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I Stopped Fighting Word Templates for Event Name Tags — Here's What I Do Now

66 K — Fri, 12 Jun 2026 09:24:55 +0000

I Stopped Fighting Word Templates for Event Name Tags — Here's What I Do Now

Every time I helped organize a developer meetup or internal workshop, the same thing happened: someone would share a Word doc with name tag placeholders, half the team couldn't open it correctly, the fonts shifted on different machines, and we'd end up printing a test sheet only to find everything was off by 3mm.

It's a small problem. But it's an annoying one that somehow ate 45 minutes every single time.

The actual problem with Word name tag templates

If you've ever tried to print Avery labels from a Word file, you know the trap. You open the template, type names into individual cells, realize you have 30 people and need to do this 30 times, then print — and the labels don't line up because your printer driver has a slightly different default margin than whoever made the file.

Then someone suggests mail merge. Mail merge from a CSV sounds great in theory. In practice, it's twenty minutes of watching tutorial videos to do something that should take two.

For the record, I'm a developer. I've written scripts to automate things far more complex than this. But for event prep at 11pm the night before a workshop, I just wanted something that worked.

What I ended up using

I came across name tag template while searching for "avery 5163 name tag generator" — which is a very specific search that tells you exactly how deep into this problem I was.

The workflow is:

Paste a list of names, one per line
Pick a label layout (Avery 5160 for smaller labels, Avery 5163 for the larger badge-sized ones)
Download a PDF

That's it. No account. No upload. The PDF is generated entirely in the browser, which honestly made me more likely to trust it with an attendee list.

For a 40-person meetup, the whole process took about 90 seconds. The PDF lined up correctly on the first print because it's pre-sized to the label spec — you just have to remember to print at Actual Size (not Fit to Page, which is what kills alignment every time).

Why this matters for developer events specifically

Hackathons, meetups, internal tech talks, onboarding sessions — these are all situations where you need name tags and you have roughly zero time to spend on logistics before the actual event starts.

The Avery 5163 format (4" × 2", 10 per page) works well for conference-style badges where people need to read names from across a table. The 5160 format (2.625" × 1", 30 per page) is more compact — better if you just need desk labels for a workshop or want to label seats for a presentation.

There are three template styles: a minimal black-and-white Professional one, a Colorful Event version with a green header band, and a Friendly School style with rounded corners. For tech events, the Professional one is usually the right call.

The part that actually surprised me

I half-expected the PDF to look slightly off — like the names would be centered weird, or the font would be some default serif that made everything look like a 2003 document.

It looked fine. Clean sans-serif, names centered properly, margins correct. Not exciting, but that's the point. A name tag shouldn't be exciting. It should just be readable.

What it doesn't do

It's not a design tool. If you need custom logos, brand colors, or QR codes on your badges, this won't do it — you'd want something like Canva or a proper badge printing service.

It also only supports two label sizes right now (5160 and 5163). If your event uses a different format, you'd need to check compatibility first.

But for "I have a list of names and I need them on printable labels before tomorrow morning," it removes every friction point that normally makes this task annoying.

Practical printing tip

One thing I learned: always do a single test print on plain paper first, then hold it up against a blank label sheet to check alignment before loading real labels. Takes 10 seconds and saves an entire sheet of labels. Even with a well-formatted PDF, printers occasionally have margin quirks.

Name tags are one of those things that feel trivial until you're dealing with them at 11pm before an event. Having a tool that handles it in under two minutes is the kind of small quality-of-life improvement that actually adds up across a year of organizing things.

If you run into the same problem, it's at name tag template. No signup, free to use.

I Built a Tool to Fix My Bad Midjourney Prompts

66 K — Thu, 14 May 2026 08:22:29 +0000

I Built a Tool to Fix My Bad Midjourney Prompts

A lot of AI prompt tools try to do everything.

They help with ChatGPT, image generation, copywriting, brainstorming, coding, and whatever else can fit into the landing page. That sounds broad and useful, but in practice it often means the output becomes generic.

That was the problem I kept seeing with Midjourney prompting.

