Fifteen days ago, SpaceX completed the largest initial public offering in financial history, raising $75 billion at a $1.77 trillion valuation. On its first day of trading, the stock blew past $160. Within 48 hours it had nearly reached $225. Then, just as quickly, it fell — shedding more than 30% in a week, settling … Continue reading SpaceX at $153: Three Companies, One Stock, and a $1.2 Trillion Question

With 29 tools in my MCP server, it's still just a collection of tool execution. User experience is not good. Phase 1 (Tool Execution Model): classify_by_hierarchy() → returns 334 IDs Claude Desktop streams all 334 to chat (agonizing) No continuity → lose context, restart from scratch No branching → can't compare two weighting approaches No … Continue reading Upgrading My AI Platform

The main speed bottlenecks are from tool design, remote deployment, snowflake/API latency, and how much data the MCP server returns. Tool ambiguity: if tool names/docs are unclear, the aagent spends extra turns choosing tools, validating results, or calling exploratory tools like run_sql_query. Reponses verbosity: returning both final IDs and full audit detail every time makes … Continue reading User Experience of Index_Plugin: Prompt and Precise

As I grow older, I increasingly believe that the difference between people who live wise and prosperous lives and those who do not comes down to one thing: how many fundamental truths they have discovered, truly understood, and consistently acted upon. Knowledge alone is not enough. Many people encounter truth, but few believe in it … Continue reading First Principle: Achieve Crystal Clarity About Reality

An agent to reply messages from email and TEAM is not difficult to build. Once it's equipped with MCP servers, plugins and skills it could be powerful and actually useful. There is a question to answer: should this agent have an interface/UI? Maybe it could be floating there like many apps do, it does the … Continue reading An Agent to Reply Messages from Email and TEAM

Use claude [options] [command] [prompt], how? here are explanation with examples: Basic prompt (interactive vs. one-shot) # Start an interactive session claude # Start interactive with an initial prompt claude "explain the architecture of this project" # One-shot, print result and exit (non-interactive) claude -p "what does src/main.py do?" # Pipe input in cat error.log … Continue reading Use Claude Effectively

No vendor uses plain SQL as the primary interface for terminal users — they all have proprietary query languages optimized for financial workflows. Behind the scenes, they may use SQL databases, Hadoop, or columnar stores (e.g., kdb+, Arctic, Parquet) internally for storage and processing, then expose data through their own APIs. Bloomberg is the most "closed" — almost everything stays … Continue reading How FinTech Store and Process Their Data

Using Haiku is much cheaper than Opus, being constrained by budget quota each week, I tend to use Haiku most of the time, but for complex and/or important tasks, Opus is the go-to as it can solve problems that Haiku can NOT. Here is a real case I would like to share. Asking the same … Continue reading Ten Times More Cost of Opus to Haiku Is Worthy

Most people think index providers sell benchmarks. They don’t. The real business is: ETF product creation thematic intelligence commercialization speed distribution enablement institutional trust Legacy firms like S&P, MSCI, and FTSE win with brand and scale. Newer players like Solactive and Indxx win with: speed customization flexibility lower pricing faster product launches AI shifts the … Continue reading The Future of Indexing Is Not Benchmarking — It’s ETF Commercialization

AI-generated quarterly opportunity reports. Every quarter, generate this report for each client: market gaps trending themes competitive whitespace ETF flow anomalies issuer comparison underrepresented exposures AI relationship memory system. Institutional sales teams forget things constantly. AI should remember below and then suggest: best next action, best timing, likely objections and likely internal champions. This becomes … Continue reading AI-powered, Proactive ETF Ideation Partner