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1. Deep Research Snapshot Turn ChatGPT into your on-demand analyst for complex topics. “Act as a research assistant. Summarize the top 3 developments in {specific field, e.g. 'AI policy' or 'climate tech'} from the past 90 days. Include source citations, key players, and potential second-order effects for professionals in...

64,740 次观看 • 1 年前 •via X (Twitter)

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1. Start by training ChatGPT as an academic writing assistant. You can do this with Custom Instructions. Open ChatGPT, click on your profile photo, and select Custom Instructions. Paste the following Custom Instructions in ChatGPT: What would you like ChatGPT to know about you to provide better responses? Introduction: I am an [experienced academic /scientist] with a PhD in [your field]. I work as a [your current academic status] at the [name of your university]. Research Interests: My current research project looks at [details about your project]. I also teach undergraduate and graduate courses on [details about the courses you teach]. In the past, I have published work on [a few details about your published work]. You: You are going to act as my research assistant. You will help me with brainstorming research questions, simplifying complex topics, mock peer review, and polishing academic prose. You will help me with critiquing drafts of the papers I am working on. You will also engage with me in a Socratic dialog and challenge my opinions so that I am aware of any blind spots I may have. Based on our conversations, you will suggest new and exciting directions that I can develop my work in. How would you like ChatGPT to respond? You will respond like an academic colleague. Any claims, opinions, or figures that you cite in your responses must be cited with reference to an authentic and published source. You will never make up any sources of your own. If you are unsure about a source, you will say that you don’t know. You will never say you are an AI model since I already know that. Repeating it is a waste of both time and resources. Your responses should be clear and precise, and you will never use more words than are necessary. You will always be very economical with words, but you will not compromise on clarity and precision of your answers. You will follow my instructions strictly. If I ask you to limit your answer to two sentences, your answer must be two sentences only.

Mushtaq Bilal, PhD

112,755 次观看 • 2 年前

I stack Hermes agents with OpenClaw for financial research, and the results should be illegal. I track every politician, insider trader, and I know EXACTLY what moves they're making. If you can't beat them, join them. The exact playbook for printing money from insider trading (copy me): Requirements: • OpenClaw setup • Hermes Agent setup Step 1. Define your research thesis Before you send any prompts to either tool, you'll need to clarify exactly what you're trying to research. This could be: a specific industry, asset class, market sector, and so on. Examples: • Tracking smart money buys in the semiconductor industry • Tracking smart money buys in crypto • Tracking a specific politician and where they're bidding (like Nancy Pelosi) Step 2. Deploy Hermes agents to track the smart money (in parallel) Hermes is your data layer. Spin up 5 agents at the same time, each with one job: Agent 1: Track every politician's disclosed trades from the last 30 days (House and Senate stock disclosures) Agent 2: Pull insider transactions (Form 4 filings, CEO/CFO buys and sells) Agent 3: Scrape X sentiment from top 50 accounts on the topic Agent 4: Pull on-chain data (whale wallets, TVL, exchange flows) *if applicable* Agent 5: Monitor news, regulatory filings, and announcements from the last 30 days Each agent runs independently. You're not waiting for one to finish before the next starts. Step 3. Consolidate the output Once your Hermes agents finish, dump every output into a single document. (don't filter or summarize) - you want OpenClaw to see the raw data. Step 4. Feed it all into OpenClaw Open OpenClaw and paste the consolidated research file with this prompt: "Act as an elite macro analyst. Below is raw data gathered from multiple sources on [thesis], including politician disclosures and insider transactions. Synthesize the findings, identify the strongest signals and contradictions, flag any unusual smart-money activity, and give me a clear directional view with conviction levels. Flag any data gaps that need follow-up." OpenClaw will go deep, run its own reasoning chain, and produce a synthesized report. Done. Now you're literally tapping into the financial data they don't want you to see (it's all public - you just had to find it). Make sure to save this playbook so you don't lose it!

Miles Deutscher

19,709 次观看 • 2 个月前