Why the next era of search won’t look like Google

Search Is Collapsing Into the Workspace

For 25 years “search” meant a list of ten blue links, an ad or two, and a guess that one of those URLs held the answer. That interface made sense when bandwidth was precious and language models didn’t exist. In 2025, it already feels anachronistic: I ask a question, a large-language model understands it, fetches real-time evidence, and hands me the answer — all inside the same chat where I’m writing code, outlining a deck, or brainstorming copy.

That behaviour shift is exactly what ChatGPT Search bets on:

Become the default place professionals and builders come to ask, understand, and act on live information — delivering cited answers, deep research, and creation tools in one ad-free workspace.

Everything else — competitive positioning, feature roadmap, even monetisation — flows from that.

Where is ChatGPT Search playing?

When we think about search, what comes to mind is quick search queries to help us get to the correct location. While this is the “traditional model” of search, it is still widely used.

Google has been leading this market, and it is unbeatable when you need that link instantly. That is precisely why, as a user, I go to Google and search “Uniqlo jackets,” expecting to get a handful of relevant results that link me to the exact experience.

But, search is starting to change slightly.

AI assistants are absorbing classic search; Gartner forecasts ≥ 25 % drop in SERP volume by 2026 as users shift to chat-style answers.

With this new style of searching, the dominance of search is being competed on the below factors:

1. Interaction Depth
2. Latency/Speed to answer

OpenAI needs to stay anchored in the bottom-left quadrant — that’s where ChatGPT is uniquely great — while cherry-picking the minimum viable navigational experience (e.g., instant “Top link” card + faster serving). The goal is defensive coverage so users never feel forced to leave, not a wholesale pivot toward Google’s turf.

The search pie isn’t shrinking; it’s collapsing into two behaviours:

• Link-out navigation (Google’s fortress)
• In-place synthesis (ChatGPT’s beachhead)

Winning the second doesn’t require storming the first, but we do need a defensive shield so users never have to bounce out for “uniqlo jackets.”

Three Audiences, One Unifying Job

Pro/Power users (knowledge workers, journalists, academics)

This segment is focused on turning raw web data into a polished brief/draft. They rely on verifying every claim with sources.

For these users, interaction depth matters more than speed. They are not seeking quick link outs but rather a list of citations to refer to.

This segment is already highly willing to pay since they are not satisfied with products like Google, Gemini, or other substandard AI search products.

Developers/Integrators

Their core job?

How can I drop a web-grounded, citation-rich answer into my app in < 250 ms?

This segment is most focused on latency budget and integration. It expands surface area and creates platform lock-in and usage revenue.

Casual Searchers

Currently, they are still spending most of their time outside of ChatGPT for search.

Need a quick fact or canonical link out quickly.

Speed is key. They need an answer instantly or the relevant link without wasting any time waiting for an AI to curate and draft a response.

I want to search “OpenAI careers” and I need a link to the career website in milliseconds.

What does this mean in terms of the strategy for ChatGPT Search?

Strategic Pillars & Initiatives

Friction-free Navigation

Even power users occasionally type “openai careers” or “UPS tracking” and expect an instant link.

Right now they flip to Google because ChatGPT Search spends three seconds composing prose before it reveals the obvious URL. Our first pillar is a “navigation shield.”

Initiatives:

1. Quick Answer/Link: Cached, sub-500ms answer that surfaces high confident information immediately to resemble quick search online. This happens as ChatGPT search tries to generate a longer response. This also involves improving classification on when to hit web search and when to resolve to local data.
2. Top-Link Card: A canonical link the moment you hit Enter. While this may seem counterintuitive by suggesting moving the member out of ChatGPT, however, this allows a user to start to build a habit of starting searches with ChatGPT. Under the hood we’ve built a tiny navigational intent classifier; if it’s >95 % confident, the card appears first, the deeper answer streams in behind it.

When a casual user realises they can stay in the chat for these micro-queries, we’ve quietly stolen the reflex to “just Google it.”

Deep-research companion

Most of the paid users aren’t looking for a single URL. They are trying to transform raw information into output.

