AI agent builders, as AI assistants see them

In the week of 19 October 2026, the AI assistants we track most often recommend LangChain (47), n8n (25) and OpenAI AgentKit (25) for ai agent builders, out of 38 products we follow in this category. Scores are the share of 58 answers naming each product, across 3 assistants.

Out of 38 AI agent builders tracked, LangChain sits clearly in front with an overall score of 47, named in 50 of 73 answers. That's nearly double second-place OpenAI AgentKit, which scores 25 and appears in 33 of 73 answers. Right behind, n8n also scores 25 but edges ahead on mentions, showing up in 35 of 73 answers. CrewAI trails closely at 24 (34 of 73 answers), while Pydantic AI rounds out the top five at 17, despite a standout 42 from Claude against just 7 from ChatGPT and Perplexity. One leader, then a tight pack fighting for second.

Updated 2026-10-19. We re-ask every assistant on a schedule and publish whatever they say.

sampled: 3 of 4 assistants this week

This week's movers

n8n ↑ climbing +7

Leaderboard

#	product	score	vs last week
1	LangChain	47	steady
2	n8n	25	↑ climbing +7
3	OpenAI AgentKit	25	steady
4	CrewAI	24	steady
5	Pydantic AI	17	steady
6	Zapier Agents	16	steady
7	Microsoft Copilot Studio	13	steady
8	Dify	12	steady
9	Make	12	steady
10	Vertex AI Agent Builder	12	steady
11	Mastra	11	steady
12	Amazon Bedrock AgentCore	10	steady
13	Microsoft Agent Framework	10	steady
14	Lindy	8	steady
15	Voiceflow	8	steady
16	LlamaIndex	7	steady
17	Relevance AI	7	steady
18	Claude Agent SDK	6	steady
19	Gumloop	6	steady
20	Vercel AI SDK	6	steady
21	Flowise	5	steady
22	Microsoft AutoGen	5	steady
23	Retell AI	4	steady
24	Vapi	4	steady
25	Bland	3	steady
26	Botpress	3	steady
27	Langflow	3	steady
28	Letta	3	steady
29	Semantic Kernel	3	steady
30	Synthflow	3	steady
31	Agno	2	steady
32	Pickaxe	2	steady
33	Taskade Genesis	2	steady
34	xpander.ai	2	steady
35	Coze	1	steady
36	Dust.tt	1	steady
37	Rasa	1	steady
38	Stack AI	1	steady

Where the assistants get their answers →

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Built from this week's run — who wins now, the exact questions we ask, the pages the assistants cite, and six steps in order.

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Score = how often an assistant names the product, weighted by position. Full explanation.