AI coding agents: Claude Code, Cursor, GitHub Copilot for production

We run AI code agents for a living and try every new tool that ships. After 18 months of production use, the landscape clarifies. Most tools are good for prototyping. A smaller set is reliable enough for production work under operator review. Here’s our practical breakdown.

Claude Code (Anthropic)

Our primary for production engineering work. CLI-first, agentic by design, very good at long-context code understanding (entire repos), conservative on edits (less likely to invent or break things). Pricing is per token via API; for typical workloads ~€80–200/month per active developer-equivalent.

Where it shines: refactoring across multiple files, adding features that touch existing code, writing tests, debugging from stack traces. Where it’s weaker: greenfield architecture decisions — it executes well but doesn’t propose strong opinions.

Cursor

IDE-first. Excellent developer ergonomics for a human writing code with AI assistance. Less suited for headless agent runs but great if your engineers are pair-programming with AI. Pricing: €15–40/month per seat.

Where it shines: human-in-the-loop coding by senior developers. Where it’s weaker: batch tasks (writing a PR while you sleep).

GitHub Copilot

The original. Now bundled with GitHub. Strong at autocomplete, weaker at multi-file refactor. Best fit for teams already deep in GitHub workflow. €10–20/seat/month.

Where it shines: line-level completion. Where it’s weaker: agentic work, complex edits.

Codex / OpenAI

OpenAI’s coding offering, accessible via ChatGPT and API. Capable but we find Claude’s code outputs more reliable in 2026 for production-grade work. Your mileage may vary.

Gemini Code Assist

Google’s answer. Strong for Google Cloud Platform integration. Less mature than Claude or Copilot for general production work as of mid-2026.

Our actual stack

For Logitelia Dev AI Agents Teams:

• Claude Code as the primary execution layer for PRs.
• Cursor for the operator who reviews and edits.
• Both wrapped in our own agent orchestration + evaluation layer that catches the most common failure modes (made-up library names, broken tests, regressions).

What none of these tools fix

Architecture. Security review. Performance at scale. Database schema decisions. The judgment work. Code agents make a senior engineer 2–3x faster at writing code; they don’t replace senior judgment about what code to write.