The Traitors star says she stopped using it because she was concerned about chemicals.
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Friday, December 12, 2025
December 12, 2025
Charlotte Church reveals she has ditched deodorant
Thursday, December 11, 2025
December 11, 2025
New top story on Hacker News: Show HN: SIM – Apache-2.0 n8n alternative
Show HN: SIM – Apache-2.0 n8n alternative
16 by waleedlatif1 | 0 comments on Hacker News.
Hey HN, Waleed here. We're building Sim ( https://sim.ai/ ), an open-source visual editor to build agentic workflows. Repo here: https://ift.tt/eMSydDx . Docs here: https://docs.sim.ai . You can run Sim locally using Docker, with no execution limits or other restrictions. We started building Sim almost a year ago after repeatedly troubleshooting why our agents failed in production. Code-first frameworks felt hard to debug because of implicit control flow, and workflow platforms added more overhead than they removed. We wanted granular control and easy observability without piecing everything together ourselves. We launched Sim [1][2] as a drag-and-drop canvas around 6 months ago. Since then, we've added: - 138 blocks: Slack, GitHub, Linear, Notion, Supabase, SSH, TTS, SFTP, MongoDB, S3, Pinecone, ... - Tool calling with granular control: forced, auto - Agent memory: conversation memory with sliding window support (by last n messages or tokens) - Trace spans: detailed logging and observability for nested workflows and tool calling - Native RAG: upload documents, we chunk, embed with pgvector, and expose vector search to agents - Workflow deployment versioning with rollbacks - MCP support, Human-in-the-loop block - Copilot to build workflows using natural language (just shipped a new version that also acts as a superagent and can call into any of your connected services directly, not just build workflows) Under the hood, the workflow is a DAG with concurrent execution by default. Nodes run as soon as their dependencies (upstream blocks) are satisfied. Loops (for, forEach, while, do-while) and parallel fan-out/join are also first-class primitives. Agent blocks are pass-through to the provider. You pick your model (OpenAI, Anthropic, Gemini, Ollama, vLLM), and and we pass through prompts, tools, and response format directly to the provider API. We normalize response shapes for block interoperability, but we're not adding layers that obscure what's happening. We're currently working on our own MCP server and the ability to deploy workflows as MCP servers. Would love to hear your thoughts and where we should take it next :) [1] https://ift.tt/i81KC7Z [2] https://ift.tt/lCLhQFc
16 by waleedlatif1 | 0 comments on Hacker News.
Hey HN, Waleed here. We're building Sim ( https://sim.ai/ ), an open-source visual editor to build agentic workflows. Repo here: https://ift.tt/eMSydDx . Docs here: https://docs.sim.ai . You can run Sim locally using Docker, with no execution limits or other restrictions. We started building Sim almost a year ago after repeatedly troubleshooting why our agents failed in production. Code-first frameworks felt hard to debug because of implicit control flow, and workflow platforms added more overhead than they removed. We wanted granular control and easy observability without piecing everything together ourselves. We launched Sim [1][2] as a drag-and-drop canvas around 6 months ago. Since then, we've added: - 138 blocks: Slack, GitHub, Linear, Notion, Supabase, SSH, TTS, SFTP, MongoDB, S3, Pinecone, ... - Tool calling with granular control: forced, auto - Agent memory: conversation memory with sliding window support (by last n messages or tokens) - Trace spans: detailed logging and observability for nested workflows and tool calling - Native RAG: upload documents, we chunk, embed with pgvector, and expose vector search to agents - Workflow deployment versioning with rollbacks - MCP support, Human-in-the-loop block - Copilot to build workflows using natural language (just shipped a new version that also acts as a superagent and can call into any of your connected services directly, not just build workflows) Under the hood, the workflow is a DAG with concurrent execution by default. Nodes run as soon as their dependencies (upstream blocks) are satisfied. Loops (for, forEach, while, do-while) and parallel fan-out/join are also first-class primitives. Agent blocks are pass-through to the provider. You pick your model (OpenAI, Anthropic, Gemini, Ollama, vLLM), and and we pass through prompts, tools, and response format directly to the provider API. We normalize response shapes for block interoperability, but we're not adding layers that obscure what's happening. We're currently working on our own MCP server and the ability to deploy workflows as MCP servers. Would love to hear your thoughts and where we should take it next :) [1] https://ift.tt/i81KC7Z [2] https://ift.tt/lCLhQFc
December 11, 2025
Huge undersea wall dating from 5000 BC found in France
Wednesday, December 10, 2025
December 10, 2025
New top story on Hacker News: Israel used Palantir technologies in pager attack in Lebanon
Israel used Palantir technologies in pager attack in Lebanon
177 by cramsession | 105 comments on Hacker News.
177 by cramsession | 105 comments on Hacker News.
December 10, 2025
World Cup ticket ballot set to open - here's all you need to know
Tuesday, December 9, 2025
December 09, 2025
Man charged after Bournemouth's Semenyo racially abused
Monday, December 8, 2025
December 08, 2025
New top story on Hacker News: Show HN: DuckDB for Kafka Stream Processing
Show HN: DuckDB for Kafka Stream Processing
17 by dm03514 | 5 comments on Hacker News.
Hello Everyone! We built SQLFlow as a lightweight stream processing engine. We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory! DuckDB also supports a rich ecosystem of sinks and connectors! https://ift.tt/Klyp86v https://ift.tt/42WNdm1 We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors I would love your feedback, criticisms and/or experiences! Thank you
17 by dm03514 | 5 comments on Hacker News.
Hello Everyone! We built SQLFlow as a lightweight stream processing engine. We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory! DuckDB also supports a rich ecosystem of sinks and connectors! https://ift.tt/Klyp86v https://ift.tt/42WNdm1 We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors I would love your feedback, criticisms and/or experiences! Thank you