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Delphi Pythia
Research platform that measures which arguments change minds
Polls tell you what people think. Focus groups tell you what they say. Neither tells you which arguments actually change minds. Ask an LLM what the public thinks and you get a plausible hallucination. Delphi Pythia is a deliberation platform: real respondents supply every claim, AI maps the debate, and randomized experiments prove which arguments actually work. Try the AI Governance demo case on the website: https://delphipythia.xyz/ai_governance/
I built Delphi Pythia out of frustration with a simple gap: polls tell you what people think, focus groups tell you what they say - but nothing tells you which arguments actually change minds. And the new wave of "synthetic respondent" AI tools makes it worse: ask an LLM what the public thinks and you get a confident hallucination.
Pythia works the other way around. Real people answer in their own words, and AI only reads and maps, clustering free text into a live picture of every distinct argument in a debate. Then the survey itself becomes an experiment: each respondent is exposed to a randomized subset of arguments, so "this argument is persuasive" is a measured causal effect.
Surprise: the arguments people rate highest are not the strongest movers - the arguments that actually shifted opinions were often different ones.
One thing I'm proud of: the insights are built bottom-up. There are no predefined answer options. The map of the debate is assembled entirely from what respondents actually say, so our own assumptions never shape what we find.
The first pilot ran on "Who should set the rules for AI?" There's a public demo on the site.
The argument mapping idea is genuinely interesting, especially the randomized experiments part since so few polling tools actually measure persuasion. One thing that would make this much more useful for me: let me export the full chain of claims, counterclaims, and which arguments moved which demographics as a structured CSV or JSON. Right now the value is locked inside your platform and most researchers will need to feed the results into their own analysis pipelines or share them with stakeholders who never log in.
About Delphi Pythia on Product Hunt
“Research platform that measures which arguments change minds”
Delphi Pythia was submitted on Product Hunt and earned 0 upvotes and 3 comments, placing #118 on the daily leaderboard. Polls tell you what people think. Focus groups tell you what they say. Neither tells you which arguments actually change minds. Ask an LLM what the public thinks and you get a plausible hallucination. Delphi Pythia is a deliberation platform: real respondents supply every claim, AI maps the debate, and randomized experiments prove which arguments actually work. Try the AI Governance demo case on the website: https://delphipythia.xyz/ai_governance/
Delphi Pythia was featured in Analytics (172.8k followers), Artificial Intelligence (473.8k followers) and Data & Analytics (5.7k followers) on Product Hunt. Together, these topics include over 126.4k products, making this a competitive space to launch in.
Who hunted Delphi Pythia?
Delphi Pythia was hunted by Stepan Goncharov. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Stepan Goncharov
I built Delphi Pythia out of frustration with a simple gap: polls tell you what people think, focus groups tell you what they say - but nothing tells you which arguments actually change minds. And the new wave of "synthetic respondent" AI tools makes it worse: ask an LLM what the public thinks and you get a confident hallucination.
Pythia works the other way around. Real people answer in their own words, and AI only reads and maps, clustering free text into a live picture of every distinct argument in a debate. Then the survey itself becomes an experiment: each respondent is exposed to a randomized subset of arguments, so "this argument is persuasive" is a measured causal effect.
Surprise: the arguments people rate highest are not the strongest movers - the arguments that actually shifted opinions were often different ones.
One thing I'm proud of: the insights are built bottom-up. There are no predefined answer options. The map of the debate is assembled entirely from what respondents actually say, so our own assumptions never shape what we find.
The first pilot ran on "Who should set the rules for AI?" There's a public demo on the site.
Curious: which debate would you start at first?