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Archive for the ‘Technology’ Category

When I was seeding the database for fintechbenchmark.com with Claude-generated or Openai-generated content, I needed structured data that matched my database schema. My format of choice was JSON, and my approach was straightforward:

  • Request JSON in the prompt
  • Provide an example of the desired structure
  • Parse Claude’s response—a text string containing JSON wrapped in markdown code blocks with triple backticks
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MCP (Model Context Protocol) solves a fundamental problem: how do you give an AI model access to external data like databases, files, or APIs without embedding everything in each request? Introduced by Anthropic in November 2024, MCP is now mature enough (15+ months old) for serious production use. Think of it like a USB-C port for AI—a standardized way to connect AI models to external systems.

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When we planned fintechbenchmark.com (currently in beta), we realized that AI wasn’t optional—it was essential. We could either embrace this revolution or watch competitors leave us behind.

We faced a classic startup dilemma: build a custom AI solution (expensive and slow) or use an off-the-shelf product to launch quickly and learn what our visitors actually need. We chose the pragmatic route.

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I am thinking about putting together a presentation on AI for the uninitiated. I thought a good starting point would be a SWAT analysis (Strengths, Weaknesses, Opportunities, Threats). It is a technique that is very useful in analysing new projects. A number of people have done this but why not have another go.

So I asked an AI (Claude).

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When I began the project I am currently working on (more details will be provided next month – probably), it was initially intended as a small test to determine the capabilities of AI.  Over the last six months it has turned into something that we might take further. 

But I hit a problem. As a little hobby project I chose the database I really really like – CouchBD.  CouchDB is elegant, simple yet very functional and efficient. Close to the perfect database management system (DBMS).  But to take it further I need to involve other developers and it turs out that CouchDB skills are few and far between. Truly it is the Betamax of DBMSs.

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My previous blog post outlines my success in converting a data structure definition from one format to another. Both ChatGTP and Gemini had a really good stab at it. The result was mainly accurate and extra information had been added for me. ChatGTP managed to make a mistake on the second attempt at the task, and when I asked it why, it used a completely made-up (and incorrect) rule about SQL Databases as an excuse. So Turing Test passed!

I gave it another task. Convert a routine from using the SQLite3 data base management system, to the higher performance MySQL. This is a straightforward, if tedious task. How did it do?

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In a previous post I showed how an AI system (ChatGPT) was an easy way of converting an SQL Schema to a JSON-Schema. It was very successful and could save hours of donkey-work when dealing with a legacy database. I am coding in TypeScript so I asked for a TypeScript schema as well. It also did that perfectly.

I asked Gemini to do the same job.

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I have been working on my hobby project, which is a generic database updating tool. It uses an extension of the JSON-Schema standard. But how do you deal with a new database from a legacy database.

I found a really simple solution, I asked ChatGTP to produce a JSON-Schema based on a database dump – which happily is a set of SQL statements.

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Lat week my wife’s desktop Outlook stopped working. It wouldn’t even start in safe mode. All the fixes we found on the web didn’t solve the problem. So the obvious solution was uninstall it and reinstall it. All our data is replicated on Outlook.com, so it would get downloaded from the Outlook server and she would be back in business.

We went into the control panel apps page. Because Outlook is part of Office 365 we ran the Office 365 uninstall and install programs. This didn’t solve the problem. OK – no problem we can just install Outlook as a stand-alone. This worked fine, the mails were all downloaded and we were back to normal.

Except we weren’t.

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In the past, election forecasts have been made on a country-wide basis. A sample of people is carefully selected to represent the population as a whole and they are asked who they will vote for. The percentages for each party are normally pretty good, but how do you convert that to seats in parliament? Just because a party gets x% of the vote doesn’t mean that get the same percentage of seats – a fact well known to the smaller parties. In the past there have been rules of thumb, but these are very crude.

Now there are forecasts by constituency based on a technique called MPR. This stands for “multi-level regression and post-stratification (MRP)”. How does this work?

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