Top Architect focuses on sharing practical architecture knowledge, covering enterprise, system, website, large‑scale distributed, and high‑availability architectures, plus architecture adjustments using internet technologies. We welcome idea‑driven, sharing‑oriented architects to exchange and learn together.
OpenAI Codex team member Jason Liu shares his 'Codex-maxxing' system: persistent cross-month threads, voice-driven tasks, Heartbeats scheduled automation, @computer UI control, test-verified completion, local Obsidian memory, and new Goal mode for autonomous multi-day workflows.
Google DeepMind releases three specialized Gemini models — 3.6 Flash for token-efficient reasoning, 3.5 Flash-Lite for high-speed low-cost volume tasks, and 3.5 Flash Cyber for vulnerability detection — while confirming aggressive pre-training for Gemini 4, signaling a push to make production AI agents faster, cheaper, and more capable.
Google DeepMind released three new Gemini models—3.6 Flash with 65% token reduction, 3.5 Flash-Lite for high-speed low-cost processing, and 3.5 Flash Cyber for vulnerability detection—while simultaneously beginning aggressive pre-training for Gemini 4, signaling continued rapid advancement in AI agent capabilities and cost reduction.
Google DeepMind released three Gemini variants—3.6 Flash, 3.5 Flash‑Lite, and 3.5 Flash‑Cyber—each promising token savings, higher speed, or security focus, while also announcing an aggressive pre‑training run for the upcoming Gemini 4, signaling a push for cheaper, faster AI agents.
A Reddit user uncovered that Gemini 3.2 Flash silently went live, delivering single‑prompt code generation of over 2,200 lines—including interactive 3D scenes and a functional Windows 98—thanks to model distillation and sparsification that cut inference cost 15‑20× while approaching GPT‑5.5 performance, and the model is already being integrated with third‑party services ahead of the I/O 2026 showcase.
Manticore Search, a C++‑based open‑source search engine forked from Sphinx, claims to outperform Elasticsearch by up to 15× in various scenarios, offers modern multithreaded architecture, SQL compatibility, extensive client libraries, and easy Docker deployment, positioning itself as a fast, lightweight, full‑text search solution.
Gemini Omni, Google DeepMind's new world model, combines multimodal reasoning and generation to enable conversational video editing, emergent physical understanding, style transfer without paired data, and avatar‑based personalization, marking a step‑change from text‑to‑video models like Veo.
Gemini 3.2 Flash quietly appeared on the Gemini web interface, letting developers generate massive code (up to 2,200 lines) in a single prompt, leveraging model distillation and sparsification, while integrating services like Canva, Instacart and OpenTable to act as a unified AI assistant.
The article demonstrates how to let users upload a JAR that implements a given interface, then hot‑replace the implementation at runtime using either reflection or Spring annotation‑based loading, covering class loading, bean registration, and cleanup with concrete code examples.
Google DeepMind’s Gemini Omni, a new multimodal world model, combines reasoning and generation to produce realistic video, images, and interactive simulations, supports conversational editing, digital avatars, and emergent capabilities, while balancing trade‑offs across five evaluation pipelines and enforcing safety measures such as avatar registration and dual watermarks.
