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tpickson Understanding is the new bottleneck

sure, if I get lazy and don't read every line of the spec or don't thoroughly review the generated code, then I have felt a gap in understanding, but thats more on me than the tools. Another case is when I'm just completely unfamiliar with the framework the code is written in, I feel this happen whenever I use AI to write any non-trivial frontend as I rarely did frontend pre-AI.

tpickson Understanding is the new bottleneck

same, I've been liking https://openspec.dev/ and find the more time I put iterating/scrutinizing the spec artifacts (proposal, requirements, design, tasks) before I let the agent implement the better understanding I have and the better results I get. Also like that it is agent agnostic so I can take it with me as I try different agents/models.

tpickson Ask HN: What are you working on? (August 2026)

thanks for taking a look!

> A great add will be to show two columns: what players like me play here and the actual best counter after that move

I think this case is handled by enabling the stockfish comparison toggle, but I may be misunderstanding.

tpickson Ask HN: What are you working on? (August 2026)

Rated Analysis, rating relative chess analysis: https://rated-analysis.pickle-dev.com/

I've been a bit obsessed with chess lately and have read/heard things like "X is the top engine move, but no one under master plays that line". To me this begs the questions "which line are players below master playing" and "which line are players at/above/below my rating playing". This question motivated me to build a tool to analyze the move distribution (win/draw/loss rate) from a given position across rating buckets (400, 500, 600... 3000). Luckily, https://database.lichess.org/ provides an open/free database of games that have just the data required to build such a tool.

The Rated Analysis tool consists of an 1) an offline job to compute/store the positional move distribution bucketed by rating, and 2) the https://rated-analysis.pickle-dev.com/ webpage to serve the data along with some nice to haves like loading user games from platforms like chess.com/lichess.org.

tpickson Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal help?

> Claude Code uses Haiku to read through the transcript and decide if the goal has been completed.

feels kinda odd to use a less capable model to determine if the goal is fully complete. Especially if the user is expecting /goal to thoroughly complete the task. A less capable model would be more likely to misclassify `isComplete?`