Michael Bogart, Founder and CEO of Revenue-Growth.AI, explains that the traditional playbook for generating pipeline (relying on predictable conversion rates from email, cold calls, and conferences) is “dead.” In response, the company focuses on maximizing the value of existing prospective and current customers by deploying specialized AI agents to predict and reduce churn, improve close rates, and reduce time-to-close.

The core value proposition is demonstrated through a simple deal inspection agent built on an automation platform (make.com), utilizing the Gemini large language model. This agent is trained to synthesize a plethora of information (call transcripts, emails, notes, next steps) for any deal. The agent can then automatically take action, such as updating a field in Salesforce (e.g., confirming competitive intelligence is present, citing the call ID as the source) and sending a critical, automated notification via Slack to the relevant team (CRO, rep, etc.) if key deal criteria are met. Crucially, Revenue-Growth.AI avoids the typical blockers to AI adoption, security review, and the build-versus-buy debate by building, deploying, and maintaining these custom agents natively within the customer’s existing tech stack and environment. This approach ensures a fast time-to-market, allowing customers to start with one agent and see results within the same quarter.

Takeaways:

• Audit Your Deal Data: Use the agent framework to immediately start inspecting deal quality. Train the first agent to output one of three conclusions on a critical deal stage component (e.g., Pain Identified: Met, Partially Met, Unmet) and require a source citation.

• Automate Business Cases: Leverage the agent’s ability to take action by setting up criteria to automatically generate a Version 1 business case or slide deck for any deal that hits a specific stage and close date. This saves high-value sales time.

• Bypass Security/IT Roadblocks: Given that the agents are built in your existing environment (bypassing the need for new software security reviews), identify one critical, high-impact revenue problem and allocate budget to pilot a single agent immediately.

• Prioritize Pipeline Efficiency over New Lead Volume: Focus AI investment on maximizing the conversion and retention rates of the existing pipeline and customer base, acknowledging that traditional pipeline generation math is no longer reliable.

• Special Offer: For members of the 100 Founders Network, the initial build and deployment of the first AI agent is offered for a one-time fee of $10,000 (a reduction from the typical $15,000 setup fee). Contact Michael Bogart at MD Bogart (LinkedIn) or revenue-growth.ai to initiate the conversation.

Links:

• LinkedIn: https://www.linkedin.com/in/mdbogart/

• Website: https://www.revenue-growth.ai/

Omer Gotlieb of Salespeak AI joins Dave Rubinstein to discuss the “broken” B2B buying experience, arguing that buyer expectations have dramatically changed due to high-quality AI interactions (like ChatGPT and Waymo), while many B2B companies still use “legacy playbooks”. The current landscape is noisy, with an “improper use or wrong use of AI” leading to an overwhelming “spam cannon” of intelligent-sounding but poorly targeted emails and messages. Salespeak AI aims to fix this by enabling intelligent conversations across all digital touchpoints, including websites, email, and forms, to deliver the expert-level experience buyers now expect, which often feels like speaking directly to a founder or a chief product officer.

Salespeak’s platform first trains its AI on a company’s website, internal documents, battle cards, and call recordings, allowing marketers to control the knowledge base. Marketers then define goals and qualification criteria in plain English, allowing the AI to guide prospects toward scheduling a demo or watching a product video. Crucially, the platform provides deep intelligence for the company, generating gold nugget insights on what customers are asking, what content is missing, and which campaigns are bringing in the right questions. The entire platform is designed for marketers, requiring minimal engineering support, just a small code snippet for implementation, and a five-minute CRM integration.

Takeaways:

• Prioritize Intelligent Conversations: A positive B2B buying experience relies on having intelligent, expert-level conversations that quickly save the buyer time and help them make a decision.

• Treat the Buyer as a 2025 Customer: Traditional, static websites and legacy playbooks are no longer enough because AI (like ChatGPT) has educated buyers to expect instant, trustworthy, high-quality experiences.

• Unify Digital Touchpoints: Ensure the intelligent conversational experience is consistent across every channel—website, forms, email, etc.—to create a much better overall situation for the buyer.

• Leverage AI for Company Insights: Use conversational AI to generate “gold nuggets” of intelligence for your company, such as identifying content gaps, analyzing competitor questions, understanding messaging gaps, and seeing what questions specific marketing campaigns generate.

• Use Missing Information as a Training Tool: Pay attention to the AI’s dashboard feature that highlights questions the AI was asked but didn’t have enough training on. This is a crucial opportunity for marketers to train the AI on new or strategic information (like competitive details or pricing) that they may not want publicly on the website.

Links:

• LinkedIn: https://www.linkedin.com/in/omergotlieb/

• Website: https://salespeak.ai/

Noah Jacobs, co-founder of BirdDog, demonstrates how his platform helps sales teams cut through the noise of automated “spam your TAM” strategies to identify exactly which accounts to target. Jacobs explains that while salespeople can technically sell to many companies, the real challenge is identifying those with specific active pain points—such as training foundation models, hiring specific engineering roles, or opening new facilities—that align with a vendor’s value proposition.

BirdDog automates this manual research process by providing real-time “signals” directly into workflows like Slack and Teams, creating a transparent “signal floor” where leadership and AEs can collaborate on breaking news. The demo showcases how the platform not only alerts teams to these triggers but also acts as an analytical tool, comparing signals against past “Closed Won” and “Closed Lost” data to mathematically determine which behaviors are most predictive of actual revenue.

Takeaways:

• Move Beyond Basic Firmographics: Instead of just filtering by company size or industry, sales teams should look for specific behavioral triggers—like product launches or new facility openings—that indicate a genuine need for their specific solution.

