The Agent Playbooks from Salesforce, Snowflake, Databricks, Harvey, and Lovable: Inside SaaStr AI 2026

The main stage at SaaStr AI 2026 in San Mateo ran end to end on agents.

Agents in production, carrying quota, writing to systems of record, and reshaping how companies are built. Below is a session-by-session recap of maintage on our biggest day, with every speaker and their title, followed by the themes that showed up again and again no matter who was talking.

The CPO Panel: The Hardest Job in B2B Right Now

Jason Lemkin opened by arguing that chief product officer went from the cushiest job in B2B to the most stressful one in about 18 months. For a decade the job was bringing your mug to the office and deciding what to push to next quarter. Now every CPO is under the gun to ship agentic features that customers will actually pay for.

The panel:

Emrecan Dogan, Head of Product, GleanAnneka Gupta, Chief Product Officer, RubrikRachel Wolan, Chief Product Officer, WebflowAnique Drumright, Chief Product Officer, Harvey

Rubrik’s Anneka Gupta walked through Ruby, Rubrik’s agent for operating the platform. It started as a simple RAG application on top of documentation and is now agentic, taking on tasks like forward-looking capacity planning that used to take a customer a full day. The constraint in cyber recovery is that nothing can take the core service down, so Rubrik uses LLMs to generate the plans but keeps the recovery plans themselves deterministic and explainable.

Webflow’s Rachel Wolan described Webflow as an agentic web marketing platform that started as a website builder. The new launch is an answer engine optimization agent that detects when you need to upgrade technical AEO, looks at what competitors are doing, drafts content, and runs autonomously with a human approving changes. Webflow has roughly 18% of the top 2,000 websites and saw customers get a 75% bump in organic traffic from technical AEO automation. Her framing: answer engines now drive about 50% of visitors, up from 10% a year ago, so a brand that does not show up in answer engines is invisible to buyers.

Glean’s Emrecan Dogan made the case that retrieving information was the original job, but the world is moving from getting informed to getting AI to perform. Glean now operates two ways: as the AI assistant front door, and as a single MCP server that feeds superior company context into tools like Claude Code, Cursor, and Codex. The interesting wrinkle he flagged is the spillover effect: the more usage happens in external harnesses, the more it pulls users back in