# learningai.blog
> Learning, building, and experimenting with artificial intelligence
Public Ghost content for AI and LLM tooling. This file includes a bounded export of public pages first, then recent public posts.
Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`).
## Pages
### About this site
URL: https://www.learningai.blog/about/
Last updated: 2026-07-15T19:41:20.000Z
Learning AI is an occasional build journal by **Richard Linnington**, a secondary maths teacher and the creator of [maths tutor portal esheets.io](https://www.esheets.io/?ref=learningai.blog)

I started this site in February 2026 to document what happened when I began using artificial intelligence not simply to answer questions, but to help me build things.

Most of those things have been connected with mathematics education: self-marking worksheets, classroom games, visualisation tools, financial-literacy activities and a teacher portal for setting work and recording results. ESHEETS is where the finished resources live. This site is where I occasionally write about how they were made.

## A little background

Before becoming a teacher, I worked in front-end web development. I was comfortable with HTML, CSS and JavaScript, but much of what I wanted to build for ESHEETS required knowledge outside my old skill set: databases, authentication, server hosting, deployment, payments and automation.

AI has helped me bridge those gaps.

It has not produced a functioning educational platform while I sat nearby drinking coffee. There have been broken builds, poor ideas, database errors, awkward interfaces and features that appeared perfectly sensible until I tried to use them with actual students.

AI makes ambitious projects more achievable. It does not remove the need for judgement, testing or a willingness to start again.

## What this site is for

This is not an AI news website, a prompt library or a promise that artificial intelligence will transform your life before breakfast.

I write when I have something concrete to report: a project built, a problem solved, an experiment that worked or a mistake worth admitting to.

The posts will mainly be about:

- building educational websites and classroom tools;
- using AI for coding, design and problem-solving;
- what happens when those tools meet real teachers and students;
- the practical limitations of working with AI;
- lessons learned while developing ESHEETS.

There is no fixed publishing schedule. Maintaining one website already keeps me adequately occupied.

## About ESHEETS

ESHEETS is a GCSE mathematics website containing [self-marking worksheets](https://www.esheets.io/maths/?ref=learningai.blog), [games](https://www.esheets.io/battles/?ref=learningai.blog), [puzzles](https://www.esheets.io/puzzles/?ref=learningai.blog) and [visualisation tools](https://www.esheets.io/tools/?ref=learningai.blog). It also includes a lightweight homework system through which teachers and tutors can set activities and view submitted results.

Most of the experiments discussed here eventually appear there in some usable form.

## Keep in touch

You can subscribe to receive an email when I publish something new.

Emails will be occasional. Your inbox is in very little danger.
## Posts
### From paper grids to online battles: how AI helped me build maths games for esheets.io
URL: https://www.learningai.blog/from-paper-grids-to-online-battles/
Last updated: 2026-07-17T23:17:15.000Z
The games on [esheets.io](https://www.esheets.io/?ref=learningai.blog) began with some very old technology: sheets of paper, pencils, dice and two students arguing about whether a move was legal.

Long before I attempted anything resembling an online multiplayer game, I was interested in the classic pen-and-paper games that occasionally appear in maths books, puzzle collections and teacher-training sessions. Many have very simple rules, require almost no equipment and contain far more strategy than their appearance suggests.

My first aim was not particularly ambitious. I wanted to turn some of these games into small browser versions that students could play on a shared iPad or laptop.

Each game was built as a single HTML file, with the HTML, CSS and JavaScript bundled together. There was no database, no login system and no multiplayer server. Two students sat beside each other and passed control of the same device.

That apparent limitation was partly deliberate. Students huddled around one screen still talk, negotiate, gloat and accuse each other of cheating. As a teacher, I am not entirely convinced that every educational activity is improved by placing each child behind a separate device.

## Recreating classic strategy games

That early approach gradually produced the collection now found on the ESHEETS [Battles page](https://www.esheets.io/battles/?ref=learningai.blog).

Some games are extremely quick. In [Teeko](https://www.esheets.io/teeko/?ref=learningai.blog), players first place four counters and then move them around the board, trying to create either a line of four or a small square. The rules can be explained in a minute, but the movement phase introduces enough strategy to make repeat games worthwhile.

[Neutron](https://www.esheets.io/neutron/?ref=learningai.blog) is more demanding. Players manoeuvre their own pieces while trying to move a neutral piece—the Neutron—into their home row or trap it so that their opponent cannot move it. It is the sort of game where a move that appears harmless can turn out to have ended the contest several turns later.

