissions, recovery, scoping) so systems survive model churn.
practical payoff: efficiency and lower cost when you match task to model.
multiple replies report Claude as the go‑to for complex analysis and heavy lifting.
model rankings shift fast; treat recommendations as flexible, not permanent.
several replies ask for benchmarks or data rather than just anecdotes.
invest in durable expertise and judgment that transfer across changing tools.
some users claim GPT 5.5 outperforms traditional platforms, finding cases Lexis misses and improving research results.
relying on multiple separate models feels excessive, adding friction, cost, and coordination headaches.
mocking a “flowchart with 47 checkmarks” highlights how overly complex processes can become counterproductive.
Most popular replies, ranked by engagement
taste knowing what to ask and what to throw away
谁在用AI? 你说80%的人用错模型,其实是心在乱用。 复杂就找 Claude,搜索就找 Grok,画图就找 GPT,语言交给 Gemini,开源给 Kimi。 听起来很对,但这只是“器”。 禅里讲:器随心转,不是心随器走。 同一把刀,有人切菜,有人伤人。 同一个模型,有人放大认知
you can have perfect intent and still pick the wrong tool that's not a mindset problem - that's a missing map
thats why you learn the skill not the tool :)
And this is not pointed out. But you should use GPT 5.5 for legal research. It is by far the best. It finds cases that Lexis cannot.
imagine needing 5 AIs to get things done 🤔
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