If you already use Midjourney regularly, you probably know the pattern:

the idea in your head is clear enough
the prompt you type is rough
the result comes back close, but not really right
then you start stacking more adjectives, style words, and random references
and the prompt gets longer without getting much better

So instead of building another general-purpose AI prompt helper, I built a small tool focused on one thing:

turning rough image ideas into cleaner Midjourney prompts with more useful settings.

That tool is Midjourney Prompt Optimizer.

Why I focused on Midjourney only

I think a lot of prompt tools fail because they are built from the tool-maker’s perspective, not from the actual workflow.

From the tool-maker side, it is tempting to say:

one prompt box, one AI model, many use cases

From the user side, that usually creates weak output.

Midjourney is not just “another AI text box.” It responds to a particular mix of:

subject clarity
composition hints
visual hierarchy
lighting and mood direction
parameter choices like aspect ratio, stylize, chaos, and weird

So if the system treats Midjourney like generic prompt writing, the output often becomes bloated or vague.

I wanted something narrower and more practical.

Instead of trying to generate a “perfect” cinematic super-prompt every time, the goal is to produce a better first draft:

clearer subject
cleaner structure
stronger framing direction
more usable settings
less random keyword stacking

The real problem is not prompt length

One thing I noticed early is that many people assume weak Midjourney output comes from prompts being too short.

I don’t think that is usually the real problem.

The real problem is more often one of these:

the subject is unclear
the image goal is mixed or contradictory
the style words are doing too much work
the settings do not match the intended result
the prompt is adding noise instead of direction

That is why I designed the product around structure instead of prompt inflation.

For example, a rough input like:

dark fantasy knight

should not automatically become a giant wall of decorative terms.

A better transformation is something more like:

dark fantasy character portrait of a battle-worn knight in blackened steel armor, standing in a ruined temple, cold blue rim lighting, drifting ash and fog, dramatic cinematic framing, detailed metal textures, grounded heroic stance

Then the tool can suggest settings that actually fit the use case, instead of leaving the user to guess.

What the product does right now

The current version focuses on a simple workflow.

You start with a rough concept. Then the tool helps generate:

a cleaner Midjourney-ready prompt
a suggested aspect ratio
stylize guidance
chaos guidance
weird guidance when appropriate

That means the output is not just "better wording." It is meant to be a more usable starting point for actual image generation.

Right now the product is aimed at:

creators
designers
marketers
beginners who want better first drafts

The free plan gives a few optimizations per day, and paid plans are there for people who use Midjourney more seriously in ongoing creative work.

What I learned while building it

A few things became clearer once I started shaping this into a real product instead of just a landing page.

1. Generic AI UX is easy to ship but weak as a product

It is very easy to build a text area, a submit button, and some nice marketing copy.

It is much harder to make the output consistently feel tailored to a real use case.

For this product, the real work is not "make the UI look like an AI startup." The real work is:

understanding intent better
classifying the image goal correctly
resolving conflicting prompt directions
recommending settings that feel sensible
making outputs feel less templated

2. Before/after examples matter more than abstract claims

People do not care much when a tool says "get better prompts."

They care when they can see:

what the rough input was
what changed
why the optimized version is more usable

That is one reason I think example pages and use-case pages matter so much for a product like this.

3. The first draft is the real product promise

I do not think tools like this should pretend to eliminate iteration.

Creative work still needs taste and refinement.

But getting from a weak rough idea to a strong first draft faster is already valuable.

That is the promise I want to keep the product honest about.

Why I'm writing this now

The site just launched, and I'm now in that awkward early phase where the product is real enough to use, but still early enough that outside feedback matters a lot.

I'm especially interested in feedback from people who:

use Midjourney often
build creative tools
have strong opinions about prompt quality
think most AI products are too generic

If that sounds like you, I'd love for you to take a look.

Try it

The product is here:

mjpromptoptimizer

If you try it, I'd love to know:

whether the prompt output feels more useful than generic prompt helpers
whether the settings suggestions feel sensible
which use cases should be improved first
where the output still feels too templated

Early products usually do not need more hype. They need sharper feedback.

That's what I'm after now.