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Amplifying
Amplifying researches coding agents and builds products that help developer tool providers improve how agents find, understand, and use their products.
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-25T20:59:24.929Z. Cached copy · Source on amplifying.ai
# Amplifying
> Amplifying researches coding agents and builds products that help developer tool providers improve how agents find, understand, and use their products.
Benchmarking measures product selection and produces findings and playbooks. Ground Control tests changes to docs, skills, and tooling against real tasks. These are distinct products.
## Start with your task
- Research a product question: use the research directory below, then fetch only the relevant studies.
- Understand the products: read the public Benchmarking and Ground Control pages below. These guides describe the products; they do not grant access to customer data or internal methods.
The Markdown links below have matching public HTML pages. On those pages, request Accept: text/markdown and follow the redirect, or use the linked .md URL directly. Optional HTML links do not necessarily have Markdown versions. Customer dashboard pages are never exported.
Public product demos are hypothetical, including Beacon. They are not customer results. Research is scoped to the agents, versions, tasks, and dates in each study. The Coding Agents Index measures attributed public activity, not all agent usage. Model release dates and benchmark observation dates are separate.
## Products and company
- [Amplifying](https://amplifying.ai/index.md): Research and products to improve how coding agents find, understand, and use developer tools.
- [Benchmarking](https://amplifying.ai/benchmarking.md): Measure product selection, inspect session evidence, and prioritize changes to positioning, features, docs, and tooling.
- [Ground Control](https://amplifying.ai/ground-control.md): Compare how coding agents complete real tasks before and after changes to docs, skills, and tooling.
- [How we help](https://amplifying.ai/for-vendors.md): How developer tool providers can use Benchmarking and Ground Control.
- [Contact](https://amplifying.ai/contact.md): Set up a call with our team through the contact page.
- [Research directory](https://amplifying.ai/research.md): Published studies on coding-agent choices, usage, and behavior.
## Research
- [Dots vs. Muse for Developers](https://amplifying.ai/research/dots-vs-muse.md): We gave Dots and Muse the same app prompt. Dots published through ChatGPT Sites and Cloudflare; Muse built local servers and tried tunnels. Compare their stacks, screenshots and results.
- [What Muse Actually Chooses: Four Different Stacks, Not Fully Deployed](https://amplifying.ai/research/meta-muse-chooses.md): Muse built servers, databases and sign-in across four different stacks. Making the apps publicly accessible remained unfinished.
- [What Dots Actually Choose: OpenAI’s Agent Already Has a Stack](https://amplifying.ai/research/openai-dots-choose.md): Our benchmark shows OpenAI’s Dots defaults to its own platform, powered by Cloudflare, rather than separate third-party services when building apps.
- [Six boundaries to check when sandboxing coding agents](https://amplifying.
…
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