Google is redefining the essence of AI value, shifting the focus from instantaneous chat responses to deep asynchronous analytics. The launch of Deep Research and Deep Research Max agents based on the Gemini 3.1 Pro model is a clear signal to the market: the era of chasing minimal latency is coming to an end. As noted in the report, the standard version of Deep Research still targets real-time interaction, prioritizing speed. However, Deep Research Max uses extended test-time compute to reason, search, and iterate on hypotheses in the background. Google positions this as a tool for "overnight" tasks: for example, you start an automated due diligence in the evening and receive a ready report by morning. In our view, this changes the rules of the game: now businesses will have to pay not for the volume of tokens, but for the time spent "thinking" and the thoroughness of the work.
Technical integration of the Model Context Protocol (MCP) allows these agents to finally link the open web with closed corporate repositories. Google explained that developers via the Gemini API can now build R&D chains that pull data from internal isolated bases to create verified reports. This is a direct attempt to solve the problem of hallucinations in business intelligence by grounding the model on specific data streams. However, the competitive environment remains ambiguous. While Google's benchmarks demonstrate Max's success in search and logic, comparison with competitors reveals a methodological gap. According to available data, OpenAI GPT-5.4 Pro shows 89.3% in the BrowseComp test, and Anthropic stated that their Opus 4.6 performs better with "reasoning intensity" turned off. This directly contradicts Google's approach, which bets precisely on maximum logic settings.
For R&D heads, this means the end of perceiving AI as a fast search engine. With MCP combining private data with web intelligence, you can automate the first 80% of market analysis or competitor mapping. However, given that test results critically depend on whether "reasoning" mode is enabled during the API call, your technical teams will have to strictly verify the reports of autonomous agents before they reach the top management's desk. We believe that trusting "hallucinating" intelligence without a human filter is still too expensive.