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Search results for “Developer Tools”

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309 results for “Developer Tools”

  1. CodeRabbit reviews pull requests in the agent era

    #CodeRabbit#AI Code Review#Developer Tools

    The context is clear: coding agents and autocomplete tools create more changes in less time. That moves the bottleneck from writing to reviewing. A review tool like CodeRabbit is interesting not because it promises

  2. LM Studio brings local language models to regular computers

    #LM Studio#Local LLM#Private AI

    models such as Qwen, Gemma, DeepSeek and others, plus developer features such as a JavaScript SDK, Python SDK, CLI, MCP client and OpenAI-compatible API. That makes LM Studio a concrete tool for people who do not want to

  3. Muse Glimmer brings a 30B AI agent to local computers

    #Meta AI#Muse Glimmer#Open Weights

    2.0 license. It is designed for local AI agents that call tools, work with code, and process both images and text. Meta says a quantized version fits in under 20 GB. That does not target ordinary office laptops, but

  4. Amazon Q flaw shows the repo risk in coding agents

    #Amazon Q#AI Security#MCP

    Research publicly disclosed a vulnerability in Amazon Q Developer on 26 June 2026. The flaw, CVE-2026-12957, affected Language Servers for AWS before version 1.65.0 and could allow a crafted repository to execute

  5. Sim makes agent workflows visible and controllable

    #Sim#AI Agents#Workflow Automation

    to make that work more visible: Which steps run? Which tools are called? Where can a human check the result? What Sim actually does Sim provides a workspace for agentic workflows. Users can connect blocks, add

  6. OpenSkillRisk shows how risky agent skills can be

    #OpenSkillRisk#AI Agents#AI Security

    because agents no longer only write text. They install tools, read files, call APIs, and change real work environments. The central number is uncomfortable: in the experiments, even the safest tested configuration still

  7. Kimi K3 sharpens the open model race

    #Kimi K3#Moonshot AI#Open Weights

    to push a very large model with open weights into everyday developer workflows. If teams can test, fine-tune, or serve weights through their own providers, it changes their bargaining position against closed model APIs.

  8. Cohere Releases an Open Coding Agent for Private Teams

    #Cohere#North Mini Code#Open Source AI

    Code on June 9, 2026, its first model built explicitly for developers and coding agents. The core facts are simple: 30 billion total parameters, 3 billion active parameters per token, an Apache 2.0 license, weights on

  9. GPT-5.6 shows how political model launches have become

    #OpenAI#GPT-5.6#AI Safety

    model, and Luna as the fastest and cheapest option. For developers, OpenAI lists per-million-token pricing of $5 input and $30 output for Sol, $2.50 and $15 for Terra, and $1 and $6 for Luna. Two technical points stand

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