Code-first engineering intelligence is having its moment
Gartner’s latest research reinforces a growing reality: code is the most reliable source of engineering insight.
Codebase intelligence
Codebase navigation, technical debt, identifying signals in messy repos, architectural mapping, and ground-truth visibility. Understanding the reality of your code without having to read every single line.
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Why we built Flux, and where we’re taking it
Today we’re announcing $5 million in new funding led by Calibrate Ventures, with participation from True Ventures and Glasswing Ventures.
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In the age of LLMs, token usage is a recurring topic
Discover how to filter garbage data from code repositories for LLMs. We share insights from building tools to ensure only useful data is processed for models.
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The signals senior engineers read that juniors don’t (yet)
Ramping in a new codebase is about reading the right signals—where work is happening, what kind it is, and where things keep breaking.
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Your Life Preserver for the AI Flood: A Code Analysis Tool
AI-written code is flooding codebases with speed and risk, and engineering teams need a code analysis tool alternative to track, understand, and triage what’s in their repos.
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Tricking the LLM into Vibe Coding
Can ChatGPT be coaxed into writing bad code? Our summer intern tried everything—from existential pleas to mafioso-esque threats—in the name of testing Flux’s detection powers.
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The Engineering Leader’s Dilemma: Balancing Expectations and Team Productivity
Effective engineering stakeholder management means creating systems that balance stakeholder demands with developer focus—minimizing interruptions, boosting productivity, and enabling faster, more informed decision-making.
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The State of Code Reviews: Modern Code Review Approaches and Tools
Modern code review is evolving fast—engineering leaders must adapt to AI-driven complexity, distributed teams, and rising pressure on code quality.
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The Hidden Costs of Fragmented Code Evaluation Tools – And How to Fix Them
Fragmented code evaluation tools create inefficiencies, increase costs, and reduce developer morale. AI-powered solutions offer a better path forward.
