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Posts Tagged ‘ai’

After retiring 15 years ago from professional software development, I had a clear picture of what source control should provide for a commercial development team:

  • Prevention of simultaneous edits – avoiding the chaos when two developers unknowingly work on identical code
  • Real-time visibility into who’s currently working on what files
  • Version metadata embedded in code files – a lifesaver when you find a piece of code and need to know what version it is
  • A comprehensive audit trail showing who modified which files and when
  • Automatic version incrementing for every modification
  • A single authoritative codebase representing the current production state
  • The ability to roll back to any previous version

When a business opportunity pulled me out of retirement and back into managing a development team, I naturally asked about source control. The universal response? “We use Git.”

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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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When I need some information I used to just type into Google and sort out what I want from the results. But a few months ago, got on the Bing Chat pre-release program It is a whole new way of finding information. Google’s version is now out called Bard. Both give excellent results, but my impression is that Bard is better but with a major drawback.

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