Then there is [Pig](https://www.esheets.io/pig/?ref=learningai.blog), which has been particularly popular with my students. Players repeatedly roll dice to build a temporary score, but risk losing the entire turn if they roll a single one. They can stop and bank their points at any time.

The arithmetic is straightforward. The real mathematics lies in the decision-making: how much risk is sensible, whether the current score is worth protecting and whether your strategy should change when you are behind. Students rarely describe this as a probability lesson, which is probably part of the reason it works.

[Corners](https://www.esheets.io/corners/?ref=learningai.blog) takes a different idea. Players place dots and attempt to identify four that form the corners of a square—including squares tilted diagonally across the grid. It is a game of visualisation, spatial reasoning and noticing structures before your opponent does.

These games are not disguised worksheets. Some contain very little formal calculation. What they do encourage is mathematical behaviour: planning, pattern recognition, logical deduction, spatial awareness and adjusting a strategy when the evidence changes.

## From paper activity to miniature simulation

The [Puzzles section](https://www.esheets.io/puzzles/?ref=learningai.blog) developed alongside the two-player games, although these activities were designed mainly for individual students.

The most successful example has been [Zoo Mogul](https://www.esheets.io/zoo-mogul/?ref=learningai.blog).

The original idea came from a pen-and-paper activity I encountered while training to become a teacher. Students had to plan a zoo while working within a budget. I always liked the premise because it gave money calculations a purpose: the numbers represented decisions rather than isolated exercises.

The browser version gradually became something much more elaborate. Players now build paths, choose animals, add facilities, set ticket prices and attempt to balance income against running costs. Visitor happiness, animal welfare, cleanliness and reputation all affect the outcome.

A zoo containing the most expensive animals is not necessarily a successful zoo. Visitors need to reach the attractions. Toilets and bins matter. Food stalls can generate income while also creating more litter. An impressive expansion can become a financial disaster if the daily costs are ignored.

Zoo Mogul is now the most popular page on my website. That was not something I predicted when I began converting an old teacher-training activity into a browser game. It is also a useful reminder that educational games do not need extraordinary graphics or complicated controls. A strong underlying idea can do most of the heavy lifting.

Another experiment was [Escape from Pentades](https://www.esheets.io/escape-from-pentades/?ref=learningai.blog), a graphical maths adventure in which students travel across five islands representing different areas of GCSE mathematics.

It sits somewhere between a revision activity and an old-fashioned adventure game. Students solve mathematical problems to progress, but the questions are part of a larger setting rather than presented as another page of exercises. The graphics are hardly going to trouble a modern games console, but the format creates curiosity: students want to find out who they are going to meet next.

## The jump to online multiplayer

For a long time, the shared-device model was enough.

A single browser only needs to maintain one version of the game. It always knows whose turn it is, which moves have been made and whether somebody has won. Even when the code becomes untidy, everything is happening in one place.

Online multiplayer changes that.

Once players are using separate devices, both screens must agree about the state of the game. A move made on one device needs to appear on the other. The game needs some way to place players together, decide who moves first and prevent both players from acting at once. You also have to consider refreshes, abandoned games, invalid moves and what happens when somebody’s connection briefly disappears.

This was where I began using Google Antigravity more seriously. Antigravity is an agentic development platform that can work across a code editor, terminal and browser rather than merely suggesting the next few lines of code.

I used it first to turn [Ultimate Noughts and Crosses](https://www.esheets.io/ultimate-noughts-and-crosses/?ref=learningai.blog) into a game that could be played remotely.

Ultimate Noughts and Crosses is already more complicated than the ordinary version. It contains nine smaller boards arranged inside one large board, and the square chosen by one player determines which small board the opponent must use next. That made it a useful test: the game has a clear state, strict turn rules and plenty of opportunities for two devices to disagree.

[Dandelions](https://www.esheets.io/dandelions/?ref=learningai.blog) followed. In that game, one player places flowers while the other selects wind directions that spread seeds across a grid. The two players have different roles, different controls and different winning conditions, making it another useful multiplayer experiment. Both games can now be played locally on a shared screen or remotely on separate devices.

The process was not a matter of typing “make this multiplayer” and going for a cup of tea.

