Adviserry

Adviserry is an AI-powered action engine designed for professionals, founders, and operators who consume a high volume of expert content but struggle to translate that knowledge into tangible outcomes. The product addresses a fundamental problem in knowledge work: reading newsletters, watching YouTube videos, and studying frameworks without producing measurable progress on your goals. Adviserry ingests content from multiple sources including newsletters, YouTube channels, documents, pitch decks, strategy docs, market research, and business plans. It then processes this content against your specified goals and projects to generate weekly action drafts. The system operates on a proactive model rather than a reactive one. It does not wait for you to ask a question. Instead, it continuously scans new content, maps it to your current objectives, and delivers specific moves to take each week. Core technical capabilities include automatic ingestion from Gmail and content channels, a searchable archive with a live knowledge graph, cross-source synthesis that aggregates recommendations from multiple experts, a working memory system that remembers your past work and refines advice over time, and proactive daily digests with alerts for urgent insights. The product also provides a chat interface for querying your archive and supports integration with Claude Desktop and ChatGPT via the Model Context Protocol (MCP). Adviserry is built for anyone who follows experts like Patrick Campbell or Alex Hormozi and wants to ship actual results instead of accumulating reading material.

Action Drafts

Every new piece of content ingested by Adviserry is distilled into a specific, actionable move rather than a generic summary. These action drafts are copy-paste ready and include cited sources. For example, when content about pricing strategies is processed, the output might be a concrete recommendation such as "Test this pricing change" or "Send this email to your current customers." Each draft is tied directly to what you are working on, ensuring that every piece of advice has immediate applicability. The system evaluates content against your defined projects and generates drafts that are specific enough to execute without additional analysis.

Cross-Source Synthesis

When multiple experts in your feed publish content on the same topic within a short timeframe, Adviserry automatically detects the overlap and synthesizes their combined position. This feature eliminates the need for you to manually compare viewpoints from different creators. The system analyzes the content for shared recommendations, conflicting advice, and complementary insights. It then produces a unified recommendation that represents what the collective group of experts suggests. This synthesis is particularly valuable for complex topics like pricing, hiring, or market positioning where multiple perspectives need to be reconciled into a single coherent strategy.

Working Memory

Adviserry maintains a persistent memory of your projects, past attempts, and what has worked or failed previously. This working memory ensures that every recommendation is contextualized against your actual situation rather than providing generic advice. The system tracks what you are building, what you have tried, and the outcomes you achieved. Over time, as you use the product, the recommendations become increasingly sharp and personalized. The working memory integrates with the action draft system to avoid repeating failed strategies and to build upon successful approaches. This creates a feedback loop where the product learns from your actions and continuously refines its output.

Insights While You Sleep

The system operates on an automated scanning schedule that checks new content against your goals every hour. When it identifies content that is highly relevant or time-sensitive, it flags it for immediate attention. The most actionable insights are compiled into a daily digest that arrives in your inbox each morning. Urgent items can trigger direct notifications to ensure you do not miss critical opportunities. This proactive alerting system means you wake up with the next move already identified and prepared. The hourly scanning ensures that no important insight from your experts is missed, even when you are not actively monitoring your feeds.

Pricing Strategy Optimization

A founder working on pricing their product can configure Adviserry to monitor experts like Patrick Campbell and Alex Hormozi for content related to pricing models, value-based pricing, and customer willingness to pay. The system will automatically synthesize any overlapping recommendations and generate a specific action draft, such as "Raise your prices by 15 percent and test with your top 20 customers this week." The working memory tracks which pricing experiments have been attempted and their results, so future recommendations build on past learnings. The founder receives proactive alerts when new pricing research is published that directly applies to their current pricing stage.

Competitive Positioning in Crowded Markets

For a startup trying to stand out in a saturated market, Adviserry ingests content from marketing experts, growth strategists, and industry analysts. The cross-source synthesis feature identifies when multiple experts recommend similar differentiation strategies, such as focusing on a specific niche or emphasizing a unique technical capability. The system generates action drafts that include specific messaging frameworks to test, target audience segments to prioritize, and channels to use for distribution. The daily digest provides ongoing insights about competitor moves and market shifts as reported by the experts being monitored.

Hiring and Co-Founder Matching

When a founder is actively seeking co-founders or key hires, Adviserry tracks content about hiring best practices, equity splits, cultural fit assessment, and interview techniques. The system synthesizes advice from multiple experts into a structured hiring playbook with specific actions for each stage of the recruitment process. The working memory remembers which candidate profiles have been evaluated and what feedback was received, enabling the system to refine its recommendations for the next search round. Proactive alerts notify the founder when new content about hiring in their specific industry or stage is published.

Shipping with AI Agents

A technical founder building AI-powered products can use Adviserry to stay current with the rapidly evolving landscape of AI agents, tooling, and deployment patterns. The system monitors experts who publish about agent architectures, prompt engineering, and integration strategies. It synthesizes conflicting viewpoints and generates action drafts that recommend specific frameworks to test, APIs to evaluate, or deployment configurations to try. The searchable archive allows the founder to quickly retrieve past recommendations and compare them against current project requirements. The MCP integration with Claude Desktop and ChatGPT enables querying the archive directly from development environments.

How does Adviserry determine which content is relevant to my goals?

Adviserry uses a multi-step matching process. First, you define your current projects and objectives during setup, such as pricing your product or hiring a co-founder. The system then analyzes every piece of ingested content using natural language processing to identify topics, themes, and actionable recommendations. It compares these against your defined goals and ranks content by relevance. Content that directly addresses your stated objectives is prioritized for action draft generation. The working memory system also tracks your past actions and outcomes, which influences how the system weights future content recommendations. Over time, the matching algorithm becomes more precise as it learns which types of content lead to successful outcomes for you.

Can I control which experts and sources Adviserry monitors?

Yes, you have full control over your content sources. Adviserry ingests content from newsletters, YouTube channels, and documents you specify. During setup, you can connect your Gmail account to automatically import newsletters you already subscribe to. You can also manually add YouTube channels and upload documents such as pitch decks, strategy docs, and business plans. The system maintains a configurable reading list that you can modify at any time. You can add or remove sources, pause monitoring of specific channels, and set priority levels for different experts. The searchable archive includes all ingested content regardless of source, and you can query across your entire collection using the chat interface.

How does the MCP integration with Claude Desktop and ChatGPT work?

Adviserry implements the Model Context Protocol (MCP) to expose its searchable archive to external AI tools like Claude Desktop and ChatGPT. When you connect the integration, these tools gain the ability to query your Adviserry archive directly. This means you can ask questions such as "What did Patrick Campbell say about retention last month?" or "Summarize all advice from Alex Hormozi on pricing" without leaving your chat interface. The MCP integration provides structured access to your knowledge graph, cross-source syntheses, and action drafts. It respects the same working memory and personalization that Adviserry uses internally, so answers are contextualized against your projects. This integration is particularly useful for developers who work primarily in AI-assisted environments and want to access their curated knowledge base without switching applications.

What happens to my data and content privacy?

Adviserry processes your ingested content and personal data to generate recommendations. The system stores your content archive, working memory, and project definitions on secure infrastructure. Your data is not used to train public models or shared with third parties. The content you ingest from newsletters and YouTube channels is processed solely for your personal use and recommendation generation. You retain full ownership of your data and can delete your archive at any time. The system uses encryption for data in transit and at rest. Access controls ensure that only authorized users can query your archive. If you use the MCP integration, your queries and responses are handled through authenticated API calls that do not expose your data to the external AI tool's training pipeline.