I am Anand B - Co-Founder at Arbor, computer science student at VIT Vellore, and a systems builder obsessed with making complex software legible.
My main bet is Arbor: graph-native code intelligence that maps a repository with ASTs, walks the real call paths behind a pull request, and gives humans and coding agents the exact blast radius before merge.
The same commit should produce the same answer. Deterministic context beats plausible guesswork.
Generated every day by a pinned GitHub Action. No request-time stats API, no sleeping dyno, and the last good card survives a failed refresh.
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The map AI coding agents are missing. A Rust graph engine, PR blast-radius system, and MCP context layer built around deterministic program understanding instead of embedding-based RAG.
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Ground truth for APIs used by coding agents. Blocks the APIs that do not exist and serves the ones that do - one index, queried in both directions.
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Structural weight paging for consumer GPUs. Experiments in local adapter routing, just-in-time model state, and the telemetry needed to know when the system is actually winning.
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A safer, bloat-free Lenovo Vantage replacement. A Windows-first control plane with read-only discovery, explicit capability evidence, and a short-lived elevated broker for guarded hardware access.
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More systems from the lab
- Runoscope - the portable HAR file for AI coding-agent runs.
- Agent Lens 2.0 - visual debugging for agent workflows.
- Zubaan - live multilingual compliance checks for Indian financial sales.
- FinShield - financial document forensics and graph investigation.
- witr - process, port, and service causality diagnostics.
I optimize for determinism over vibes, local-first over rented black boxes, instrumentation before optimization, and safety gates before privileged writes.
Languages: Rust Python C# / .NET TypeScript Dart
Systems: AST parsing code graphs MCP agent observability local AI Windows internals
Default posture: build deeply -> measure honestly -> ship relentlessly