{Insights}
Oct 16, 2025
by alchemain team
AI Coding Assistants Can't Own Dependency Management: 00felix can.
AI coding assistants are an exciting advancement in DevOps technology. They are powerful tools that boost developer velocity by reducing manual work and suggesting vulnerability fixes. They can even propose version bumps, run tests, and attempt to patch basic breakage. The latest advancements in AI coding assistants provides greater visibility into the entire repo, for example through integration with GitHub Copilot and GitHub MCP server and Dependabot.
But here’s the uncomfortable truth: No coding assistant, no matter how powerful can own the lifecycle of dependency management, which means even the best AI coding assistant is a half-measure that pushes work back onto your team, leaving the hardest problems untouched.There are two main problems:
1. Failures Happen Outside the Editor: An AI coding assistant sees a project file, and through integrations it may even see the entire repo, but it doesn't understand the build lifecycle, the dependency map or the whole operational environment. Dependency failures don't happen in the code editor; they happen during compilation, test execution, or when a new library clashes with your actual runtime (e.g., a sudden requirement for JDK 21 on a production system running JDK 17). Assistants don’t control the build graph, they don’t understand toolchain drift, and they cannot execute the iterative compile → test → fix loops required to safely modernize a codebase.
2. Engineers Become the Automation: When a simple version bump cascades into transitive conflicts, CI chaos, or toolchain shifts, an engineer is needed to step in. The overreliance on the "human in the loop", necessary to constantly prompt the assistant, debug incorrect answers, and manually untangle broken builds can’t help but slow everything down and increase costs. You’re trading one kind of manual work for another, and you’re not actually solving your original problem.
The Difference Between Helping and Owning
Where assistants help, 00felix delivers. Where assistants suggest, 00felix guarantees. And where assistants stop in their tracks, 00felix self-heals. The distinction lies in both responsibility and execution:
Area | AI Coding Assistants | 00felix |
Where does it operate? | Inside the IDE with whatever context the developer gives it. | Inside the build pipeline with full visibility into manifests, dependency graph, compiler and test outputs. |
Who owns the problem? | Helps the engineer fix things; developer still debugs, validates, and retries. | Fully owns the upgrade lifecycle — analysis → refactor → compile → test → fix → PR. |
How does it handle breakage? | Stops at the first compile/test failure; requires manual prompting + troubleshooting. | Runs a self-healing compile → test → fix loop until the build is green or hands off a precise failure report. |
How deep is its understanding of dependencies? | Limited; can’t reason about transitive dependencies or version conflicts without extensive prompting. | Builds a complete direct and transitive dependency graph, detects API diffs, resolves conflicts, and plans safe upgrade paths. |
What is the outcome? | Code suggestions that might work but could still lead to red builds. Developer must validate everything. | Merge-ready, validated PRs with real compiler and unit test signals — not guesses. |
While a coding assistant can help chase down a vulnerability and suggest a fix, it still needs a chaperone to watch the build and validate the change. And ultimately, this is why 70% of bot-created PRs never merge and 60% of upgrades break builds in the real world.
You are paying both in time and reliability for “automation” that still expects developers to finish the job.
00felix runs within the pipeline, absorbing the full cost of breakage. It returns either a merge-ready pull request or a precise explanation of why the automation can't proceed. This means:
Upgrades no longer block sprints or derail releases.
Security patches do not become fire drills.
Technical debt doesn't accumulate silently
Developers are freed from fixing the same dependency issues repeatedly.
The right tool for dependency management should own the full lifecycle, so your product teams don't have to. If you’ve caught yourself saying, “Our assistant helps us patch vulnerabilities”, “Our in-built tool is good enough most of the time”, or “Our engineers can fix whatever breaks” try 00felix for yourself here and see the difference.
