What is coding ops?
Coding ops is the operational discipline for AI-assisted software development: governing the cost, consistency and visibility of the coding agents a team runs, the way DevOps governed how teams ship. It emerged because coding agents arrived as individual tools — one developer, one agent, one bill — and organizations adopted them by the hundred without an operational layer.
The forcing functions are measurable. Per-developer agent spend runs $150–250/month in enterprise deployments and $400–1,500/month for heavy agentic users — at team scale, a six-figure budget line with no owner. Meanwhile every major agent moved to usage-based billing in 2025–2026 (Cursor's credit pools, Copilot's AI Credits), which converts agent inefficiency directly into invoices.
Coding ops asks four questions of an engineering org:
- What do our agents cost, and where? — per-repo and per-team attribution, not a monthly total
- Is agent output consistent? — one team's conventions, or each developer's agent drifting its own way (LLM steering)
- What did the agents do? — decisions, changes, failures: visibility without surveillance
- Do agents share context? — or does each one rediscover the codebase alone (memory ops)
Coding ops is the software-engineering specialization of agent ops. The cost mechanics underneath it are in token optimization for AI coding agents; unerr is the control plane built for exactly this job — flat-rate per seat, across every agent the team already uses.