I had to become much more precise about the rules. Which device is allowed to change the game state? What information needs to be stored? What happens if a move arrives twice? When is a board considered complete? What should a returning player see after refreshing?

The AI could write large amounts of code, investigate bugs and make changes across several files. My job increasingly became defining the behaviour, checking the result and finding the situations neither of us had considered.

That is an important part of learning to work with coding agents. Better code often begins with a better specification.

## Inventing Maths Melee

After reproducing classic games and building the first online versions, I became confident enough to attempt something original.

[Maths Melee](https://www.esheets.io/maths-melee-online/?ref=learningai.blog) is loosely based on the classroom activity usually known as the Pirate Game. Students answer mathematics questions, earn points and then decide whether to protect what they have or risk it in search of something better.

Correct answers allow players to take an action. They may bank their points safely or uncover a tile that could provide a reward, a penalty or an opportunity to interfere with another player. Shields, thefts, mirrors, swaps and wildcards create enough uncertainty to ensure that the student with the strongest mathematics does not automatically win.

That balance matters. The maths must remain meaningful, but a classroom game becomes fairly dreary if the result is determined solely by who answers the most questions correctly.

The first version supported two to four players sharing one device. The online version allows players to join from separate devices and supports larger games. It involved far more development than the early single-file battles, but it grew directly from them: simple rules first, then interaction, then enough chaos to make students ask for another round.

## What the AI contributed—and what it did not

AI coding tools have changed what I can realistically attempt.

I am a maths teacher with previous front-end development experience, not a professional games studio. Before tools such as Antigravity, I could build a standalone browser game, but an online multiplayer system would probably have remained on the list of things I might tackle one day.

The AI reduced the distance between the idea and a working prototype. It could create infrastructure, trace code across files and attempt technical work that would have required me to spend days reading documentation before I could even begin.

It did not decide which games were worth making.

It did not know that Pig would work particularly well with my students, that shared-device play could be more sociable than individual screens, or that an old zoo-budgeting activity deserved to become a miniature management simulation.

It also did not remove the need for testing. AI-generated games can contain rule errors, interface problems and impressive-looking features that are not actually enjoyable. Students remain brutally efficient quality-control testers. They will find the loophole, discover the button that should not be clickable and announce that the game is boring long before a formal test plan reaches the same conclusion.

The most useful combination has been teacher judgement, enough technical understanding to challenge the output, and an AI agent capable of doing much of the implementation work.

## A slightly unruly collection

ESHEETS now contains a growing and slightly unruly mixture of [two-player battles](https://www.esheets.io/battles/?ref=learningai.blog), [one-player puzzles](https://www.esheets.io/puzzles/?ref=learningai.blog), simulations and multiplayer games.

Some are careful digital versions of established pen-and-paper games. Some are classroom activities that expanded far beyond their original form. Others are experiments that would probably never have existed without AI-assisted development.

They are not intended to compete with commercial video games. Their job is smaller and, for me, more interesting: give students a reason to calculate, plan, take risks, spot patterns and talk about mathematics.

I do not think AI has magically turned me into a game designer. It has, however, made it much easier to discover whether an idea in a teacher’s notebook can become something students genuinely want to play.
### Five Months Later: What I Actually Built with AI
URL: https://www.learningai.blog/five-months-later-what-i-actually-built-with-ai/
Last updated: 2026-07-15T19:48:38.000Z
On 21 February, I published a post about what I had been building with artificial intelligence.

I ended it with a fairly specific intention:

> “The next stage is structured progress tracking.”

Then I stopped writing.

This was not because I had lost interest in AI. The more mundane explanation is that maintaining two websites felt like one website too many. [ESHEETS](https://www.esheets.io/?ref=learningai.blog) was growing, there was always something else to fix, and writing about the work kept losing out to doing the work.

Five months later, it seems reasonable to check whether I ever built that progress-tracking system.

I did.

## From worksheets to a homework system

At the time of my last post, ESHEETS was mainly a collection of interactive maths worksheets. Students could answer questions, receive immediate feedback and generate more practice without waiting for somebody to mark a piece of paper.

That part worked well, but each worksheet was still largely an isolated activity. A student could complete it and see a score, but the result did not go anywhere useful.

The new teacher portal changes that.

A teacher or tutor can now create a class, choose a worksheet and generate a short task code. Students enter the code, complete the activity and submit their results. The teacher can then see who has attempted the work, what they scored and whether they have subsequently improved.

