Reading path
Tech founder building on AI
From GPT-3 to your product: APIs, costs, agents and MCP as infrastructure.
You are a founder, product manager or startup CTO who wants to build a real product on top of AI — not a demo. This path guides you through the foundational decisions (closed APIs vs open source, costs, vendor lock-in) all the way to modern agentic infrastructure, covering the milestones that concretely changed what you can ship today.
- 01
Why it matters to you
The moment mass-market users met LLMs: if you are building a consumer or B2B AI product, this is the ground zero of your category.
Landmark Foundation ModelsChatGPT: AI lands in everyone's browser
OpenAI launches ChatGPT, a free conversational interface on GPT-3.5 aligned via RLHF. It crosses one million users in five days.
- 02
Why it matters to you
Opening the API makes it possible to integrate the model into your product in a few lines of code: this is where the wrapper economy and vertical AI SaaS begin.
High Foundation ModelsChatGPT API: gpt-3.5-turbo at $0.002 per 1K tokens
OpenAI ships the ChatGPT API (gpt-3.5-turbo) at one tenth the price of text-davinci-003, plus Whisper API for speech-to-text. The wrapper era begins.
- 03
Why it matters to you
The primitive that turns an LLM from a chatbot into a structured component: you cannot design a product that integrates with real data without understanding function calling.
High AI InfrastructureFunction calling: GPT learns to speak JSON
OpenAI adds 'function calling' to the API: the model returns structured JSON conforming to a schema, enabling reliable tool integrations without fragile prompt engineering.
- 04
Why it matters to you
The first distributed marketplace of specialized GPTs: study why it struggled to take off before deciding whether your distribution runs through a closed ecosystem.
Medium Enterprise AIGPT Store: the custom GPTs marketplace opens
OpenAI launches the GPT Store inside ChatGPT: anyone with Plus/Team/Enterprise can publish custom GPTs. First serious attempt at an app store for AI agents.
- 05
Why it matters to you
The project that popularized the autonomous agent concept: essential for understanding the real limits of unsupervised agents before promising them to your customers.
High AgentsAutoGPT: the first viral AI agent
A developer publishes AutoGPT on GitHub: given a text goal, the system calls GPT-4 in a loop to plan tasks, execute them, and self-criticize. In two weeks, becomes the most-starred repo in history.
- 06
Why it matters to you
The open standard for connecting agents and tools: adopting it in your infrastructure now means not rewriting everything in six months when it becomes the default.
High AI InfrastructureModel Context Protocol: the open standard to connect LLMs and data
Anthropic open-sources the Model Context Protocol (MCP), a JSON-RPC standard that lets AI assistants talk to tools, file systems, databases, and SaaS without per-model ad-hoc integrations.
- 07
Why it matters to you
The first general-purpose agent that convinced non-technical users: analyze what made the product credible to understand where the boundary of AI products is shifting.
High AgentsManus: the Chinese 'general-purpose' agent that runs tasks end-to-end
Butterfly Effect launches Manus, an invite-only Chinese AI agent that runs autonomous tasks (stock analysis, research, CV screening) and ships reports with files. Devin-2024-level hype, invite-only access.