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The Bootstrapped Founder

410: Building for the Age of AI Consumers

23 min episode · 2 min read

Episode

23 min

Read time

2 min

Topics

Remote Work, Artificial Intelligence, Software Development

AI-Generated Summary

Key Takeaways

  • Rate Limiting for AI Features: Implement internal rate limits on any user-triggered AI functionality that costs money per request, capping usage to a few times per minute regardless of user count to prevent spending hundreds of dollars daily on unintended API consumption.
  • Model Context Protocol (MCP): Explore MCP as the first standardized attempt to make products accessible through large language models, enabling customers to integrate your service into their agentic workflows and conversational AI systems while maintaining structured programmatic access.
  • Session Definition Challenge: Traditional concepts like sessions, requests, and workflows become ambiguous with AI agents that pause for human approval mid-execution, requiring new frameworks to define boundaries between synchronous human interactions, asynchronous machine processes, and hybrid consumption patterns.
  • Domain Specific Languages: Flexible query systems like Elasticsearch's DSL and GraphQL offer infinitely configurable interfaces that AI agents need, allowing them to construct novel queries without requiring developers to implement new endpoints for every possible use case or data combination.

What It Covers

Software products must now serve AI agents that combine human-like exploration with machine speed, requiring new interfaces beyond traditional websites and APIs to handle flexible, unpredictable consumption patterns while managing security and cost risks.

Key Questions Answered

  • Rate Limiting for AI Features: Implement internal rate limits on any user-triggered AI functionality that costs money per request, capping usage to a few times per minute regardless of user count to prevent spending hundreds of dollars daily on unintended API consumption.
  • Model Context Protocol (MCP): Explore MCP as the first standardized attempt to make products accessible through large language models, enabling customers to integrate your service into their agentic workflows and conversational AI systems while maintaining structured programmatic access.
  • Session Definition Challenge: Traditional concepts like sessions, requests, and workflows become ambiguous with AI agents that pause for human approval mid-execution, requiring new frameworks to define boundaries between synchronous human interactions, asynchronous machine processes, and hybrid consumption patterns.
  • Domain Specific Languages: Flexible query systems like Elasticsearch's DSL and GraphQL offer infinitely configurable interfaces that AI agents need, allowing them to construct novel queries without requiring developers to implement new endpoints for every possible use case or data combination.

Notable Moment

Cloudflare introduced a web payments API allowing website owners to charge AI scrapers like OpenAI and Anthropic micro-amounts per scrape, transforming access control from binary yes-no permissions into conditional, transaction-based authorization models for AI consumption.

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Episode Transcript

Hey. I'm Arvid, and this is the Bootstrap founder. I think we're at the precipice of a pretty significant change in how we build software products. And I know I say this a lot and I've said this every year, but this time, I think it's weird in a way. Obviously, the recent ascent of wipe coding and all the agentic coding tools that we all find super useful and highly effective, well, that shows a difference in how we approach building products. Sure. But there's another change, not just in how we build, but in who we build these products for. This episode is sponsored by paddle.com, my merchant of record payment provider of choice who's been helping me focus on PodScan and my other projects. They have been taking care of all things related to money so that founders like you and me can focus on building the things that only we can build for all the audiences we might wanna serve with that. Paddle handles all the rest, sales tax and credit cards failing, all of that. I highly recommend it. So please check out paddle.com. Now there used to be a time where websites were mostly for people, and people were browsing websites. They were reading websites. They were handwriting websites in HTML in text editors. If you did this in school or at any point, I commend you. It was a great time to learn how to be on the web and how to produce something meaningful. The late nineties, early two thousands were pretty much that. And then, of course, technology evolved around it, and it made it easier to build things, but that's kinda what websites were. Right? They were crafted HTML for people by people. And then there was a time where APIs became all the rage, and applications became these programmable things that could work with each other. They would exchange information and orchestrate each other to get data from one point to the other. And first, software was made for people and then software was made for machines to consume. Of course, I know that software was always for machines to consume. Even an HTML website technically was consumed by the browser before the person used it, but you know what I mean, right? It was meant for active consumption by other machines in a scaled way. And now we have this weird hybrid of man and machine, and that's the new thing. That's agentic AI. The AI that follows human logic and has human approaches to process and discovery and exploration, but is effectively a machine that can do things much faster and much more targeted, maybe also much more dangerously than what most humans alone could do. So we are looking at the age of building software and interfaces, most importantly, for AI systems. And it's always a progression. Right? When you look at user interfaces, browsers, or desktop applications, there was this progression towards making these things …

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Books, tools, and gear mentioned in this episode

SignalCast may earn commission on purchases via these links.

Tools

  • Explore MCP as the first standardized attempt to make products accessible through large language models, enabling customers to integrate your service into their agentic workflows and conversational AI systems while maintaining structured programmatic access.
  • by Elastic

    Flexible query systems like Elasticsearch's DSL and GraphQL offer infinitely configurable interfaces that AI agents need, allowing them to construct novel queries without requiring developers to implement new endpoints for every possible use case or data combination.
  • Flexible query systems like Elasticsearch's DSL and GraphQL offer infinitely configurable interfaces that AI agents need, allowing them to construct novel queries without requiring developers to implement new endpoints for every possible use case or data combination.
  • by Cloudflare

    Cloudflare introduced a web payments API allowing website owners to charge AI scrapers like OpenAI and Anthropic micro-amounts per scrape, transforming access control from binary yes-no permissions into conditional, transaction-based authorization models for AI consumption.

company

  • SPONSORS [{"name": "Paddle", "url": "https://paddle.com"}]

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