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Practical writing on software architecture, SaaS products, AI automation, legacy modernisation, and the business of building reliable systems.
Curated links from external sources — not 360Softy original articles.
Cloudflare has integrated with Anthropic's Claude Managed Agents to provide a fast, isolated execution environment for autonomous code delivery. This means builders can scale agent workflows globally while strictly controlling access to private backends and easily customizing their agent’s tools and runtimes.
The Setup: The Hype Machine It’s vector database season. Conferences are full of RAG pipeline talks. Pinecone raised over $100 million; Milvus, Weaviate, and Qdrant are all well-funded and competing to disrupt how we store and search embeddings. Let’s be blunt: The vector databases are poorly implemented, and most of the companies implementing them are doing so to solve a problem that doesn’t exist.
Posted by Matthew McCullough, VP, Product Management, Android Developer Today at Google I/O, we announced the many ways we’re powering agentic workflows to increase your productivity and ensure your apps shine across the expanding Android ecosystem. Here’s a recap of 17 of our favorite announcements for Android developers; you can also see what was announced last week in The Android Show: I/O Edition. Stay tuned over the next two days as we dive into all of the topics in more detail! Build H
Posted by Emma-Louise Leavey, Group Product Manager and Mike Taylor-Cai, Product Manager Google AI Studio can build entire Android apps for you in minutes from just a prompt. You don't need to install any software or configure any libraries, which significantly lowers the barrier to development. Whether you’re a seasoned developer looking to prototype at lightning speed or a creator building your first-ever mobile experience, you can now go from a single prompt to a high-quality, Kotlin-base
Hi HN, I'm Antoine Zambelli, AI Director at Texas Instruments. I built Forge, an open-source reliability layer for self-hosted LLM tool-calling. What it does: - Adds domain-and-tool-agnostic guardrails (retry nudges, step enforcement, error recovery, VRAM-aware context management) to local models running on consumer hardware - Takes an 8B model from ~53% to ~99% on multi-step agentic workflows without changing the model - just the system around it - Ships with an eval harness and interactive das
Article URL: https://www.apple.com/newsroom/2026/05/apple-unveils-new-accessibility-features-and-updates-with-apple-intelligence/ Comments URL: https://news.ycombinator.com/item?id=48192224 Points: 721 # Comments: 378
I've found a core misconception is persistent... people use the CLIP interrogator model expecting it to recover the original prompt from an image. It cannot do this, and if you look at the architecture, it becomes clear why. The mapping from prompt to image is non-injective — many different prompts produce nearly identical outputs, and some visual features in a generated image were never written explicitly in any prompt at all. There is no hidden string to extract. What CLIP Interrogator actuall
What held up in production when the goal wasn’t just functional accuracy but better dialogue
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