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Adobe vs Google Gemini

Adobe scores higher on the AgentReady, 51/100 against 35/100. They differ on 7 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Adobe. Adobe products and services empower developers to create memorable digital experiences through developer creativity

Google Gemini. Gemini is Google's AI assistant and conversational AI model.

Where Adobe is ahead

Adobe passes clear canonical domain, clear product positioning and llms-full.txt / full agent docs, and Google Gemini does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: structured api reference. Google Gemini misses it.

And on operate, observable execution and agent compatibility verified. Google Gemini misses those.

Where Google Gemini is ahead

Google Gemini passes authentication documented, and Adobe does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.

What neither does

Both fail public docs discoverable, llms.txt published, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented, self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Adobe leads 80 to 53. Adobe misses public docs discoverable, llms.txt published; Google Gemini misses clear canonical domain, clear product positioning, public docs discoverable, llms.txt published, llms-full.txt / full agent docs.

Understand. Adobe leads 31 to 23. Adobe misses openapi / spec quality, authentication documented, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Google Gemini misses structured api reference, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented.

Adopt. Both sit at 40/100 here. Adobe misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart; Google Gemini misses self-service signup, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart.

Operate is whether an agent can run against it in production and recover when a call fails. Adobe leads 53 to 24. Adobe misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable; Google Gemini misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, observable execution, agent compatibility verified.

Pricing

Adobe does not publish a machine-readable starting price. Google Gemini does not publish one.

Signal by signal

Which to pick

Adobe clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Adobe and Google Gemini. Alternatives to each: Adobe, Google Gemini.

An agent can fetch this as data: POST /v1/compare {"slugs": ["adobe", "gemini"]}