6 months of AI-assisted dev across 37 repos: the bottleneck is suspiciously human
Xander-XGCS · reddit · 2026-11-05
An author with a finance/quant/systems background shares six months of scaling AI-assisted development across 37 repos.
Engineering infrastructure
- On-prem Proxmox virtualization with dedicated CPU/GPU, reproducible Nix environments, self-hosted CI, model/dataset registries, scheduling and validation services for research workloads.
- Agents work in separate Git worktrees with automated testing gates and defined integration/deployment procedures.
- A separate operations bridge lets independent AI sessions submit structured requests via GitHub; a persistent local service validates them against a whitelist before executing, so agents coordinate without unrestricted machine access.
Cost efficiency first
- Deliberately avoids new paid APIs, managed services, or always-running agents; leverages existing subscriptions, local compute, self-hosted runners.
- GitHub Issues isn't the ideal message bus but provides persistence, permissions, and a familiar interface — a less elegant process at lower cost isn't a problem worth solving.
Core finding: agents produced remarkable output, but the team spent surprising time building systems to manage the systems developing their systems — and the real bottleneck is human communication bandwidth.
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