CHAPTERS
Why AI agents are a real “2025 game-changer” (and what you’ll see in the episode)
Aakash frames the episode as a look at the near-future of work: AI agents that meaningfully replace chunks of human labor rather than just assisting. Jacob (Relay founder) sets expectations: you’ll see real agents he uses and a live build anyone can copy.
Meet Jacob Bank: building a “one-man marketing army” with Relay
Jacob introduces himself as a startup founder without a human executive assistant, and explains why he built one from multiple agents. The conversation quickly anchors on ROI: replacing expensive EA services with inexpensive agent workflows.
Live demo: a 12-agent executive assistant (calendar, email, task management)
Jacob shows his executive assistant “team” split into calendar, email, and task management agents. He emphasizes that the value comes from composing small, reliable workflows over time as needs emerge.
Meeting Briefing Generator: pre-meeting research + Slack delivery
Jacob walks through a meeting-prep agent that triggers before calendar events and assembles a briefing. It researches attendees, prior emails/meetings, pulls LinkedIn context, and posts a combined dossier to Slack 30 minutes before the meeting.
Model selection inside agents: cost/quality trade-offs and “model per task” heuristics
The discussion dives into using different LLMs for different steps. Jacob explains why he mixes models based on cost, context window needs, and writing/analysis strengths—and recommends quick comparative testing as models evolve.
How the LinkedIn lookup works: sub-workflows and tool chaining
Jacob explains the mechanics behind turning an email address into a LinkedIn profile and then into structured profile data. The key idea is composing “building blocks” (Google queries, selecting best result, then fetching data) into reusable sub-workflows.
Follow-Up Drafter agent: from meeting transcript to Gmail draft (with human-in-the-loop)
Jacob demos an agent triggered by Fireflies transcripts that drafts follow-up emails. He adds a critical gating step—deciding whether a follow-up is appropriate—and keeps the final email in drafts for review to avoid high-stakes errors.
Extending the follow-up workflow: pulling recent emails as extra context + Relay’s AI credit options
Aakash and Jacob iterate the workflow idea live: add a step to find recent emails exchanged with attendees after the meeting and incorporate them into the follow-up. They also cover how Relay handles model access via built-in credits or user-provided API keys.
Competitor pricing tracker: automated competitive intelligence and change alerts
Jacob shows a monthly agent that scrapes competitor pricing pages, summarizes them into a sheet, and detects material changes versus last month. The value is net-new capability: competitive monitoring that PMs rarely have time to do manually.
Live build: Reddit brand tracker (sentiment report + links) in ~10 minutes
They build a Reddit monitoring agent from scratch: scheduled weekly trigger, Reddit search, AI summarization, and email delivery. Jacob highlights how prompting differs in workflows (one-shot, precise inputs/outputs) and demonstrates quick prompt hardening via iteration and examples.
Managing notification overload: cadences, digests, and meta-agents that summarize other agents
Aakash raises the operational downside: more pings and more review work. Jacob explains how he prevents chaos by assigning consistent delivery days/times and using additional agents to aggregate and digest incoming information (like newsletters).
Limitations of AI agents today: workflows vs autonomous agents + a practical human-in-the-loop framework
Jacob explains why fully autonomous agents still struggle on complex tasks: most users succeed more with predefined workflows than open-ended agents. He shares a two-axis framework (AI capability vs task stakes) to decide when to automate fully versus require review.
Relay’s business and the bigger market shift: small teams, GTM adoption, tool choice, and founder lessons
The conversation broadens to market dynamics: Relay’s traction and positioning (less-technical users), why small teams can scale, and why GTM functions are adopting agents faster than PMs. They close with guidance on platform selection, product strategy for AI (chatbot/copilot/agent), MCP’s promise, and Jacob’s candid take on leaving Google and PM-to-founder realities.
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