Author here . I grew increasingly frustrated by the mess coding agents made with the design system, so I took a crack at creating a tighter structure with AI agent instructions in the form of Claude.md and a Claude Skill to hopefully enforce it better.
Curious any thoughts. What's working / not working for folks
We are getting hit with exactly the same at a much greater scale. 260K in our case. Exactly the same issue.
When you create Gemini Flash Cache with a TTL of 1 or 3 hrs, it creates the cache and TTLs it correctly, but the billing system keeps charing the hourly rate for the cache making the charges grow exponentially.
We've seen charges go up since 9/19 even though we turned off all the services from that account.
Struggling to get the attention of folks at Google (ticket, account manager, sales engineer: no one responds)
Interesting deep dive into how Adobe built a streaming ingestion layer on top of Apache Iceberg to handle massive volumes of Experience Platform data, addressing challenges like the small‑file problem and commit bottlenecks with asynchronous writes and compaction. All stuff I've had to deal with in the past.
Good nuggets on they partition tables by time, stage writes in separate ingestion and reporting tables, and tune snapshot and metadata handling to deliver a lakehouse‑style pipeline that scales without melting the object store.
The Eclipse Foundation just opened up its Theia AI platform and an alpha Theia IDE that let you bolt the LLM of your choice into your workflow and actually see what it’s doing. You get complete control over prompt engineering and agent behavior, can plug in a local model or a cloud model, and even wire up external tools via Model Context Protocol. The AI‑powered Theia IDE bakes in coding agents, an AI terminal and context sensitive assistants while giving you license‑compliance scanning via SCANOSS. Instead of being locked into a proprietary copilot, you can customize the entire AI stack to your needs and still keep your code private, which is the kind of hackable openness Hacker News loves.
Asta isn’t just another chatbot; it’s a full stack for building and evaluating AI agents that can actually assist researchers. It ships with an open research assistant that reads papers, synthesizes evidence and even cites its sources. AstaBench’s 2,400‑problem benchmark suite gives us a reproducible way to compare agents on real multi‑step science tasks like literature review and code execution. The project also includes open‑source agents, APIs and language models tuned for research, plus access to a 200 M‑paper corpus.
In a world full of closed, untested agent tools, Asta is refreshing and gives developers all the components they need to build their own trustworthy science agents.
This isn’t another hype piece. The InternVL3.5 is a coherent vision‑language model that actually understands pixels and text together. It comes in sizes from 1 B up to a monster 241 B parameters, and on benchmarks like MMMU and ChartQA it beats closed models like GPT‑4V, Claude and Qwen. An open‑source LLM that competitive signals we can build cutting‑edge multimodal apps without depending on a black‑box API, which is a big deal for devs who care about hackability and reproducibility.
This doesn’t just feel like business as usual, it’s a flashpoint. Nvidia hit pause on its H20 chip, the one tailor-made for China, because Beijing raised red flags over backdoors and data risks. It’s classic tech meets geopolitics: export controls, supply chain pressure, and the chip fight getting sharper. If you’re into how hardware becomes policy, this is it.
This whitepaper digs into the sneaky dependencies you didn’t knowingly add (thanks, transitive bloat). It lays out how an SBOM can be a universal metadata layer across ecosystems—pip, npm, you name it—to let you trace every ghost package in your stack.
Feels like the Python dev community quietly dropped a supply-chain lifeline here.
Curious any thoughts. What's working / not working for folks
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