ai coding agents
11 articles tagged ai-coding-agents.
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Claude Code reads your clone. Cursor reads similarity. Neither sees the graph.
Both agents can be handed more than one repo — but Claude Code only sees your clone and Cursor's index answers similarity. How to wire in the dependency graph.
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The repo your agent didn't clone is the one it breaks
Coding agents got cross-repo access this year. They still can't see the blast radius of a base-image bump — because that edge was never a function call, and it lives in a repo they never cloned.
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How to give GitHub Copilot cross-repo context today
Three working ways to get cross-repo context into GitHub Copilot right now — multi-root workspaces, Copilot Spaces, and MCP for the cloud agent — and the one question all three leave you to answer by hand.
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Monorepo vs polyrepo: the debate is measuring the wrong thing
Monorepo vs polyrepo is argued as a code-location debate. The real variable is whether "what depends on this" is queryable — and infrastructure never got a vote.
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Repo access was never the hard part
The multi-repo agent race is solving repository access. But access is plumbing — the cross-repo dependency graph is the part nobody upstream is parsing.
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Inferred context is not a dependency graph
An enterprise context engine makes your agent generate better code. A parsed dependency graph is the thing you gate a deploy on. Two jobs, two kinds of machinery, and why a confidence score is the wrong guarantee for the second one.
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Symbol graphs and artifact graphs: why Sourcegraph stops where infrastructure starts
Why Sourcegraph's symbol graph can't tell you who consumes your Helm chart at v3.2.0 — and why symbol graphs and artifact graphs are different categories.
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Cross-repo context is in product docs. The graph is not.
The vocabulary moved into vendor docs in sixty days. The parser-derived cross-repo dependency graph it describes hasn't shipped in any AI coding product.
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You don't need a virtual monorepo. You need a graph.
Two patterns give AI coding agents cross-repo context. The virtual monorepo scales by hand and breaks past ~100 repos; a queryable dependency graph scales by construction.
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AI coding agents need cross-repo context. The teams running them at scale are already building it themselves.
Three teams shipped the same diagnosis in two weeks: AI coding agents need cross-repo context. Two built the dependency graph substrate. One built around it.
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Meta needed 50+ AI agents to map their tribal knowledge. The most durable piece of their stack is the part you can build today.
A close read of Meta's April 2026 tribal knowledge engine, the academic paper they cited, and the architectural argument hidden inside both.