For Developer Tools
AI Agents Pick Your Competitor 91% of the Time. You Don't Even Know It.
Based on 2,430 prompts across three Claude models, AI coding agents have already formed near-monopoly preferences. Stripe: 91.4%. Vercel: 100%. Is your dev tool on the list, or on the outside?
Near-Monopolies Form Fast. Yours May Already Be Lost.
In the Amplifying.ai study, Vercel captured 100% of JS deployment picks. Stripe took 91.4% of payment processing. But Prisma went from 79% agent selection to 0% in a single model update. The difference? Training data recency. If your documentation isn't in the latest training corpus, you don't exist to agents. And unlike Google rankings, there's no Search Console to tell you.
Perfect For
Built for teams who need to understand their AI presence
VP of Product
Know if agents choose your tool or build custom alternatives, before it shows up in churn data
VP of DevRel
Track whether developer content actually translates to agent selection, not just awareness
Product Marketing
Build competitive intel from the agent decision layer that G2 and Gartner can't see
How It Works
Add Your Dev Tool
Enter your product, category, and key competitors. We start querying agent-style prompts across 22+ AI models immediately.
Monitor Agent Decisions
See when agents pick you, a competitor, or build custom. Track selection rates by model, model version, and prompt type.
Act on Signals
Get playbooks for improving training data recency, API simplicity scores, and documentation presence in agent training corpora.
From invisible to instrumented
Know your agent selection rate, spot recency fade before it kills your numbers, and track the build-vs-buy threat in your category.
Invisible to AI coding agents
Tracking agent selection in real time
What you'll get
Everything you need to understand and improve your AI visibility.
- Track your agent selection rate across Claude, GPT, and Gemini
- Get alerted when training data shifts drop your ranking
- Monitor the build-vs-buy threat in your category
- See exactly which competitors agents prefer and why
Agent Selection Rate
Your tool's pick rate across agent-style prompts vs every competitor. The metric that npm downloads can't show you.
Training Data Recency Tracking
Know when a model update shifts your visibility. Catch the Prisma problem (79% to 0%) before it happens to you.
Build-vs-Buy Alerts
In 12 of 20 categories, agents build custom instead of using a vendor. Know if DIY is your real competitor.
A Blind Spot in Your Developer Intelligence
You track downloads, stars, and search rankings. But none of those tell you what happens when an agent picks tools.
Developer popularity, adoption trends
Agent selection behavior
Search visibility, keyword rankings
Coding agent recommendations
Agent selection rate, recency tracking, build-vs-buy across 22+ models
Nothing in agent decisions
Common Questions
Answers to what you're probably wondering
Do AI agents really influence tool adoption?
Yes. Amplifying.ai tested 2,430 prompts and found 73% run-to-run consistency in agent selections. Tools like Stripe (91.4%) and Vercel (100%) show near-monopoly concentration. These aren't random picks. They're patterns shaped by training data, API simplicity, and documentation quality.
What's the build-vs-buy threat?
In 12 out of 20 categories, DIY was the #1 'competitor' with 252 total picks across the study. Agents will write their own solution rather than use a tool they find complex. If your integration takes more than a few lines of code, you're competing against 'just build it.'
Can I actually change my agent selection rate?
Yes. Selection correlates with training data recency, API simplicity, and documentation presence in recent tutorials. An ArXiv study showed product description changes can shift agent selection by 80+ percentage points. The signals are measurable and actionable.
Stop being invisible to coding agents
See your agent selection rate across Claude, GPT, and Gemini. Know where you stand before your competitors do.