Lifehacker published a how-to on June 1, 2026, listing 10 hacks that expand what Perplexity can do beyond simple Q&A, including setting Perplexity as a browser default, using multiple models, and leveraging background processing and mini-apps, according to Lifehacker. The article notes that paid tiers unlock features such as Model Council and Perplexity's background Perplexity Computer, which enable multi-model cross-checking and longer-running automations, per Lifehacker. Editorial analysis: These capabilities make Perplexity more useful for rapid research, simple automation, and prototype app-building for practitioners who already use LLM-based search.
What happened
According to Lifehacker, on June 1, 2026 the outlet published a guide titled "10 Hacks Every Perplexity User Should Know" that shows how to extend Perplexity from an answer engine into a task tool. Lifehacker documents steps such as making Perplexity the default browser search engine (with Chrome instructions), using multiple models in one query, and enabling paid features that the article identifies as Model Council and background processing via Perplexity Computer.
Technical details
According to Lifehacker, Perplexity lets users select different models such as Gemini, GPT, and Claude in one interface, and the article describes Model Council (available in paid tiers) as a way to have multiple models cross-check or corroborate answers. Lifehacker also reports that Perplexity supports background tasks through Perplexity Computer, which the article frames as useful for automations and longer-running mini-apps; Lifehacker provides step-by-step examples for these workflows.
Industry context
Editorial analysis: Tools that bundle multiple model backends and provide background processing are following a broader industry pattern of composable AI experiences, where cross-model comparison and off-thread execution reduce single-model failure modes and enable lightweight application logic without a separate infrastructure build. For practitioners, the immediate implication is lower friction for prototyping information-gathering pipelines and simple automations using a search-centric interface.
What to watch
- •Pricing and tier changes that affect access to Model Council and background processing.
- •Additional model integrations or developer APIs that would enable programmatic access to multi-model outputs.
- •Privacy and citation-handling practices when Perplexity runs background tasks on user data.
Takeaway for practitioners
Editorial analysis: Perplexity's combination of multi-model selection and background execution, as documented by Lifehacker, reduces friction for rapid experiments and small automations, making it a useful tool for researchers and engineers who need quick, source-cited answers plus lightweight workflow automation.
Scoring Rationale #
Practical, actionable tips for practitioners using Perplexity are useful but not transformative. The piece documents product features (multi-model, background processing) that lower prototyping friction; freshness is recent, so moderate relevance.
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