edgee: Instructions file for Codex

AGENTS.md

Context for coding agents working in this repository. CLAUDE.md is a symlink to this file.

What Edgee is

Edgee is an Agent Gateway, built in Rust by Edgee Cloud SAS (Paris) with a US subsidiary, Edgee Corporation (Delaware).

Edgee sits between AI agents and LLM providers as a transparent gateway. It intercepts, routes, compresses, meters, and secures every LLM request, with no code change on the agent side. It works with all major coding agents (Claude Code, Codex, Cursor, GitHub Copilot, OpenCode, CodeBuddy, Crush) and all provider plans, including consumer subscriptions — not just API credits.

Who it's for: engineering organisations (typically 150+ developers) whose coding-agent bills are growing fast and whose leadership lacks visibility and control over token spend. Buyers are VPs of Engineering, CTOs, and platform teams.

Core value: cut token costs by up to 70% while giving engineering leaders full control and visibility over agent usage.

Product pillars, in order of strategic importance

1. Smart routing and budget management — the moat. The routing engine can redirect requests to open-weight models mid-task without quality loss. The upcoming Strategies system lets customers define routing policies scoped to a person, a squad, or the whole organisation (e.g. a $100 weekly Claude budget: at 75% consumption Opus requests reroute to Kimi K3, at 85% Sonnet goes to GLM 5.2, at 100% everything routes to DeepSeek).
2. Team observability — cost and usage per developer, repo, PR, model, and environment.
3. Token compression — input trimming and output brevity, semantically lossless for coding tasks. A strong acquisition hook, but expected to become a commodity.

Positioning guardrails (apply to all user-facing copy)

• The category is Agent Gateway. Keep it. Lead with token cost reduction through routing and control — that's what converts and what wins POCs. Compression is a supporting feature, never the headline.
• Never write "Agent Engineering Platform" (or equivalents) in product copy. It reads as a platform for building agents — LangChain/CrewAI territory — whereas Edgee governs agents. The category label only broadens once the desktop app, Strategies, and skills/MCP management have shipped and been adopted.
• There is an expansion narrative — enter through cost reduction, become the control plane through which every AI agent in the company operates (routing, budgets, observability, skills, MCP, governance), the way Datadog expanded from infrastructure monitoring. It is reserved for the Series A deck, the vision page, and founder talks. It does not belong in the README, the CLI, the docs, or any copy you write here.
• Roadmap items may be named as roadmap items (see README) without implying a category change.
• Against OpenRouter and LiteLLM (the competitors seen in POCs): OpenRouter is a gateway for apps that consume LLMs; Edgee is specialised for agents, wrapping the agent itself with zero code change. Differentiators: agent-specialised, token compression, observability per developer/repo/PR rather than per API key, native 500-developer onboarding (seats, budgets, per-squad policies), and budget-driven Strategies with mid-task rerouting.
• Compliance facts that may be stated: SOC 2 and GDPR compliant, on-premise deployment available, BYOK supported.