Datadog

datadoghq.com

B2BRank #03 of 309 agent-blocking issuesMethodology ar-1.0

62/100

Mostly Ready

How an agent reads Datadog

Journey Completability

10/20

Everything behind a form

Agents can't fill arbitrary human forms; gating blocks autonomous completion.

Fix: Let agents self-serve the core path; reserve forms for genuinely human steps.

+2 more issues flagged in this dimension.

B2B Conversion Signals

5/10

Pricing is unclear

An agent assessing fit needs a price signal; if it can't find one it ranks you below rivals that show it.

Fix: Publish clear pricing, or at least transparent ranges and starting points.

+1 more issue flagged in this dimension.

Agent-Readable Content

12/20

Content only loads with JavaScript

Many agents read raw HTML and don't run heavy JS — your value prop and products effectively don't exist to them.

Fix: Server-render or pre-render critical content so it's present in the HTML.

+1 more issue flagged in this dimension.

Agent Discoverability

13/20

No llms.txt file

Without it an agent guesses your structure from raw HTML and often misses pricing, products or the path to buy.

Fix: Add an /llms.txt summarising your offering, key URLs, and how to buy or book.

ICP Signal Clarity

14/20

Unclear what you offer

If an agent can't classify your offering fast it can't match you to the buyer's need and moves on.

Fix: Lead with a plain one-line description of what you do and for whom.

Trust & Proof

8/10

No agent-blocking issues flagged here.

The fast win

Now

→

Projected

Publishing a tailored llms.txt and structured-data block alone would lift Datadog by +18 points to AI Ready — no re-platforming required. Actum generates both files automatically from a scan.

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Scored by the Actum agent-readiness engine (ar-1.0) against the live datadoghq.com on 8 June 2026. Scores reflect how readable and completable the site is for autonomous AI buying agents, not its quality as a human-facing experience. Datadog is not affiliated with Actum.