Straight Answers
An LLM assessed 1,140 question → answer exchanges, the host's own answers included. Speaker names were hidden during assessment. Each exchange was marked answered, partly, redirected or not addressed, with a quote as its source. Every exchange below is timestamped and plays. How it works →
These readings are observational: the transcript shows whether the question was answered directly, whatever the reason. It is an AI reading of a public exchange, never a claim about intent, and the tape is one tap away on every row. full disclaimer →
Every one of the 221 people on the record is accounted for: 6 carry a full rate (8 or more assessed questions on raw tape), 207 more have their questions counted (29 of them with at least one not answered directly; too few raw questions for a fair percentage, edited feed included), and the remaining 8 never took a direct question in any tape we hold: compilations, panels and cameo appearances leave nothing to assess.
No needle for Panos Panay: fewer than 8 assessed questions on raw tape, and a percentage on a sample that small would mislead. Their counts are real: 2 not answered directly in 6 assessed questions.
Panos Panay: every exchange, playable
The question Alex asked, then the AI assessment note from the answer. Tap to play the moment. Not addressed = the question was not engaged; redirected = acknowledged, then steered elsewhere.
“Uh, even we have, uh, AirPods with Siri in them today, but we have, there's echo earbuds. Um, so what does the future of the device look like to you when we get past these early days of the AI assistant and into where you really want to see the vision play out?”
answered: “first you focus on the devices that are available to you now, for me”
“And I think it's very interesting to see all these companies going through this moment of when is it time to flip that switch to generative AI? Because like you mentioned, you mentioned when we spoke last, a startup can do it quicker because they don't have to worry about their current customers.”
answered: “starting from hundreds of millions and, and handing it over. I think that's just reality.”
All speakers
All 6 people with 8 or more assessed questions on raw tape. Click a name to see their exchanges. highest rate none identified small samples
| Person | Not answered directly (%) | Redirected + not addressed | Questions | Argument clarity /5 |
|---|---|---|---|---|
| Alex Kantrowitz Founder & Host, Big Technology | 23% | 18 | 78 | 4.0 |
| M.G. Siegler Author & Publisher, Spyglass | 7% | 1 | 15 | 4.0 |
| Ranjan Roy Co-author, Margins | 6% | 1 | 17 | 4.1 |
| Reed Albergotti Technology Editor, Semafor | 0% | 0 | 10 | 4.0 |
| Dallas Dolen US TMT Industry Leader, PwC | 0% | 0 | 9 | 3.9 |
| Matthew Prince Co-Founder & CEO, Cloudflare | 0% | 0 | 9 | 4.3 |
Percentages come from raw unedited recordings only: produced podcast audio has tangents and stumbles cut in the edit, which moves the speaker up by about 12 percentile points. The small-sample counts include the produced feed. This is a reading of a transcript. It is not an accusation of dishonesty, and there are many good reasons not to answer a question directly (confidential numbers, unreleased products, someone else's news to break).