There are no student accounts to create and no passwords for children to forget. Results can be filtered and exported, and personal-best scores are recorded alongside the latest attempt.

It is not intended to replace the large platforms used by schools. It is a much smaller system for teachers and private tutors who want to set a piece of interactive maths work and see what happened afterwards.

In other words, it is more or less the thing I said I wanted to build in February.

## AI did not build it while I made a cup of tea

Descriptions of AI-assisted development often skip the untidy middle.

You describe an idea to an AI model. Some code appears. The music swells. A fully functioning technology company emerges before lunchtime.

That has not been my experience.

AI has written a considerable amount of code for ESHEETS, but the difficult part is rarely producing the first version. The difficult part is deciding exactly what the system should do.

Should students need accounts? How should teachers identify them? What happens when two students enter the same name? How long should results be stored? What should happen when a class is archived? Can the whole thing be used comfortably on an iPad? What happens when somebody refreshes the page halfway through?

These decisions are not especially glamorous, but they determine whether a classroom tool is useful or merely impressive in a screenshot.

There have also been failed deployments, database problems, broken layouts and features that worked perfectly until an actual person tried to use them. AI helps me understand and repair these problems, but it does not prevent me from creating them.

My role is still to decide what is worth building, test it in realistic conditions and notice when the proposed solution is technically clever but educationally daft.

## More than 200 worksheets

The underlying collection has continued to grow as well.

ESHEETS now contains more than 200 [self-marking maths worksheets](https://www.esheets.io/maths/?ref=learningai.blog), organised across the main GCSE curriculum areas. Recent additions have included probability trees, probability scales, two-way tables, composite bar charts, sectors, equations with unknowns on both sides and graphical solutions of quadratics.

The more important development, however, has been behind the scenes.

The worksheets increasingly use a shared framework rather than each page behaving like a separate miniature website. This means improvements to scoring, printing, navigation and mobile layouts can be made across the collection instead of being repeated manually on hundreds of pages.

This is one of the less visible benefits of working with AI. It becomes possible to tackle the tedious structural jobs that a lone developer might otherwise continue avoiding for several years.

I still avoid some of them, naturally. Just fewer than before.

## Games, simulations and visual tools

The site has also moved beyond conventional worksheets.

I have built [mathematical visualisation tools](https://www.esheets.io/tools/?ref=learningai.blog), including one for exploring the [ambiguous case of the sine rule](https://www.esheets.io/sine-rule-ambiguous-case-visualiser/?ref=learningai.blog). Students can alter a triangle and see why the same information can sometimes produce two possible answers.

Other tools explore geometrical situations such as a sheep tethered to a building or attached to a sliding ring. These are fairly niche things to build, which is precisely why AI helps. A visual idea that might once have been too time-consuming to justify can now be tested relatively quickly.

I have also produced larger classroom activities.

[Trip Tycoon](https://www.esheets.io/trip-tycoon/?ref=learningai.blog) asks students to manage the budget for a school trip over several days. [Bills & Buffers](https://www.esheets.io/bills-and-buffers/?ref=learningai.blog) gives them an income and requires them to survive three months of rent, bills, subscriptions and unexpected expenses. And [Zoo Mogul](https://www.esheets.io/zoo-mogul/?ref=learningai.blog) (where you design and operate a for-profit zoo) remains the most popular.

These began as activities for financial-literacy lessons at school. They are not attempts to disguise ten arithmetic questions with a picture of a wallet. The decisions, consequences and uncertainty are part of the mathematics.

There are multiplayer games too, including [Maths Melee](https://melee.esheets.io/?ref=learningai.blog), along with [puzzles](https://www.esheets.io/puzzles/?ref=learningai.blog) and [end-of-term activities](https://www.esheets.io/end-of-term-maths-activities-2026/?ref=learningai.blog). Some have attracted considerably more search traffic than I expected. [Dandelions](https://www.esheets.io/dandelions/?ref=learningai.blog), a small strategy game that I nearly regarded as an eccentric side project, remains strangely popular.

The internet has its own judgement.

## Being noticed by Resourceaholic

Another encouraging moment came in July when ESHEETS was featured by Jo Morgan on [Resourceaholic](https://www.resourceaholic.com/?ref=learningai.blog).

Resourceaholic is a well-known and widely used website among secondary maths teachers. ESHEETS appeared in its 200th *Maths Gems* post alongside established resources including MathsPad and materials from the NCETM.

