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    Yeah, there's AI, but I added it because I found it easier to find answers I'm looking for. For the data scientists, you can download the CSV and go crazy. Would love to know what discoveries or learnings can be found from it. To download the raw scraped data you need to become a paid member but you don't really need it unless you're wanting to finesse a table of data for a particular need. The cost is mostly just an incentive to help me pay the bills for running the website. The bunch of available CSV files contain large amounts of data which has everything from tags, genres, pricing,…

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    we had hundreds of discussions with engineering leaders over the past few months, and everyone's trying to understand where they are in the AI journey. we collected all this data into a benchmark and built a free grader to let you know where you stand. you answer on a 1–5 scale (e.g., autonomy runs from "suggestions only" to "agents own multi-hour workflows across code, infra, and external systems") - takes about 5 minutes. https://agent-benchmarks.com/software-factory/ waiting for your results!

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    Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…

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