Signal to BuildSIGNAL TO BUILD中文Owner sign in ↗Find the mechanisms, cases and conditions in each episode. Start with a topic, follow a guest, or read chronologically to see how perspectives change.
Dates refer to original episode releases. An episode may have multiple topics; roles and claims retain their historical context.
Guests / narrator：张阳
Once AI writes code, can small games be consumed in a scrolling video-like feed? Zhang’s team explored that direction, then chose deeper creation tools and play among friends. Ordinary generated material may offer strangers limited value, while friendship supplies a shared reason to care.
Guests / narrator：Binson
逗逗游戏伙伴 is an AI desktop companion that watches gameplay, accompanies players and converses. Binson’s approach asks users to allocate less additional time to AI content: participate in something they already want to do. The game continues while the companion acts like interactive commentary beside it.
Guests / narrator：Ted
Open conversation has no single correct answer. A user may enjoy a response, rewrite it, delete it or request another. Reflecting on approximately a year at Character.AI, Ted discusses turning such behavior into data, training and experiments. The central subject is a system that continually discovers mistakes.
Guests / narrator：Tristan
Tristan wants EVE to build a continuing relationship around the real user’s life: understanding earlier experiences, connecting them with present goals and participating in new daily conversations. He distinguishes this aim from jointly creating stories about characters. The host points out that extended use can also come from consuming content.
Guests / narrator：陶芳波
An AI can retrieve information or fill out forms without knowing which result matters to you. Tao uses this distinction to explain the move from MindOS to Me.bot: first build AI that understands an individual’s needs, then let it call tools providing services. He also wants AI to keep learning from daily experience rather than depend permanently on its original workflows.
Guests / narrator：赵充 / Joe / 胡修涵
Product–market fit, or PMF, means that a group of people repeatedly finds a product worth using or paying for. These three interviews show why no single number proves it for every business. An occasional office tool can first demonstrate that individual tasks merit payment. Professional software needs to participate in real delivery. A character entertainment product must explain why people return.
Guests / narrator：张涛（Hidecloud）
Hidecloud previously designed consumer products and worked on customer success, presales and consulting at 神策数据. Reflecting on roughly seven months of AI practice, he repeatedly emphasizes understanding through direct work: how a model receives input, where it fails and which change makes an interaction possible. His argument does not require every product manager to become an algorithm engineer.
Guests / narrator：Jay 党嘉成
A prompt contains instructions, background and rules supplied to a model. Sharing one can resemble sharing a template, but a consumer may actually want a text adventure, a conversational character or a tool that repeatedly completes a task. FlowGPT’s changing description reflects a move from collecting instructions toward consuming those experiences directly on its platform.