How I Designed ChessIQ Around Repeated Real Use

ChessIQ was not designed from a master plan. It was shaped one game at a time.

My process was simple: play a game, open it in my tool, review the analysis, notice what felt off or missing, fix it, then repeat. Sometimes I would run the same game through other analysis tools as well, comparing accuracy, move classifications, evaluation feel, reliability, and performance. Over time, that loop became the real design process:

• play
• analyze
• notice friction
• improve
• repeat

ChessIQ did not start as a grand attempt to build a full chess platform. At first, I just wanted a simpler way to analyze games without running into review limits. But once I depended on the tool regularly, weak ideas got exposed fast. Features that sounded good on paper but interrupted the analysis flow became hard to justify. Anything unclear, noisy, slow, or untrustworthy stood out almost immediately.

Repeated use forced the product to become more intentional.

Where that showed up

One of the clearest examples was move classification. At a glance, move labels can look convincing, but once you actually inspect them, wrong classifications are easy to spot. And when that happens, the whole analysis feels less trustworthy. I felt that problem myself. If move badges were going to act as a source of truth in the review flow, they had to be taken seriously. That pushed me to improve the system instead of treating it as a cosmetic extra.

The same thing happened with analysis quality and performance. Engine-based features can still "work" while quietly doing far more processing than they should. It is surprisingly easy to make a system slower or heavier without realizing it, especially when the output still appears correct. Repeated daily use exposes that quickly. I was often reviewing games immediately after playing, usually on my phone, so speed and focus mattered. I wanted to get to the important moments quickly and stay focused on the board.

That daily use shaped a lot of the product decisions.

What stayed

I added a game flow chart because I wanted a clearer sense of how a game had unfolded, but it went through multiple versions before it stopped cluttering the experience.

I added continuous analysis because sometimes a position still felt unclear and I wanted the engine to keep working without forcing a full re-analysis of the entire game.

I added critical moments because I wanted a faster way to jump to what mattered.

I added accuracy percentage because it had become a useful shorthand for quick review.

I added opening statistics because I wanted to know how I was actually performing in my openings over time.

I added puzzles generated from my own mistakes because training from my own games felt both more personal and more useful than relying only on generic puzzle databases.

The product also expanded to support the kinds of games I actually wanted to study. Support for Chess960 and start-from-FEN positions came from real use, not roadmap theory. Even PGN handling became part of the refinement process, because using a tool seriously means running into messy real-world data and deciding whether the product can handle it cleanly.

What did not survive

Just as important were the things that did not survive.

Some ideas were interesting, but not useful enough. An early opportunity meter is a good example. On paper, it seemed promising: a way to show when a player had strong chances or tactical windows. In practice, it added lag, was often empty, and did not justify the attention it demanded. It was more interesting as an idea than as part of an actual workflow, so I cut it.

That became one of the most important filters in the whole product. Repeated use strips away features that are merely interesting and exposes the ones that are genuinely useful. A crowded interface, a weak metric, or a flashy but low-value feature can survive a demo. It does not survive becoming a daily tool.

The standard

That is probably the biggest lesson behind ChessIQ.

The product was not shaped by trying to imagine everything a chess analysis platform could become. It was shaped by a narrower question: does this help me understand my games better? If the answer was yes, it stayed and improved. If the answer was no, or only sometimes, it became a candidate for revision or removal.

Over time, ChessIQ grew far beyond the original goal of being a simple wrapper around analysis. It became a more serious analysis environment, a personal study system, and eventually a foundation for deeper pattern analysis. But even as it expanded, the standard stayed the same. The point was never to collect features. The point was to make post-game review dependable enough, clear enough, and focused enough that I would actually want to keep using it.

That is still how I think about products more broadly. I trust repeated use more than early ideas. It exposes what is bloated, what is weak, and what actually helps. The best products are not usually the ones that begin with the most elaborate plan. They are the ones that get shaped by real workflows, real friction, and enough repetition for each part to earn its place.

ChessIQ got better because it had to.