Developer's Notebook
A course on learning AI and putting it to work, plus quick-reference guides, standard operating procedures and working notes on web development, servers, Git, game development and CLI tooling.
Written from real work rather than assembled from search results. Every entry is something that was actually done, kept because it was worth writing down.
Learning AI
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Learn AI: where to start and how to get good at it
This is a course, not a list of links.
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What AI actually is
In one line: the AI you talk to is a program that is extremely good at guessing what comes next, and everything it can and cannot do follows from that one
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Who makes the models
In one line: there are about five names worth knowing, they leapfrog each other every few months, and the useful thing to learn is what KIND of choice you
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Choosing a model for the job
In one line: ask what it costs you to be wrong, and whether the text is allowed to leave your machine.
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Asking for what you actually want
In one line: most disappointing answers are not the model being stupid, they are a request that left out something the model had no way to know.
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What to be careful about
In one line: four things actually go wrong.
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Running AI on your own machine
In one line: you can download a model and run it on your own PC — free, private, no internet — and it is genuinely good enough for a great deal of everyday
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Letting AI use tools
In one line: give a model the ability to search, read files or run commands and it stops being a thing that answers and becomes a thing that does — which i
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Where to go next
In one line: you now know enough to use these tools well.
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Track: writing and thinking
Start here whatever your job is.
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Track: coding
This is the track where the tooling changes fastest and where the gap between people who use it well and people who use it badly is widest.
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Track: planning and running projects
The honest summary of this track: AI is very good at two specific parts of planning and actively harmful at a third.
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Track: research and learning
This is the track with the sharpest trade-off in it.
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Track: images, audio and video
The creative tools are the most visible part of AI and the most oversold.
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Track: everyday admin
The least interesting track and probably the one that gives you back the most hours.
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Track: building your own tools
This is the last track and the one the others lead to.
Web Development
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Verify Security Headers Are Actually Being Sent
Apache can accept a perfectly valid security configuration and deliver none of it.
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SOP: A Working Contact Form with PHPMailer and Gmail
A contact form that silently stopped sending, what actually broke, and the setup that survives a rebuild.
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Lighthouse: What Actually Moved the Number
Notes from tuning a static site, including the changes that measured as nothing.
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A Renamed File Can Break Your Site For Nine Months
A stylesheet was renamed.
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What Front-End Development Is, and Why It Matters
Front-end development is the part of a site a person actually touches.
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Setting Up a Development Environment From Scratch
A working environment, a codebase you will keep, and the commands that get Linux from a fresh install to ready.
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HTML: The Parts That Matter
A short reference for what HTML is actually doing, written for the point where you have opened a text editor and want to know what you are typing.
Software Engineering
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SOP: Restart, Verify and Diagnose a LAMP + Gunicorn Box
The commands, in the order you actually need them, for a box running Apache in front of a Python app.
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Git: The Commands That Matter, and the One to Never Run
A working reference, not a tutorial.
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What a Software Engineer Does, and Where to Start
Notes on what the job actually is, why I started with web development, and how to pick the next language rather than guessing at it.
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Time and Project Management for Programmers
Programming is about getting to a minimum viable solution quickly and then refining it.
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Steps Become Routines, Routines Become Systems
How a single repeated action turns into a capability you can point at a problem you have never seen before.
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Building a Routine That Survives a Bad Week
Most learning plans are written on a good day and then tested on a bad one.
AI Systems Integration
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Enabling the Google Cloud Natural Language API
The setup steps for the Google Cloud Natural Language API, from creating the project through to calling it from a FlutterFlow app.
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An AI App MVP in Ten Days with FlutterFlow
A ten-day plan for getting a working AI-backed mobile app in front of users, using FlutterFlow for the interface and a hosted model API for the intelligenc