Perplexity’s New Computer Ends Chatbot Era, Lets FinTech Clone Bloomberg Terminal

Perplexity’s “Computer” arrives at a moment when the industry’s obsession with single‑prompt chat interfaces has begun to show its limits. In a LinkedIn post, Siddhesh Surve argued that “the UX became a bottleneck” after three years of shoving ever‑larger models into chat windows, noting that users were forced to juggle separate tools—Gemini for research, Claude for coding, Grok for speed—each in its own tab. Perplexity’s answer is a general‑purpose digital worker that “operates the software stack exactly like a human co‑worker would,” breaking a high‑level goal into tasks, spawning specialized sub‑agents, and running them asynchronously for hours or even months (Surve, Feb 27). The platform’s Multi‑Model Router replaces monolithic LLM pipelines with a micro‑service architecture, routing each sub‑task to the model best suited to the workload, a design Surve says “kills the bottleneck” of single‑model orchestration.

The most headline‑grabbing proof‑of‑concept comes from a finance‑tech enthusiast who, using Perplexity Computer, claimed to have rebuilt Bloomberg’s $30 k‑a‑year terminal in a single afternoon. Bruno Ferreira reported that the engineer—identified only as “Hampton” on X—leveraged the platform’s ability to coordinate 19 different models, automatically handling API keys, data ingestion, and UI generation, ultimately delivering a functional clone of Bloomberg’s data‑rich dashboard (Tom’s Hardware, Feb 27). Ferreira notes the claim has drawn both praise and “sizable skepticism,” but the demonstration underscores how Perplexity’s orchestration layer can compress weeks of integration work into a few hours, a speed that traditional development pipelines struggle to match.

VentureBeat’s coverage adds technical depth, confirming that Perplexity Computer bundles 19 models under a single subscription priced at $200 per month (Michael Nuñez, VentureBeat). The service acts as an “AI project manager,” automatically resolving errors such as missing API credentials and even researching undocumented libraries without human intervention. According to the report, this self‑healing capability is a direct result of the platform’s distributed‑systems approach: each sub‑agent runs in isolation, reports status back to the central orchestrator, and can be retried or replaced on the fly, dramatically reducing downtime compared with monolithic chatbot deployments.

The broader market reaction hints at a shift in how enterprises will consume AI. The Verge’s interview with Perplexity CEO Aravind Srinivas highlighted the browser as “AI’s killer app,” but the real differentiator, according to the CEO, is the ability to embed AI agents directly into existing workflows rather than forcing users into a chat window (The Verge). Analysts cited by ZDNet’s coverage of an MIT study on AI agents note that uncontrolled autonomous agents can become “fast, loose, and out of control,” a risk Perplexity attempts to mitigate through its task‑oriented orchestration and built‑in error handling (ZDNet). If the platform lives up to its promise, it could redefine the economics of AI‑driven software development, especially for data‑intensive sectors like finance that have long relied on proprietary terminals.

Whether Perplexity Computer will dethrone the Bloomberg Terminal remains to be seen, but the technology marks a decisive move away from the chat‑centric paradigm that has dominated the past three years. By treating AI as a coordinated workforce rather than a single conversational interface, Perplexity offers a blueprint for enterprises seeking to automate complex, multi‑step processes at scale. If the early adopters’ claims hold, the platform could usher in a new era where AI orchestration, not chat, becomes the default interface for high‑value business applications.