Continue to build deeper into this product as the core use case.

Developer Platform

Every SaaS team wants a “chat-with-the-web” feature. OpenAI needs to continue to support a strong open Web-Search API that returns the same cited synthesis users see in ChatGPT.

Initiatives:

1. Two Modes for API: A Fast-Facts Mode with alow token, <250 ms endpoint for widgets and chatbots. Continues to include full long form answers: inline citations and a {“sources”:[]} JSON array for your UI.
2. Tool-Calling Hooks: The API includes function-call metadata so your agent can chain follow-up searches without you writing prompt glue.
3. RAG Helper SDK. A few lines of code rerank your private docs alongside web results, keeping sensitive data inside your VPC.

Multimodal Experience

Continue to develop and build a multimodal web search experience. For example, it’s very hard to understand if a search was web based or not when engaged in a voice chat. ChatGPT Search needs to continue to become a voice-native, vision-aware assistant.

Initiatives:

1. Improved Voice Citations: Citations aren’t lost—you hear, “According to The New York Times …” and can tap the phone screen to open the link.

Improved Source Surfacing/Search Experience

Generative answers are worthless if creators stop publishing. Experiences are not useful if it’s hard to decipher where the information is coming from.

Staying ad-free lets us prioritise user trust and publisher viability over CTR optimisation — an advantage incumbents structurally can’t copy.

Intiatives:

1. Hover Previews: Citations aren’t blue footnotes; hover and see the exact paragraph we used. That drives curiosity clicks to the source instead of hoarding traffic.
2. Opt-in Dashboard: Publishers can see query volume, click-through rates, and even disputed excerpts. Transparency builds goodwill faster than legalese.
3. Logo Badges & Paywall Respect: Opt-in outlets get their favicon next to citations; paywalled domains show a lock icon so users know what to expect.
4. Focussed Modes: Allow users to focus web search on specific modes like social platforms, academic searches, general search, etc.
5. Visual/Graphical Search: “canvas” for search results. Instead of or in addition to a linear text chat, users might have a more exploratory interface: imagine a canvas where the central answer is shown, and around it are cards or nodes representing the sources, which the user can click to expand or visualize connections.
6. Premium Publisher Partnerships: Develop direct relationships with high-quality content providers through API integrations, specialized citation formats, and potential revenue-sharing models that create a sustainable ecosystem.

Contextual Intelligence

ChatGPT Search must move beyond treating each search as an isolated event to understand the user’s ongoing context and work patterns. This creates a truly personalized search experience that anticipates needs rather than just responding to queries.

Initiatives:

1. Persistent Knowledge Graph: Build and maintain user-specific knowledge contexts that remember previous searches, preferred sources, and domain expertise to deliver more relevant results over time.
2. Ambient Intelligence: Develop subtle, non-intrusive suggestions based on what the user is currently working on, offering relevant information before it’s explicitly requested.

Non-Priorities

• Competing for ad-funded navigational clicks
• Building a full crawler to match Google’s global index in the near term
• Low-value novelty features (skins, personalities) that don’t advance trust or depth
• Long-tail hobby plug-ins that fragment UX

OpenAI’s ChatGPT Search is on track to redefine how we access information. By combining the strengths of conversational AI and web search, it offers an experience that is natural, up-to-date, and user-centric — a stark contrast to the classic search engine model. This product strategy lays out a path to make ChatGPT Search not just a useful feature, but a world-changing product.

We will differentiate by offering something richer and more helpful than Google’s results page, more accessible and integrative than Bing’s chat, and more comprehensive than niche players like Perplexity.

Our north star is a user experience where interacting with ChatGPT feels like consulting a brilliant human expert who has read the entire internet and can tailor their explanation to your needs — all while showing you exactly where the information comes from. Achieving this will require careful balancing of AI prowess and product design, but OpenAI is uniquely positioned to do it.

Beyond Blue Links: ChatGPT Search was originally published in UX Planet on Medium, where people are continuing the conversation by highlighting and responding to this story.