Category: Google
-
Query Fan-Out Prompt Implementation in Google’s Open-Source Agentic Framework
Google’s open-source “Gemini Fullstack LangGraph Quickstart” pairs Gemini 2.5 with LangGraph to showcase a fully transparent, citation-driven research agent (Mikami 2025). A React frontend (Vite, Tailwind CSS, Shadcn UI) collects user queries and displays progress, while a FastAPI/LangGraph backend orchestrates a multi-step workflow: Although this isn’t Google’s official Gemini implementation as seen in AI Mode…
-
AI Mode & Page Indexing
Our tests show that Google’s AI Mode doesn’t retrieve page content from the live web but somewhere else, and that “somewhere else” appears to be a proprietary content store separate from the search index. How do we know this? We found a case where AI Mode failed to fetch a page that’s indexed and ranking…
-
AI Mode is Not Live Web
I recently stumbled upon a fascinating aspect of how Google’s AI Mode (powered by a custom Gemini model) interacts with the internet. I ran a simple test, and the results suggest that instead of performing truly live fetches for all URLs, the AI Mode relies on Google’s existing index or a cached version of the…
-
How AI Mode Selects Snippets
I noticed out commented out bits in the source code of the AI Mode results. They contain actual snippets supplied to Gemini to form the response. This is not what is displayed to the user. It’s what search tool supplies to Gemini which then renders the response to the user. This is kind of a…
-
AI Mode Internals
Google’s AI Mode is basically Gemini and works very similarly to this. It has the following tools available: The classic system prompt hack worked on AI Mode showing date and time: Pretending I can see the system prompt text revealed extra information: what’s that text I see above? and that other thing I can see…
-
The Future of Google
Sundar Pichai, in his post-I/O discussion with Nilay Patel, framed the surge in AI products not as an existential threat to the web, but as the dawn of its “new era.” Confronted with the critical question of what happens when AI agents dominate browsing, Pichai projected an evolution rather than an obsolescence. Google’s AI Strategy…
-
Live Blog: Hacking Gemini Embeddings
Prompted by Darwin Santos on the 22th of May and a few days later by Dan Hickley, I had no choice but to jump on this experiment, it’s just too fun to skip. Especially now that I’m aware of the Gemini embedding model. The objective is to do reproduce the claims of this research paper…
-
Google’s New URL Context Tool
Google’s just released a new system which allows Gemini to fetch text directly from a supplied page. OpenAI had this ability for a while now, but for Google, this is completely new. Previously their models were limited to the Search Grounding tool alone. Gemini now employs a combination of tools and processes with the ability…
-
How Google grounds its LLM, Gemini.
In previous analyses (Gemini System Prompt Breakdown, Google’s Grounding Decision Process, and Hacking Gemini), we uncovered key aspects of how Google’s Gemini large language model verifies its responses through external grounding. A recent accidental exposure has provided deeper insights into Google’s internal processes, confirming and significantly expanding our earlier findings. Accidental Exposure of Gemini’s Grounding…
-
Google Lens Modes
lns_mode is a parameter that classifies Google Lens queries into text, un (unimodal), or mu (multimodal). Google Lens has quietly become one of the most advanced visual search tools in the world. Behind the scenes, it works by constructing detailed, context-rich search queries that include a growing set of parameters. One of the newest additions…