Perplexity's output teardown

Updated June 15, 2026

One query spawns multiple views on the same result, so users pivot between prose, links, and images without re-searching. Follow-ups, rewrite modes, and selection refinement extend the session instead of forcing a fresh thread. Source audit and citation depth live in the citations teardown under Trust.

Structured answers with tabbed views

Answer tab with headings, bullets, and inline source chips, Links and Images tabs beside it.

What works

Long answers use clear hierarchy , summary, “Current favorites” list, “Best single guess” , without leaving the thread.
Answer / Links / Images tabs let users switch modality without re-querying.
Completed N steps label signals research happened before the prose appears.

What we would push on

Tabs compete with the answer for attention on first load. Default tab must carry the full story for skimmers.

Business strategy

Perplexity treats each query as a small report, not a chat bubble. Tabbed views let users audit links and images without re-running search, which supports the product’s research-first positioning over generic chat.

Tradeoff

Decision	Benefit	Cost
Answer / Links / Images tabs on one result	Multiple views without re-querying	Tabs compete with prose for attention on first load

Takeaway

Treat search output as a small report: structured prose plus parallel Links and Images views.

Pattern: Response Refinement

Research steps before the answer

Expandable “Completed 2 steps” shows Searching the web and Checking predictions.

What works

Steps collapse by default so the answer stays primary; expand reveals concrete actions taken.
Plain-language step names (Searching the web) beat opaque tool names for trust.
Step count in the header sets expectation for latency on complex queries.

What we would push on

Collapsed steps are easy to miss. High-stakes queries may need a stronger “we searched N sources” cue inline.

Business strategy

Visible research steps justify wait time and build trust before users read claims. For a search product, showing retrieval happened is as important as the prose itself.

Tradeoff

Decision	Benefit	Cost
Collapsed research steps with expandable detail	Answer stays primary; auditors can expand	Easy to miss on fast scroll or casual queries

Takeaway

Show what the system did before answering, collapsed, expandable, in human terms.

Pattern: Progress Steps

Follow-up chips after the answer

Suggested follow-up questions below the answer with a 10 sources summary row.

What works

Follow-ups are contextual , squad leaders, France form, betting odds , not generic “tell me more.”
Each chip is one tap into the composer; users iterate without rephrasing the original question.
Sources row (favicons + count) sits beside share/copy/rewrite actions on the same answer block.

What we would push on

Long follow-up lists push the composer down. Cap visible chips or collapse after three.

Business strategy

Contextual follow-up chips drive session depth without blank composer anxiety. Each chip is another query Perplexity can monetize on Pro tiers with heavier modes.

Tradeoff

Decision	Benefit	Cost
Contextual follow-up chips below each answer	Iteration without rephrasing; drives session depth	Long chip lists push the composer down

Takeaway

Pair a complete first answer with specific next questions, refinement without blank follow-up boxes.

Pattern: Follow-up Chips

Pattern: Response Refinement

Images tab for visual evidence

Images tab shows a grid of thumbnails with source domain under each tile.

What works

Images tab reuses the same query , brackets, experts, trophy photos , without a separate image search.
Domain label under each thumbnail ties visuals back to provenance.
Grid layout supports scan-first research; click-through opens the source image.

What we would push on

Image quality varies by query. No inline caption explains why each image was selected.

Business strategy

A dedicated Images tab keeps visual research inside Perplexity instead of sending users to Google Images. Domain labels reinforce the citation-first brand on non-text evidence.

Tradeoff

Decision	Benefit	Cost
Images tab as peer view beside Answer and Links	Visual evidence without a separate image search	No caption explaining why each image was selected

Takeaway

When answers are visual (sports, products, places), give a dedicated Images view beside prose.

Export PDF, Markdown, or DOCX

Download menu on the answer block: PDF, Markdown, and DOCX.

What works

Export sits in the per-answer action row , share, download, copy, rewrite , not buried in settings.
Three formats cover slide decks (PDF), docs (DOCX), and dev workflows (Markdown).
Download targets the current answer, not the whole thread.

What we would push on

Export may strip citation links depending on format, verify sources survive in PDF/DOCX.

Business strategy

Per-answer export lets users ship research into their real workflows (slides, docs, repos) without copy-paste. That makes Perplexity sticky beyond the browser tab.

Tradeoff

Decision	Benefit	Cost
Per-answer export to PDF, Markdown, and DOCX	Answers leave chat in workflow-native formats	Citation links may not survive all export formats

Takeaway

Let users ship the answer out of chat in the format their workflow expects.

Rewrite with mode and model picks

Rewrite menu: Search, Deep research, Learn step by step, plus model list.

What works

Rewrite regenerates the same question with a different depth or model, not a new thread.
Modes are labeled by outcome (Deep research, Learn step by step) with lock icons for Pro tiers.
Current mode (Search) shows a checkmark so users know what produced this answer.

What we would push on

Model names (Sonar, GPT-5.4) mean little to casual users. Pair with one-line capability hints.

