Qubot, our internal Copilot-powered analytics agent, allows any GitHub employee to ask questions about our data in plain language. Here's what we learned as we built it. The post How we built an internal data analytics agent appeared first on The GitHub Blog.
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The Memory Sidecar has always been the invisible workhorse behind decentralized agent interactions—providing agent-agnostic memory persistence without coupling to any single AI framework. With v3.5.1, the focus shifts from feature velocity to operational maturity. This release, delivered via the hermes-memory-installer, is expressly designed for teams running memory sidecars in production at scale. If you’ve been treating your memory layer as a pet, it’s time to make it cattle. This is not a feature drop.
The very SERIOUSLY serious Puzzle Cube Game that is definitely not just Rubix Cube from the inside. jchildree.itch.io Juniper Dev, that one YouTuber, looked into the camera and told me to take this seriously. I think anyway, IDK, I was chewing at the time, so I definitely didn't decide to just do my own thing. The challenge: one week, build a game around the core concept of SPIN TO WIN. I asked myself what is more spin-to-win than anything else in the known universe.
Introduction When people first start using ClickHouse®, most of the attention naturally goes to the MergeTree engine. It's the default choice for analytical workloads thanks to its exceptional query performance, indexing capabilities, and efficient storage. However, ClickHouse offers a wide range of table engines beyond MergeTree. Each engine is designed to solve a specific problem, whether it's handling updates, pre-aggregating data, buffering high-frequency inserts, integrating with external systems, or scaling queries across clusters. Understanding these engines is essential for designing e
Python Selenium Architecture Key Components: Selenium Client Libraries JSON Wire Protocol/ W3C WebDriver Protocol Browser Drivers Browser Workflow A python script sends commands using Selenium client library. These commands are converted into HTTP requests following the WebDriver protocol. The browser driver receives the requests and translates them into native browser actions. the browser executes the actions and sends back the results (Success/Failure, element states, etc.) The driver communicates the response back to the python script. Advantages of the Architecture Conclusion: Python Selen
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