Jo highlighted the self-marking worksheets, games and visualisation tools, particularly the two sheep-related geometry activities.

This mattered to me because it was not paid promotion. Somebody with a strong reputation for finding useful mathematics resources had taken a look at the site and decided that parts of it were worth sharing.

There is a tendency when working alone on a website to lose any sensible sense of proportion. One day it appears to be a promising educational platform. The next day it appears to be several hundred web pages being maintained by a tired man on a Chromebook.

Independent recognition helps.

It does not prove that the project will become commercially successful, but it does suggest that the work is reaching the standard where experienced teachers may find it useful.

## What AI has actually changed

The clearest change is not that AI now does my work for me.

It is that I can attempt projects that would previously have required several different people.

I have some experience of HTML, CSS and JavaScript, but I am not a database engineer, server administrator, illustrator, copywriter, product designer or specialist in online payments. Building the current version of ESHEETS has required at least a little knowledge from all of those areas.

AI helps fill the gaps as they arise.

It can explain unfamiliar code, suggest a database structure, diagnose an error, draft documentation, produce an image, review an interface or help turn a vague classroom idea into a working prototype.

That does not remove the need to understand anything. In practice, it creates a reason to learn a large number of things rather quickly.

It also makes judgement more important.

When the cost of producing a prototype falls, the limiting factor is no longer whether something can be built. It is whether it should be built. AI will quite happily help create an elaborate solution to a problem that nobody has.

I have built a few of those as well.

## So why restart this blog?

I considered closing Learning AI because I did not particularly want the responsibility of feeding a second website.

I still do not.

I am therefore not going to promise weekly articles, AI news summaries or breathless reports about every new model release. There are already enough people doing that, many of them with excellent thumbnail faces.

Instead, I will use this site as an occasional record of things I have genuinely built, tested or learned.

The work on ESHEETS gives me something reasonably concrete to write about. I can show what worked, what failed and what AI made possible for one teacher working largely on his own.

That seems more useful than producing another list of ten prompts that will apparently transform your life before breakfast.

The blog went quiet for five months.

The project did not.
### Building with AI
URL: https://www.learningai.blog/building-with-ai/
Last updated: 2026-02-21T13:55:49.000Z
When I started experimenting with AI, I wasn’t trying to build a brand.

I was trying to build a better worksheet.

I’m a secondary maths teacher. No computer science degree. No formal coding background. Just curiosity, patience, and a willingness to break things and fix them.

What began as a small experiment has quietly changed how I think about teaching — and about myself.

---

## From PDFs to Living Pages

The first real shift was simple.

I started creating single-page HTML worksheets and uploading them directly to my content management system.

Instead of static PDFs, students got interactive pages:

- Instant feedback
- Live score updates
- Unlimited retries
- Immediate self-assessment

[![Surface area worksheet](https://storage.ghost.io/c/ac/3e/ac3e416b-5c9f-4a70-aeb3-937773339516/content/images/2026/02/Triangular-prisms-worksheet-3.png)](https://www.esheets.io/surface-area-of-a-triangular-prism/?ref=learningai.blog)

Surface area worksheet

No waiting for marking.  
No guessing whether they were right.

It wasn’t flashy AI. It was structured logic.

But it worked.

That shift — from document to system — changed everything.

---

## AI as a Creative Multiplier

Once I realised I could build interactive pages, ideas stopped feeling expensive.

Projects like:

- [Ultimate Noughts and Crosses](https://www.esheets.io/ultimate-noughts-and-crosses/?ref=learningai.blog)
- [Perigal’s Dissection](https://www.esheets.io/perigals-dissection/?ref=learningai.blog)
- [Emoji Algebra](https://www.esheets.io/emoji-algebra/?ref=learningai.blog)

weren’t essential curriculum tools. They were experiments.

[![Emoji algebra](https://storage.ghost.io/c/ac/3e/ac3e416b-5c9f-4a70-aeb3-937773339516/content/images/2026/02/Emoji-algebra.png)](https://www.esheets.io/emoji-algebra/?ref=learningai.blog)

Emoji algebra

Before AI, they would have stayed ideas. The technical barrier was too high.

With AI, ideas became prototypes.  
Prototypes became usable tools.

AI didn’t replace creativity.  
It reduced the cost of testing it.

---

## Imagery Changed the Experience

When AI image generation matured, I stopped thinking in terms of “worksheets” and started thinking in terms of experiences.

