Blog

Research and guides on making products easier for AI agents to discover, recommend, and use.

Announcements

Lightsage raises $4M to build the growth stack for AI agents

Lightsage announces $4M in funding led by Nexus Venture Partners to build the Agent-Led Growth platform, helping software companies understand and improve how AI agents discover, use, and pay for their products.

Author: Jun Liang Lee
Date: Sep 08, 2026
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Guides

Your coding agent traffic is not captured by GA4

Coding agents read your docs without running your analytics snippet, so their visits end up as bot noise, as Direct, or nowhere. Why it happens, and three checks to see how much you're missing.

Author: Charmayne Lim
Date: Oct 20, 2026
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Coding agents are recommending your competitors. You can't see it.

When a coding agent picks an API, it leaves no search query, ranking or referrer for your analytics. What disappears, why the pick sticks, and how to find out who agents choose.

Author: Charmayne Lim
Date: Oct 19, 2026
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There's a new buyer, and it doesn't read your homepage

Coding agents now find, try and pick developer tools for developers. What they judge you on, why your funnel can't see it, and one test to run today.

Author: Charmayne Lim
Date: Oct 18, 2026
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Lightsage vs. Profound: AI Visibility for Developer Products

Compare Lightsage and Profound for AI visibility. Learn when to focus on answer-engine brand representation versus coding-agent discovery and execution.

Author: Jun Liang Lee
Date: Oct 08, 2026
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How Do I Get Recommended by AI Coding Agents?

Help coding agents discover, choose, and use your developer product. A practical guide to documentation, product interfaces, competitor testing, and measurement.

Author: Jun Liang Lee
Date: Oct 04, 2026
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What Is Agent-Led Growth?

Agent-Led Growth is a go-to-market strategy for winning customers whose AI agents discover, evaluate, select, and use products on their behalf.

Author: Jun Liang Lee
Date: Oct 04, 2026
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AI Agent Evaluation Platforms Compared for APIs

Compare platforms for testing how AI agents authenticate, call developer APIs, recover from errors, and complete real integration tasks.

Author: Jun Liang Lee
Date: Sep 01, 2026
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Best CLI Usability Scoring Platforms for AI Agents

Compare CLI usability scoring platforms for AI agents across authentication, non-interactive use, JSON output, task completion, cost, and errors.

Author: Jun Liang Lee
Date: Sep 01, 2026
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MCP Compatibility in 2026: A Complete Evaluation Guide

Learn how to evaluate MCP compatibility across coding agents with protocol checks, task benchmarks, trace analysis, safety tests, and an actionable scorecard.

Author: Jun Liang Lee
Date: Aug 31, 2026
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What Is Agent Experience (AX)? A Guide for AI-Native Products

Agent Experience is how well AI agents can discover, understand, choose, and use your product. Learn the AX lifecycle, metrics, and practical improvements.

Author: Jun Liang Lee
Date: Aug 30, 2026
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7 Factors That Influence Which APIs Coding Agents Recommend

Why does Claude Code recommend Stripe over Square? The 7 factors that determine which APIs coding agents suggest, from 70+ benchmarks.

Author: Jun Liang Lee
Date: Aug 29, 2026
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How Coding Agents Actually Decide Which CLI to Use

From training data to shell execution: the 4-layer stack that determines whether Claude Code recommends your CLI tool over a competitor's.

Author: Jun Liang Lee
Date: Aug 29, 2026
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How to Track Agent Recommendations Across API, SDK, CLI, and MCP

Your API might rank #1 while your CLI is invisible. Here's how to measure visibility across all 4 surfaces coding agents use to discover developer tools.

Author: Jun Liang Lee
Date: Aug 29, 2026
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Why AI Agent Traffic Looks Invisible or Direct in GA4

GA4 relies on client-side JavaScript that AI agents often skip. Here's the technical explanation for why agent traffic disappears or shows as Direct.

Author: Jun Liang Lee
Date: Jun 27, 2026
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How to Track AI Recommendations for Your API (2026 Guide)

Track AI recommendations for your API and compare popular platforms for monitoring brand sentiment across answer engines and coding agents.

Author: Jun Liang Lee
Date: May 09, 2026
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The Devtool Visibility Stack in 2026: What API Teams Need to Measure

AI coding agents are a primary discovery channel for devtools. Here's the measurement framework API teams need in 2026.

Author: Jun Liang Lee
Date: May 07, 2026
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Best GEO Tools for Dev Tools 2026: Lightsage vs Profound vs Otterly

The best GEO tools for devtools compared. Which tracks coding agents? Which tracks ChatGPT? Lightsage vs Profound vs Otterly vs AthenaHQ breakdown for API teams.

Author: Jun Liang Lee
Date: May 05, 2026
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How Coding Agents Actually Decide Which SDK to Use

From training data to web search to tool calls — the 4-layer stack that determines whether Claude Code recommends your SDK.

Author: Jun Liang Lee
Date: Apr 27, 2026
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AEO/GEO for Dev Tools: Why Profound & Otterly Don't Work for APIs

GEO for devtools requires tracking coding agents, not just ChatGPT. Learn why consumer GEO tools fail for APIs and what to measure instead in 2026.

Author: Jun Liang Lee
Date: Apr 17, 2026
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We Tested 70+ APIs in Claude Code & Codex: What Actually Works

We tested 70+ APIs in Claude Code and Codex with live API keys. Here's what separated top performers from invisible APIs.

Author: Jun Liang Lee
Date: Apr 09, 2026
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Why Claude Code Isn't Recommending Your Library (And How to Fix It)

Great docs but AI agents never suggest your SDK? The 4 reasons Claude Code and Codex skip your library — and how to fix them.

Author: Jun Liang Lee
Date: Apr 01, 2026
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