Test-n-Tell - tiny apps, Big ideas

  The beginning of development went surprisingly smoothly. My game concept was simple and well understood, so Codex had no problem getting the project started. It created the basic structure in Godot , set up a playable scene and implemented the core rules. Very quickly, I had something resembling the main gameplay screen where I could move balls around the board and see whether the basic mechanics actually worked.

In this series of posts , I am sharing my experience creating a game from absolute zero as a non-developer and non-designer. In the introductory post , I covered why I picked a game for this experiment. Today, we'll go through the first steps of the process: selecting and setting up the key tools.

My blog's stats are clear: people are interested in practical experiences. Especially when it comes to AI and vibe coding tools. Luckily, that's what I've been doing these past few months - heavily using AI to create a digital product end-to-end. This series will get into all the fancy and stinky details of my process, challenges I've encountered along the way and, of course, the final result accompanied by the cost breakdown.

  I have been using Codex more and more recently. Not in a “look, AI wrote me a todo app” kind of way. More like: I need to ship my actual product, fix real bugs, improve real tests, and not spend my evenings arguing with a robot about why it deleted half of my codebase.

The job of a product manager is already changing. We use AI more and more in our daily work, and there is no sign of this slowing down. Writing, research, analysis, prototyping, summarising calls, checking requirements, preparing strategy docs, testing product ideas - all of it can already be supported by AI.

  I've been doing a lot of vibe coding lately, and one tech stack emerged for me as the most practical. Spoiler alert 1: it's Firebase + Codex + Google Cloud. Spoiler 2: tomorrow it could change.

  If I'd try Jules first - I'd have a totally different impression of the state of coding agents today. A much worse impression. Here's why.

  Is it only me, or have we stopped talking about frameworks? Long gone debates about Agile vs Waterfall, we stopped fighting over TDD vs BDD or KANO vs effort/value... it's KANO by the way, KANO is way superior.

  In this series, I've tested and reviewed multiple tools in the AI agents category. Some of them are useful, others less so, but one thing is certain: this category has a huge potential to change our whole industry and have major effects on people's roles.

  Writing is an essential PM activity - depending on the type of PM you are, you either write a lot or a lot a lot. Many PMs these days employ gen AI tools to help them write more or better, but they do not always get the outcomes they hoped for.

  Have you ever wished for AI to only answer based on the data you give it? Or maybe you want to turn some of your sources into a real-sounding podcast? This and much more is possible with NotebookLM.

  I continue to test different AI agents that could create digital products with no coding knowledge required. Next in the list is the tool called Replit .

  Bolt.new is next up in the category of AI agents that can create fully working products without writing any code. Let's see how it compares to Lovable which I reviewed in the previous post.

  In this series of posts I will test and tell (see what I did there?) my thoughts on different AI tools available to PMs. And we start from the most recent and exciting - AI agents category.

  In 2025, AI tools will become part of our working toolkit if they haven’t already. PMs that will use AI tools smartly will be more productive and potentially more successful than their AI-less peers. What tools should you add to your toolkit first? 

  Impact mapping is a versatile tool that should be in every PM's pocket. You can apply impact mapping to better communicate, collaborate and eventually reach better results for your product and organisation.

  Over the last few months, I got to try and review many product management tools . Some of those tools I used extensively before or actively using now. The right tool can supercharge your PM team performance and make the whole process of creating products so much easier. In this post, I'd like to offer my help in selecting the most-suited tool for your team. 

  Aha.io is the latest tool I had a chance to review and one of the most sophisticated product discovery and management software available on the market today.

  I've chosen ProdPad as the third product management tool to review. It continues my ongoing series of PM and operations software reviews available on test-n-tell.com

  JPD is a new player in the market of product management software. Jira (and the whole Atlassian suite) has been one of the most popular tool stacks for teams to deliver software products. Now they're adding a missing piece - product discovery.