Field notes

The Dayside blog

We have been building the sell-side agent for years. First as Rover, on rtrvr.ai. Now as Dayside. These are the notes from along the way — benchmarks, protocols, architecture arguments. Kept exactly as published.

Thesis

Navigation Was Never the Moat: Why Agents Make the Sell Side Bigger, Not Smaller

Models will soon navigate any website perfectly. That was never the moat. The agent that converts is the one the seller owns — its accounts, its payments, its data — and the world's biggest retailer just proved it inside ChatGPT.

·Arjun & Bhavani

Research

The Four Architectures for Website AI Agents

RAG bots can only talk. API-tool agents ship a second maintenance org. Code sandboxes burn per-user server cost. Only DOM-native execution inherits the web's own truth model — live HTML, user session, existing IAM. A structural comparison.

·rtrvr.ai Team

Analysis

Protocol vs. Prompt Injection: How Agent-Website Communication Should Actually Work

Mintlify injected hidden instructions into copied markdown to get agent feedback. Here's why the web needs declared protocols — not clipboard injection — and how Rover built the right architecture.

·rtrvr.ai Team

Research

The Agent-Web Protocol Stack: A Research Thesis

The web's protocol stack was designed for humans behind browsers. A new consumer is arriving: AI agents. This paper maps the emerging protocol landscape and positions Rover as the missing execution layer.

·rtrvr.ai Team

Launch

Agent Analytics for AI Agents

AI traffic is becoming real product traffic. Agent analytics gives Rover-enabled sites the missing observability layer: visits, runs, trajectories, AX scoring, feedback, memory, and experiment-aware analytics for agent traffic.

·rtrvr.ai Team

Thesis

Chatbots Are Read-Only. The Web Isn't.

A technical teardown of why every RAG chatbot, vision agent, and CUA fails at the one thing websites actually need — and the DOM-native architecture that replaces them all.

·rtrvr.ai Team

Comparison

rtrvr.ai vs Claude for Chrome: The $200/mo Question Nobody's Asking

Anthropic's Claude for Chrome costs $200/month and uses dangerous debugger permissions. rtrvr.ai is free with your own API keys and achieves 81.4% success rate using safe Chrome Extension APIs. Here's why architecture matters more than marketing.

·rtrvr.ai Team

Comparison

rtrvr.ai vs Browser Use vs Skyvern vs Firecrawl: The Agentic Cloud Showdown

We put the three biggest names in web agents to the test on a real-world task: extracting members from a private club. Here is why 'Black Box' clouds fail where Interactive Clouds succeed.

·rtrvr.ai Team

Deep Dive

rtrvr.ai DOM Intelligence Architecture: Why Screenshots Reduce Performance

A deep technical dive into rtrvr.ai's Chrome Extension-based architecture, Smart DOM Trees, and why we don't use CDP. Learn how DOM-native intelligence outperforms vision-based agents.

·rtrvr.ai Team

Benchmark

rtrvr.ai vs Firecrawl vs Parallel: Context Engineering is All You Need

I ran rtrvr.ai, Firecrawl, and Parallel on Reddit, ChatGPT.com, and Amazon. Only one returned full, structured data. The bigger lesson: context rot is quietly killing most AI agents.

·rtrvr.ai Team

Product

rtrvr.ai Browser as an API: The Power of Remote MCP

We've moved beyond local-only MCP, turning the browser extension into a remote server. This unlocks a new paradigm of cross-app agent collaboration, BYO subscriptions, and distributed workflows.

·rtrvr.ai Team

Benchmark

rtrvr.ai achieves SOTA Performance on Halluminate Web Bench

rtrvr.ai leads in Web Bench across task completion, speed, and cost — achieving 81.4% success rate while being 7-23x faster than competitors.

·rtrvr.ai Team

Guide

Turn Your Website into an AI Agent: Integration Guide

Step-by-step guide to adding Rover to your website. Script tag, npm, React, Vue — from setup to production in minutes.

·rtrvr.ai Team

Technical

DOM-Native vs. Screenshot Agents: Why Architecture Matters

A technical comparison of DOM-native and screenshot-based approaches to embedded web agents — speed, accuracy, cost, and security.

·rtrvr.ai Team