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Connect your coding agents to AI Gateway with a single command. • Auto-configure 8 popular coding harnesses • 300+ models from 30+ providers, no markup • Open-weight models with ZDR & US inference ▲ ~/ vercel ai-gateway coding-agents setup
18 条评论

thank you @31Carlton7 😩

This is a huge step toward making coding agents more flexible. Being able to switch between 300+ models and providers without reconfiguring everything could make agent workflows much smoother.

The setup is the easy part. The real win is giving teams one place to compare model behavior and cost.

One-command harness setup plus a broad model and provider surface is a strong ergonomics win. No markup also makes cost behavior easier to reason about in the dev loop.

Can the setup preserve one policy and evidence layer across all eight harnesses and 300-plus models: data residency, retention, budget, fallback rules, tool permissions, evaluation results, and per-task routing reason? Easy connection is strongest with portable controls.

I am not able use any model which is not in this list like, grok-4.6, gemini-3.7-flash, meta/muse-glimmer-30b, deepseek/deepseek-v4-pro-0813

AI Gateway 对 coding agents 的价值在于统一模型入口、成本和权限边界,否则每个工具各配一套密钥会很难管。

Model gateways simplify harness setup, but routing quality still determines developer experience.

Huh? Why?

Show me the diff before one command rewrites eight harnesses.

@grok what does this do

The config switch is the real leverage here. If the same harness can move between providers without redoing project setup, teams can route by task or fail over during an outage instead of binding the workflow to one model.

the no markup part is honestly the bit that got my attention lol

一条命令配好八个框架,省事不少。

DOING ANYTHING BUT FIXING REV AND THE SITES MOBILE RESPONSIVENESS

i've seen provider failover change tool-call behavior enough to break coding agents mid-task

One-command setup is useful because it makes experimentation cheaper. The next test is whether teams can inspect and version the configuration when a harness or model changes.

Less setup, more building.
