Every enterprise buying AI faces the same question: how do we adopt it without losing control of the outcome? I answer it with my own team first. Much of product and go-to-market work is still manual: reading interviews against the CRM, checking competitors every week, preparing for analysts. These sample agents show that work streamlined, with one rule: the agent does the groundwork, and a person owns the outcome. Try them below.
Pick a question about the pipeline, watch the agent dig through CRM data and buyer interviews step by step, then decide which findings go to product and leadership.
From my work: turning buyer evidence into the offer, its packaging and pricing
Set up a briefing with an analyst, watch the agent build the pack and check your claims, then rehearse her hardest questions and get scored.
From my work: the analyst relations behind a Forrester Leader position
Run this week's check on ChatGPT, Claude and Gemini, decide what sales and product should know, and watch the battlecards and the sales digest update.
From my work: one go-to-market engine across sales, marketing, product and pre-sales
Answer a few questions and get a readiness score, your gaps and the deadlines that apply. An agent watches official EU sources and drafts updates for a person to approve.
From my work: a readiness assessment that became a revenue line
I'd like to use cookies from Google Analytics and LinkedIn to see how people use this site and which companies visit. They're off unless you agree, and you can change your mind any time from the link at the bottom of the page.
Netlify, which hosts the site, also counts visits from its server logs. That uses no cookies and doesn't track you across sites.