Since my last post I’ve been using Claude Code more, and I’m pleased to report it works well and is genuinely powerful. As a confirmed control freak, I was also pleased to find that I stayed in control throughout.
Continue Reading »Posted in Still-coding, ai | Tagged ai, Technology, Claude, artificial-intelligence, llm, Claude code, Claude Cowork, Codex | Leave a Comment »
After spending a year building fintechbenchmark.com the traditional way—writing code, testing it, iterating—I’d grown comfortable with GitHub Copilot as my AI assistant. It delivered a significant productivity boost, though I’d learned when to trust it and when to ignore its suggestions and push forward on my own.
Then, weeks before our soft launch, our lead contractor dropped a demo of Google Antigravity (Project IDX) that made our entire workflow look like stone tools and campfire stories.
Continue Reading »Posted in ai, Still-coding | Tagged ai, Antigravity, artificial-intelligence, ChatGPT, Claude, Claude code, Coding risk management, Gemini, llm, OpenAI, Technology | Leave a Comment »
The assumption that bigger AI models always deliver better results is being quietly dismantled — and the economics behind this shift are compelling. Now we have Small Language Models (SLM) to distinguish them from Large language Models (LLM). How do we measure the size of a model?
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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
Posted in ai, Fintech, Still-coding | Tagged ai, artificial-intelligence, ChatGPT, Claude, json, llm, OpenAI, Technology | Leave a Comment »
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.
Continue Reading »Posted in ai, Database Management Systems, Still-coding | Tagged ai, artificial-intelligence, Database, Fintech, llm, MCP, Technology | Leave a Comment »
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.
Continue Reading »Posted in ai, Still-coding | Tagged ai, artificial-intelligence, Chatbase, Chatbot, ChatGPT, llm, Technology | Leave a Comment »
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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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.”
Continue Reading »Posted in History, Still-coding | Tagged ai, devops, GIT, GITHUB, Source control, Subversion, SVN, Technology | Leave a Comment »
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.
Continue Reading »Posted in Database Management Systems, Still-coding | Tagged ai, artificial-intelligence, CouchDB, MongoDB, node.js, NOSQL, programming, SQL, Technology, typescript | Leave a Comment »
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?
Continue Reading »Posted in ai, Still-coding | Tagged ai, Coding, javascript, programming, Technology, typescript | Leave a Comment »
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