• Create a “Signal Floor” for Transparency: Rather than siloing information, pipe real-time account alerts into a public Slack or Teams channel. This allows sales leaders to immediately tag AEs or offer executive introductions based on fresh news.

• Validate Your Signals Against Revenue: Don’t just guess which triggers matter. Analyze your past deals to see which signals appeared frequently in your “Closed Won” column compared to the “Closed Lost” column (e.g., BirdDog found specific signals made deals 2x more likely to close).

• Contextualize the “Why Now”: When reaching out, use specific data points found during research (like a job posting or SEC filing) to customize the “Why now/Why reach out” narrative, rather than using generic templates.

• Ideal Use Case for Deep Research: This level of signal-based selling is most effective for complex sales cycles (3+ months) with contract values over $30,000, where “spray and pray” tactics are ineffective.

Links:

• LinkedIn: https://www.linkedin.com/in/noah-jacobs/

• Website: https://www.getbirddog.ai/

Yoel Krupnik, co-founder of Quizit AI, demos a platform designed to address student engagement and the static nature of traditional assessments. The tool uses AI to “instantly transform learning with gamified assessments” by turning materials like prompts, videos, documents, and websites into interactive multiple-choice quizzes. While the primary focus is currently on the education system for teachers, Yoel also notes its high relevance for corporate use cases like employee onboarding, customer training, and fun team events.

The demo shows Yoel creating a specific quiz for ninth-grade students about percentages in under a minute. He highlights both the student and teacher views. Students get immediate feedback, including detailed explanations for how to arrive at the correct answer. Teachers get a comprehensive dashboard with class-wide statistics, including performance distribution and a per-question analysis to see which answers misled students. Yoel shares feedback that students are more engaged during the entire lesson because they anticipate a fun, five-minute quiz at the end.

Takeaways:

• Generate Quizzes from Diverse Content Sources: Quizit’s AI can create interactive quizzes not just from simple text prompts, but also from files, links, documents, and videos. A user can instruct the AI to combine sources, such as asking it to “take this topic from... this YouTube video and that topic from that PDF”.

• Create Highly Specific Assessments in Seconds: A teacher can create a quiz in 30 to 40 seconds. The prompt can be very specific, defining not only the topic (e.g., percentages) but also the target grade level (e.g., ninth grade) and context (e.g., real-world scenarios).

• Provide Immediate, Explanatory Feedback to Students: After a student answers a question, the platform immediately shows if they were correct or incorrect. Crucially, it also provides an explanation of how to get to the right answer. For math problems, this explanation shows the specific equation or method used to find the solution.

• Use Teacher Dashboards to Analyze Class Performance: Teachers get immediate statistics on class performance. The dashboard shows statistics for each question, a “per question analysis” detailing which options students selected, and data on individual student performance. This helps teachers identify common distractors or topics that need review.

• Boost Student Engagement Throughout the Lesson: According to feedback received by Quizit, knowing there will be a fun, five-minute quiz at the end of a lesson can change the entire dynamic. It makes students “much more concentrated and engaged from the very beginning” rather than just during the quiz itself.

Links:

• LinkedIn: https://www.linkedin.com/in/yoelkrupnik/?originalSubdomain=il

• Website: https://quizit.ai/

• Email: Yoel@quizit.ai

Zach Wright, Co-Founder and CRO of Syft AI, demos his AI sales application designed to help B2B outbound sales teams find a pipeline they aren’t aware of. Syft.ai’s mission is to move sellers away from the “volume game” by solving the problem of random prospecting. Zach showcases a three-part workflow: first, “value matching,” which identifies companies actively showing signs of a problem you can solve; second, generating “perspective-driven messaging” with recommended contacts based on that value match; and third, pushing that messaging and contact data directly into a sales engagement platform like Outreach. The goal is to provide reps with the “answer before they ask” and make outbound prospecting relevant again.

Takeaways:

• Re-evaluate the “volume game”. If your “spray and pray” approach yields less than 1% results, doubling the volume won’t fix the core issue, as “two times zero is still zero”.

• Focus on “value matching”. Instead of random prospecting, identify companies that are actively showing signals of a problem or an initiative your product can solve.

• Craft “perspective-driven messaging”. Your outreach should reference the research you’ve done, identify the challenge this implies, explain how you can help, and ideally include a relevant win story.

• Go multi-threaded from the start. Use tools that recommend multiple contacts for a single account and add them all to your outreach sequence at the same time.

• Combine email outreach with a LinkedIn strategy. After pushing contacts into an email sequence, send LinkedIn connection requests to the same people.

• Follow up on new LinkedIn connections effectively. For the contacts who accept (Zach sees ~40% acceptance ), send a screenshot of your research (the “value match”) and reiterate your perspective on how you can help.

• Accelerate new rep onboarding. Providing new hires with AI-generated value matches and messaging allows them to “learn by doing” and get into the game quickly

Links:

• LinkedIn: https://www.linkedin.com/in/zachwrightsyft/

• Website: https://www.syftai.com/

Follow Dave on LinkedIn: https://www.linkedin.com/in/daverubinstein/

100 Founders supports each step of the GTM journey from surviving to thriving, to transitioning from Founder-Led Sales. Operational experience, coupled with insights from 100s of B2B SaaS Founders with less than 10M ARR, makes 100 Founders the right partner for this stage startup.

Where to watch:

→ 100 Founders Website: https://www.100founders.ai/

→ YouTube: www.youtube.com/@100-Founders