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@gitarcode

Gitar

@gitarcode
AI code review that fixes your code, not just comments. Try free for 14 days.
San Mateo, CA
gitar.ai
Joined November 2023
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  • Pinned
    @gitarcode
    Gitar
    @gitarcode
    May 21
    Gitar is joining @SonarSource today 🚀🚀 We built the AI code review solution enterprises needed: one that doesn't just find issues, but fixes them. Now it's part of SonarQube, the platform they rely on to ensure the quality, security, and architectural integrity of everything
    @SonarSource
    Sonar
    @SonarSource
    May 21
    Sonar has acquired @gitarcode 🎸 Together, Sonar and Gitar will cover AI code verification from pull request to production, delivering the most complete answer to how enterprises move fast with AI without breaking things. Learn more: bit.ly/3RikLKN
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  • @gitarcode
    Gitar
    @gitarcode
    Mar 25
    New Gitar pricing is live - gitar.ai/pricing Core: $20/user/mo Pro: $40/user/mo Unlimited PRs on both. Unlimited repos on both. Here's what you get:
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  • @gitarcode
    Gitar
    @gitarcode
    Mar 10
    Not every AI output should reach the user. A guardrail layer sits between what your agent wants to say and what it actually posts. It reads context, makes a call, and sometimes the right answer is silence. We wrote about how we built ours what it takes to get it right.
    @gitarcode
    Gitar
    @gitarcode
    Mar 10
    Article cover image
    Article
    Guardrails for A Multi Agent System
    Every AI system that talks to people needs a way to make sure it's saying the right things. Not just accurate things but the right things, to the right person, at the right moment. That layer has a...
  • @gitarcode
    Gitar
    @gitarcode
    Mar 10
    Article cover image
    Article
    Guardrails for A Multi Agent System
    Every AI system that talks to people needs a way to make sure it's saying the right things. Not just accurate things but the right things, to the right person, at the right moment. That layer has a...
  • @gitarcode
    Gitar
    @gitarcode
    Feb 6
    We switched to a 5x cheaper LLM. Our costs went up. Cost per outcome beats cost per token. A model that finishes in one pass at $3/MTok is cheaper than one that loops at $0.60.
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