JSON

product on 11 shows · 12 statements across 11 episodes · said 30 times in 21 episodes since 2013

the MAD Podcast 11 Latent Space 10 the a16z Podcast 4 Top Founders 2 the Y Combinator Startup Podcast 1 Starter Story 1 the Startup Ideas Podcast 1 Lenny's Podcast Sourcery Big Technology TBPN

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12 statements about JSON, every show

Unclosed JSON syntax is the primary cause of model tool hallucinations
“The challenge with tool calling more and more seems to be that the companies want certain tool calling, which is a very sensitive thing to train. And because you're dealing with all of the JSON outputs, if it doesn't like close the end of the request in a very…”
Ali Taha Aug 3, 2026 ▶ 7:57 Next 100x in AI: Inference, Networking, & Self-Optimizing Models — Philip Kiely & Ali Taha, Baseten
LENNY'S PODCAST Assertion Not checkable as stated
Penn: 80% of early Claude instruction failures were invalid JSON outputs
“And what I saw was something like 80% of what people meant in the early days for this failure was Claude would not write the right JSON.”
Dianne Penn Jul 26, 2026 ▶ 45:25 Why AI is going vertical (again) | Dianne Penn (Anthropic)
LENNY'S PODCAST Assertion Not checkable as stated
Penn: Claude scores 99.9% to 100% on JSON schema formatting evals
“When we have versions of Claude, we actually run that eval and just check. I think at this point it's always a hundred percent or like 99.9. And so it's no longer a pain point.”
Dianne Penn Jul 26, 2026 ▶ 46:14 Why AI is going vertical (again) | Dianne Penn (Anthropic)
SOURCERY Insight
Field: Jailbreaking AI models requires conversational questioning rather than fancy JSON
“It's not like you have to do some fancy JSON thing. Like, that's what people like to popularize it online with, but I mean, you can just talk to them and ask them questions.”
Dylan Field Jul 2, 2026 ▶ 31:04 Dylan Field on the “Permanent Underclass of Zero Taste” · Sourcery with Molly O'Shea
Roy: Chunking Agent Context Into JSON Drops Token Use 70-80%
“Instead of using a giant CSV file as context in the agentic workflow, let's turn it into a JSON. Actually, let's chunk it into multiple different JSONs and only call, like, getting that technical, but like, that dramatically would reduce the actual tokens cons…”
Ranjan Roy Jun 2, 2026 ▶ 18:17 Warning Signs For The AI Boom, Anthropic Passes OpenAI, Robinhood’s AI Trading
Isenberg: Formatting prompt text in JSON improves AI text rendering accuracy
“If you include the text in a JSON format, it's more likely to give you the right text.”
Greg Isenberg Jun 25, 2025 ▶ 12:22 Genspark vs ChatGPT, my brutally honest review
TBPN Insight
Brown: OpenAI's o3 already achieves practical program synthesis
“Like when people say program synthesis, like we're already there, like O three is program synthesis, but the programs are like JSON and Python.”
Will Brown Apr 26, 2025 ▶ 9:37 Why Humor Is the True Test of AI Intelligence | Will Brown on TBPN
Pokrass: Use XML for structuring LLM inputs and JSON for parsing outputs
“I do think XML is very helpful for structuring prompts, whereas for parsing outputs maybe the story is a bit different. Like sometimes it's really useful to get outputs in JSON, so you can plug them directly into your application. But I do think the models wor…”
Michelle Pokrass Apr 15, 2025 ▶ 24:38 GPT 4.1: The New OpenAI Workhorse
Schluntz: JSON Escaping Overhead Degrades LLM Performance Across the Board
“Like if you're trying to output a code in JSON, there's a lot of extra escaping that needs to be done. And that actually hurts model performance across the board. Where versus like if you're in just a single XML tag, there's none of that sort of escaping that …”
Erik Schluntz Nov 28, 2024 ▶ 36:44 The new Claude 3.5 Sonnet, Computer Use, and Building SOTA Agents — with Erik Schluntz, Anthropic
LATENT SPACE Assertion Supported
Harrison Chase says TypeScript yields better LLM tool-calling performance than JSON
“I saw some paper that used TypeScript notation instead of JSON notation for tool calling and it got a lot better performance.”
Harrison Chase Sep 27, 2024 ▶ 46:42 Language Agents: From Reasoning to Acting — with Shunyu Yao of OpenAI, Harrison Chase of LangGraph
MAD Insight
Schemaless JSON fails as companies scale beyond 50 employees
“It works well, like, if you're, like, a ten-person company, or, like, even to a fifty-person company, when you're, like, scaling to, like, thousands of people, like, you actually need a proper negotiation in between.”
Praveen Murugesan Sep 30, 2016 ▶ 6:56 The Uber Big Data Story // Praveen Murugesan, Uber (Data Driven NYC / FirstMark)
MAD Prediction Held up
Merriman: JSON document models will emerge as the standard NoSQL data model
“My belief, which is opinion, is that in, in the end of these NoSQL data models, that the document-oriented model will be the one that kind of converges on for standard, and specifically JSON style, or JSON based.”
Dwight Merriman Dec 5, 2013 ▶ 13:07 Fireside chat with Dwight Merriman // Data Driven #8 // Sep 2012 (interviewed by Matt Turck)

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