A Gemini Gem (AI agent) that transforms raw search results across tiered Tech, AI, and Innovation media outlets into a structured analysis of external factors that impact any organization.
CHALLENGE
There is so much happening in the AI space that’s it’s hard to keep up with the latest. Also, when news is trending on a hot topic, it’s really hard to capture and make sense of various perspectives in market. Especially marketing and PR teams who are trying to keep their organization relevant in market by having a point of view on a trending news story. Alternatively, it also makes it hard for someone who is just trying to stay informed be able to speak intelligently on the latest news.
Traditionally, to search information about a specific trending news story, is a time-consuming and fairly manual process. It would involve doing a surface level search on the trending news story and then aggregating the findings. Even if you were to use an AI tool today with a generic prompt to find details about a news story, it would still remain surface level.
SOLUTION
To help, I built a specialized Gemini Gem (AI agent) converts raw search results into a structured, executive-ready briefing in minutes rather than hours.
The Gem scans a tiered list of media outlets (Tier 1 to establish the baseline, Tier 2 to understand regional implications, Tier 3 to surface more technical or specialist views, and Tier 4 to seek out any divergent or conflicting thoughts not already surfaced).
After this research is complete, the agent will then organize the information it has found against the PESTLE framework. It weighs and filters based on the executive (and industry) this is meant to brief. The agent will also analyse the cross-sections where two PESTLE factors intersect to highlight any frictions and complexities.
To prevent the agent from hallucinating, I programmed the agent with evidence discipline. Every claim requires direct source attribution, neutral language, and explicit identification of coverage gaps (e.g., “Not prominent in current coverage”).
With this brief, a user can then build out the “so what” narrative of why this is relevant for their own organization, why this is relevant for their client base. Ultimately, it enables an individual to lead conversations with a nuanced, multifaceted perspective that accounts for the typical external factors that affect organizations.
GEM (AGENT) IN GEMINI:
Media Research & Briefing for Tech / AI / Innovation Topics
The Gem should be open to anyone to use.
OUTPUT EXAMPLE
The agent was asked to complete a briefing for a CEO of a logistics/transportation organization who needs to be briefed on American AI executives cautioning the market on Chinese AI models. Here are two parts of the output generated by the agent:
Executive Summary
This strategic briefing provides an intelligence scan of the warnings issued by American artificial intelligence executives regarding Chinese AI models, tailored specifically for the Chief Executive Officer of a Transportation & Logistics organization.
As a Growth & Market Driver operating in logistics, your strategic lens prioritizes Economic (cost structures, enterprise spend, ROI) and Social (workforce trust, sentiment, operational adoption) dimensions, backed by Political (supply chain resilience, trade/export restrictions) factors.
American AI executives (including leaders from OpenAI and Anthropic) have escalated warnings to Washington and enterprise markets regarding low-cost Chinese AI models (such as DeepSeek, Moonshot AI’s Kimi K3, and Alibaba’s Qwen). While US executives frame these low-cost open-weight models as national security risks and intellectual property theft via “distillation,” industry analysts and Tier 4 commentators suggest US tech firms are attempting to wall off competition ahead of planned public listings. For logistics executives, this creates an operational tension between adopting hyper-efficient, low-cost AI for fleet and supply-chain optimization versus exposure to national security regulations, data sovereignty risks, and vendor lock-in.
Synthesis
A) Compounding Trends
- High-performing open-weight models are driving down the cost of enterprise AI capabilities worldwide.
- Western governments are increasingly treating AI software models — not just semiconductors — as regulated export-controlled assets.
B) Contradictions
- US AI firms advocate for open, market-driven innovation while simultaneously calling on federal regulators to restrict cheap, open-weight competitor models.
- Coverage shows rapid enterprise adoption of open-source models happening simultaneously with rising global government bans on the same software.
C) Open Questions
- Will future US executive orders or federal legislation explicitly prohibit commercial enterprises from deploying open-weight models originating from foreign adversaries?
- How will global supply chain networks handle compliance when overseas logistics partners deploy Chinese AI models that are restricted in Western markets?