Business strategy

Rewrite with explicit mode and model choice is how Perplexity upsells Pro tiers and justifies compute on heavier runs. Users re-ask the same question with different depth instead of starting over.

Tradeoff

Decision	Benefit	Cost
Rewrite with labeled modes and model picker	Non-destructive retry with clear depth knobs	Model names opaque to casual users

Takeaway

Non-destructive rewrite with explicit mode/model choice beats “try again” with no knobs.

Pattern: Response Refinement

Pattern: Model Selection UI

Thumbs up with quality chips

Optional chips: Up to date, Accurate, Helpful, Followed instructions, Good sources.

What works

Thumbs up opens structured praise, Good sources is explicit for a search product.
All chips optional; users can submit without categorizing.
Thank-you toast confirms receipt without blocking the thread.

What we would push on

Modal interrupts flow for simple satisfaction. One-tap up with optional expand might feel faster.

Business strategy

Good sources in the positive taxonomy trains retrieval quality directly. For a citation product, praise should distinguish accurate prose from accurate sourcing.

Tradeoff

Decision	Benefit	Cost
Structured quality chips on thumbs up	Source-quality signal in praise taxonomy	Modal interrupts flow for simple satisfaction

Takeaway

On search answers, include source-quality in positive feedback taxonomy.

Pattern: Feedback

Thumbs down flags wrong sources

Negative feedback chips include Wrong sources beside Inaccurate and Out of date.

What works

Wrong sources is first-class, critical for a product whose value is citation quality.
Length chips (Too long / Too short) separate formatting issues from factual ones.
Optional modal keeps downvote fast while still capturing structured signal.

What we would push on

No way to flag a specific citation inline from the feedback modal. Users must remember which source failed.

Business strategy

Wrong sources as a first-class chip routes retrieval failures separately from writing quality. That is core signal for a product whose moat is cited answers.

Tradeoff

Decision	Benefit	Cost
Wrong sources chip in negative feedback	Citation failures routable separately from Inaccurate	No per-citation flag from the modal

Takeaway

Negative feedback on search products needs a source-specific issue type.

Pattern: Feedback

Selection → follow-up or check sources

Highlight a passage; Add to follow-up or Check sources targets that span.

What works

Users can select prose inside the answer, not just react to the whole block.
Add to follow-up scopes the next query; Check sources jumps to evidence for that claim.
Split actions match intent: iterate vs verify.

What we would push on

Selection menu is discoverable only after highlighting. No persistent hint for new users.

Business strategy

Selection splits iterate (follow-up) from verify (check sources) on the same span. That keeps skeptical users auditing claims without re-running the whole query.

Tradeoff

Decision	Benefit	Cost
Selection menu with Add to follow-up vs Check sources	Iterate and verify on the same span	Discoverable only after highlighting

Takeaway

Pair refinement (follow-up) with verification (check sources) on the same selection.

Pattern: Response Refinement

How output fits with citations

The pattern

Report-first output: tabbed Answer / Links / Images, visible research steps, structured prose with inline chips.
Refinement via follow-up chips, Rewrite with mode/model picks, export, and selection actions.
Feedback taxonomy includes source quality (Good sources, Wrong sources).

Where it varies

Modality: Answer prose vs Links audit vs Images grid on the same query.
Refinement path: follow-up chip vs Rewrite mode vs selection → check sources.
Citation depth lives in the citations teardown; output covers the answer shell those chips sit in.

Business strategy

Perplexity optimizes for search iteration: new focus, rewrite mode, or a follow-up chip rather than editing one bubble in place. The output layer is a report users can audit, export, and refine; the citations layer is the evidence stack underneath.

Tradeoffs

Decision	Benefit	Cost
Answer / Links / Images tabs on one result	Multiple views without re-querying	Tabs compete with prose for attention on first load
Collapsed research steps with expandable detail	Answer stays primary; auditors can expand	Easy to miss on fast scroll or casual queries
Contextual follow-up chips below each answer	Iteration without rephrasing; drives session depth	Long chip lists push the composer down
Images tab as peer view beside Answer and Links	Visual evidence without a separate image search	No caption explaining why each image was selected
Per-answer export to PDF, Markdown, and DOCX	Answers leave chat in workflow-native formats	Citation links may not survive all export formats
Rewrite with labeled modes and model picker	Non-destructive retry with clear depth knobs	Model names opaque to casual users
Structured quality chips on thumbs up	Source-quality signal in praise taxonomy	Modal interrupts flow for simple satisfaction
Wrong sources chip in negative feedback	Citation failures routable separately from Inaccurate	No per-citation flag from the modal
Selection menu with Add to follow-up vs Check sources	Iterate and verify on the same span	Discoverable only after highlighting

Takeaway

Perplexity’s output model is report-first with layered refinement and source-aware feedback. Steal tabbed views and rewrite knobs; pair with the citations teardown for the full evidence stack.

Pattern: Response Refinement

Pattern: Follow-up Chips

Pattern: Feedback