Preparing a business plan for a game on Steam
Earning millions is easier than ever. I'll tell you how :-D
When I posted my final presentation [ru] (slides) for World Builders 2023 (my posts, site), I promised to tell how I made a roadmap and a financial model for the game. So, here they are.
At the end of this post, we will have:
- A brief strategy of our company: what we do, how, and why.
- A table with our beacons — successful games roughly similar to what we want to make. Similar in gameplay, team size, budget, etc.
- A composition of the team we need to assemble.
- A roadmap — a development plan for our game.
- An outline of our marketing strategy.
- A financial model — how much we will spend, how much we will earn.
- A large number of my caveats throughout the post.
- Jokes and
I hopewitty remarks.
All the final documents can be found here.
Migrating from GPT-3.5-turbo to GPT-4o-mini
Guess when I switched models.
Recently OpenAI released GPT-4o-mini — a new flagship model for the cheap segment, as it were.
- They say it works "almost like" GPT-4o, sometimes even better than GPT-4.
- It is almost three times cheaper than GPT-3.5-turbo.
- Context size 128k tokens, against 16k for GPT-3.5-turbo.
Of course, I immediately started migrating my news reader to this model.
In short, it's a cool replacement for GPT-3.5-turbo. I immediately replaced two LLM agents with one without changing prompts, reducing costs by a factor of 5 without losing quality.
However, then I started tuning the prompt to make it even cooler and began to encounter nuances. Let me tell you about them.
My GPTs and prompt engineering
Ponies are doing prompt engineering (c) DALL-E
I've been using ChatGPT almost since the release of the fourth version (so for over a year now). Over this time, I've gotten pretty good at writing queries to this thing.
At some point, OpenAI allowed customizing chats with your text instructions (look for Customize ChatGPT in the menu). With time, I added more and more commands there, and recently, the size of the instructions exceeded the allowed maximum :-)
Also, it turned out that a universal instruction set is not such a good idea — you need to adjust instructions for different kinds of tasks, otherwise, they won't be as useful as they could be.
Therefore, I moved the instructions to GPT bots instead of customizing my chat. OpenAI calls them GPTs. They are the same chats but with a higher limit on the size of the customized instructions and the ability to upload additional texts as a knowledge base.
Someday, I'll make a GPT for this blog, but for now, I'll tell you about two GPTs I use daily:
- Expert — answers to questions.
- Abstractor — makes abstracts of texts.
For each, I'll provide the basic prompt with my comments.
By the way, OpenAI recently opened a GPT store, I'd be grateful if you liked mine GPTs. Of course, only if they are useful to you.
Two years of writing RFCs — statistics
Slightly more than two years ago, I became a Lead/Engineering Manager for Palta's payment team. I left the company at the end of 2023 for another sabbatical [ru].
It is time to sum up. I will start with my favorite initiative.
From the first month, I promoted the idea of preceding major changes with text documents — RFC — Request for Comments.
In this post, I will analyze two years of applying this practice to share the experience, summarize the results, and have convincing arguments for my next job.
Preferences of strategy players
Looking at the survey data and trying to find something useful.
Recently I've conducted a survey about the preferences of strategy players.
In the previous post, we cleaned up the data, and in this one, we will try to find insights within it.
In this post you will find an interactive dashboard with a bunch of charts, where you can compare two samples of your choice. There are many samples — for every taste and color, so feel free to explore and share the patterns you find on Telegram and Discord.
But be careful with conclusions. There is little data, in some cases very little. For example, the difference between the sample sizes of male and female respondents is about tenfold => you should be very careful in interpreting the differences between them.
In general, do not take this post as a full-fledged study. I'm sure many analysts would have torn my hands off for such a thing. Then sewed them back and torn them off again :-D Use the post as an interface to the data, and make your own conclusions.