[Escape from Pentades](https://www.esheets.io/escape-from-pentades/?ref=learningai.blog) isn’t just questions. It has atmosphere. Theme. Visual identity.

[![Mathematics adventure game](https://storage.ghost.io/c/ac/3e/ac3e416b-5c9f-4a70-aeb3-937773339516/content/images/2026/02/Maths-adventure-game.png)](https://www.esheets.io/escape-from-pentades/?ref=learningai.blog)

Mathematics adventure game

Previously, custom artwork meant budget or compromise.

Now, I can iterate visuals as quickly as I iterate code.

That changes what’s possible in education.

---

## The Skills I Didn’t Expect to Learn

This journey didn’t stay at the surface.

To build multiplayer games like [Maths Melee Online](https://www.esheets.io/maths-melee-online/?ref=learningai.blog), I had to learn:

- APIs
- Hosting
- Deployment
- Version control
- Rate limits
- Automation

[![Multiplayer mathematics game](https://storage.ghost.io/c/ac/3e/ac3e416b-5c9f-4a70-aeb3-937773339516/content/images/2026/02/Maths-Melee-screenshot.png)](https://melee.esheets.io/?ref=learningai.blog)

Multiplayer mathematics game

It wasn’t smooth.

There were frustrating evenings. Broken builds. Dead ends.

AI didn’t remove the struggle.

It made the struggle navigable.

That’s the difference.

---

## The Identity Shift

I still teach full-time.

But I don’t only see myself as a teacher anymore.

I build systems.  
I design interactive tools.  
I experiment in public.

AI hasn’t replaced my role. It’s expanded it.

---

## What Comes Next

The next stage is structured progress tracking.

I want students to:

- Record completed worksheets
- Store percentage scores
- Track topics over time
- See when it’s time to revisit something

And teachers to see the bigger picture.

Nothing glamorous.

Just feedback at scale.

---

## A Quiet Realisation

You don’t need to be a developer to build anymore.

You need direction.

AI fills knowledge gaps.  
You provide intent.

That combination is powerful.

---

I’m documenting this because I suspect many people are sitting on ideas they assume are “too technical”.

They aren’t.

The barrier hasn’t disappeared.

But it’s lower than it has ever been.

And that changes behaviour.
### Why I’m Learning AI in Public
URL: https://www.learningai.blog/why-im-learning-ai-in-public/
Last updated: 2026-02-20T00:17:02.000Z
Artificial intelligence is everywhere at the moment.

Depending on who you ask, it’s either about to revolutionise everything or destroy half the workforce. The tone is often breathless. Occasionally apocalyptic. Rarely calm.

I’m a secondary mathematics teacher. I’m not a technologist, a startup founder, or an AI evangelist. I’m someone who spends most days in classrooms, thinking about how people learn, how systems work, and how to make complicated ideas understandable.

Over the past year, I’ve started experimenting seriously with AI tools — not just asking them questions, but trying to build things with them. Automating small tasks. Testing workflows. Breaking systems. Rebuilding them. Occasionally getting something to work in a way that feels genuinely useful.

Sometimes it’s impressive.  
Sometimes it’s frustrating.  
Sometimes it’s a complete waste of time.

But it’s never boring.

I’ve realised that the most useful way for me to approach AI isn’t as a passive consumer of tools, nor as a loud critic or cheerleader. It’s as a learner.

So this blog is exactly that: a record of learning.

Not polished thought leadership.  
Not “10 hacks to master AI overnight.”  
Not grand predictions about the future.

Just experiments, reflections, and practical lessons from someone trying to understand how artificial intelligence fits into real work and real life.

As a teacher, I’m naturally interested in how AI affects education. But I’m equally interested in productivity, systems, writing, automation, and the quieter question of how we think clearly in a time of rapid technological change.

I don’t want to be left behind.

I also don’t want to be swept along uncritically.

Learning AI feels like something that should be done deliberately — with curiosity, scepticism, and a willingness to admit when something doesn’t work.

That’s what I’ll try to do here.

I’ll share:

- Tools I’m testing
- Systems I’m building
- Mistakes I’m making
- Things that genuinely save time
- And things that turn out to be more hype than help

If nothing else, writing about this process should sharpen my own thinking.

If it’s useful to others — teachers, professionals, or anyone trying to make sense of AI — even better.

This is simply the start.

— Richard Linnington