Building and deploying AI agents in products. How product teams approach agentic AI, autonomous workflows, and the future of AI-powered products from Lenny's Podcast.
“It's meant for you to say, 'I want you to get something done,' and it goes and does it. And I think we're just getting to a point where for pretty much all the usual applications, AI is going to be good enough that we can get rid of the interfaces more or less where you're digging into all the things that it's actually doing.”
“All these LLMs are sitting idle overnight and on weekends, while humans aren't there. There's no need for that. They should be working all the time. They should be trying to build in anticipation of what we want.”
“The general trend right now is going from models knowing things to models doing things. And the next question becomes, what can it do for me? How does the agent make decisions for you?”
“We had 10 SDRs doing this inbound workflow and now we just have one that is effectively QA-ing the agent. The other nine we deployed on outbound, so we got to move them up the value chain.”
“When I think about agents, I think about three things. One is an increasing level of autonomy and kind of independence that you can delegate higher and higher order tasks. Second thing I think of it is complexity. It's not a one-shot, it's build me this prototype. And then the third thing I would say is asynchronous. It works when you are not working.”
“I think that we're approaching this world in which the marginal cost of a good output is approaching zero. And I think when that happens, we're going to see exponential demand for productivity and outputs. And I think that the way that you scale to that is with agents.”
“I think that's where agents will go. I think it's going to be more about product than it is about technology over time. Just going back to my metaphor, in 1998 when Mark and Parker started Salesforce, just getting that database running in the cloud was like a technical achievement.”
“Management is just about having an outcome. You have a north star, you have a vision, and you're just trying to figure out how to use the resources that you have to get that thing done. Used to be people, but now it's basically models and different models have different strengths. You have to assemble the Avengers so that you can use the right tools for the right purposes.”
AI will democratize expensive services - what was once only affordable for rich people and big companies (lawyers, chiefs of staff, call centers) becomes accessible to everyone through cheap intelligence.
Dan ShipperAI model training has evolved from simple preference tasks to requiring expert PhDs and professionals spending hours on sophisticated domain-specific labeling.
Jason DroegeGTM engineers are transforming sales by automating rote workflows with AI agents, enabling one SDR to do the work of ten while maintaining the same lead-to-opportunity conversion rate.
Jeanne GrosserThe allocation economy is replacing the knowledge economy - management skills like evaluating talent, having vision, knowing when to delegate vs dive in are becoming the most valuable skills as everyone becomes a manager of AI.
Dan ShipperThe biggest mistake in building new products is underestimating buyer urgency - value alone isn't enough if you're not solving the customer's most pressing daily concern.
Jason Droege80% of enterprise customers buy to avoid pain or reduce risk rather than increase upside - founders need to shift their pitch from art of the possible to risk reduction.
Jeanne GrosserCompanies should hire an AI operations lead - someone dedicated to identifying repetitive tasks across the organization and building prompts and workflows to automate them.
Dan ShipperIndependent thinking and unique insight are the foundation of entrepreneurship - you must understand why you have an insight that a million other smart entrepreneurs do not.
Jason Droege