Try it outMario Nawfal (@MarioNawfal):GROK GOT HIRED AND PROMOTED – SAY HELLO TO YOUR NEW SENIOR DEVJetBrains just handed Grok a desk, a badge, and the authority to fix your code like it owns the place.Dev Boost:•⁠ ⁠Junie, JetBrains’ coding agent, now powered by Grok’s brain•⁠ ⁠Explains your mess, https://t.co/xDvmFnulcn ...

Product Launch & Core Concept - Command Code, a coding agent with taste, is launched after over a year of development [1] - The core idea is to build a coding agent that learns and adapts to a programmer's coding style and preferences, creating a personalized coding experience [3][4] - Command Code aims to address the sloppiness and lack of personalization in existing LLM-based coding tools [12][14][16] - Taste models are introduced as a way to capture and share coding intuition and intentions, potentially revolutionizing code generation [28] Technology & Architecture - Command Code utilizes a meta-neurosymbolic architecture with reinforcement learning to create a deterministic and explainable system [9][22][23] - The architecture combines LLMs with a "taste" model, which is a representation of the user's coding preferences [24] - Reflective context engineering enables the system to continuously learn and adapt to the user's evolving coding habits [25] - The system uses both explicit and implicit feedback to refine the neurosymbolic space and enforce the user's coding choices [24] Business & Market Opportunity - Langbase, the company behind Command Code, raised $5 million from investors [11] - The company aims to build a large ecosystem around taste models, enabling developers to share and leverage coding styles [27] - Command Code has shown internal gains at Langbase, with a 10x increase in code merged to the main repository and a significant reduction in code review time [32] - The product targets individual developers, teams, and enterprises seeking to improve coding speed, consistency, and maintainability [29]

Infrastructure Monitoring and Issue Detection - The system proactively monitors application infrastructure, including services, resource metrics (CPU, memory), and HTTP metrics (request error rate, failed requests) [5][8][9] - It analyzes metrics against predefined thresholds to identify affected services, moving beyond simple alert-based systems by analyzing a slice of time to reduce noise from spiky workloads [5][10][11] - The system gathers additional context for suspicious services, including project health, logs, and potentially upstream provider status, to avoid false positives due to high usage or external issues [12][13] Automated Issue Resolution - Upon detecting an issue, the system formulates a detailed plan, leveraging AI to analyze the application architecture, performance data, and errors [14][38] - A coding agent then clones the repository, creates a to-do list based on the plan, implements fixes, and generates a pull request [15] - The coding agent uses Open Code, an open-source AI agent, deployed on a server with necessary tools and Git configured, enabling it to open pull requests [22][23][25][26][27] Durable Workflows and Implementation - The system utilizes durable workflows to manage complex logic and ensure reliability, with automatic retries and caching of successful steps [16][18][19][20] - The workflow involves fetching application architecture, resource metrics, and HTTP metrics via API calls [21][31][32][34] - The system formats the collected information and passes it to the coding agent to generate a fix [33][35][37] Demonstration and Results - A demonstration showcases the workflow, starting from issue detection to the opening of a pull request with proposed changes [6][29][30][40] - The pull request includes a summary of changes, analysis, root causes, and fixes, allowing for review and merging [40][41] - The demonstration highlights a scenario where memory usage is high at 3196% GB out of a maximum of 32 GB, triggering the automated fix [33]

What's up everyone. It's Brace from Langchain and in this video I am extremely excited to announce our newest project openu. Open suite is an async cloud-based open source coding agent.What that means is you connect your GitHub account to open send it a task and it does the rest. It plans, executes the plan, writes code, runs tests, runs your different scripts, and then reviews the code before putting up a poll request to make sure it's all high quality code. And when it's done and it determines that everyt ...

Technology Stack - Codegen is used as the coding agent, powered by Claude 4 [1] - Google DeepMind Gemini 1.5 serves as the LLM for video RAG [1] - Streamlit is utilized as the UI [1]