Before Soloop, I built products at a large tech company. Our team could solve hard product problems, but we spent too much time waiting for decisions to move through meetings, quarterly reviews, reports, and handoffs.
AI coding tools later made it possible for one person to ship a working product. I could build the first version alone, then faced the work code could not cover: choosing an audience, finding users, reading their feedback, and deciding what to build next.
I built Soloop to give a solo founder a coordinated AI team.
You give the AI CEO a company goal. It makes the plan and coordinates the other agents. The AI CTO builds and iterates from user signals. The AI CMO finds potential users, runs distribution, and brings their responses into the next decision.
While building Soloop, we stopped treating each agent as a standalone assistant. Separate assistants left the founder carrying context between chats and reconciling their plans. We organized the team around one company goal and a daily review. Soloop brings decisions that need judgment back to the founder for approval.
Soloop is early, and we want solo founders to shape it with us.Where does the path between a working demo and a real business break down for you? Which part would you trust an AI team to run?
PH 用户
Hey Product Hunt,
I’m Qingfeng Meng, CFO of Soloop.
I first knew this company as an investor. At Shuimu Tsinghua Alumni Seed Fund, I worked on investments in more than 30 Tsinghua-founded startups. I later worked on global GTM at Zhipu AI. After the fund invested, I crossed the table and joined the team.
Early-stage investing taught me to treat every important decision as an allocation of capital. That capital includes cash, a founder’s time, and the paths given up by choosing one direction over another. Building, selling, and waiting all have a cost.
I measure an AI team by how much uncertainty it removes each week. Soloop helps a founder turn a company thesis into a focused bet, test it in the market, and bring back evidence before making the next commitment. Most AI tools make an individual task cheaper. Soloop aims to reduce the cost of deciding what the company should do next.
That is the vision I joined: a founder with conviction should be able to build a real company without first assembling a large organization.
My job is to help make the economics of that model work. I’d be glad to hear your stories and explore collaborations with founders, operators, and investors building or backing one-person companies.
PH 用户
I designed almost exactly this for my own company — departments instead of loose agents, each with a manager, shared memory, daily reviews. The one place I landed differently is approval. I started approval-first and moved to "execute and report, stop only at what's irreversible", because the approval queue became the bottleneck it was meant to remove. As a solo founder my scarcest resource is attention, and a system that asks me twelve times a day is a slower version of doing it myself. Curious how you're drawing that line — is "requires approval" a fixed category, or does it widen as the founder builds trust?
PH 用户
Hey Product Hunt,
I’m Xinyu Shi, CTO of Soloop.
Building Soloop taught me that creating a useful AI team is very different from putting several agents into the same product.
The hard part is not getting an agent to generate code, write a marketing post, or produce a plan. The hard part is making sure every agent understands the same company goal, works from the same context, and turns its output into something the next agent can actually use.
As CTO, I’ve focused on building the system behind that coordination.
When the AI CMO discovers a user need, the insight should not disappear inside a chat history. It should become structured context for the AI CEO to evaluate and, once approved, a clear task for the AI CTO to implement.
That requires more than prompts. It requires shared memory, clear ownership, reliable handoffs, execution environments, approval checkpoints, and feedback loops that help the system improve without taking control away from the founder.
We are still early, and many of the most interesting technical problems are ahead of us: how much autonomy agents should havehow they should recover from failureand how founders can understand why a decision was made.I’d love to hear from other builders:What would make you trust an AI agent with a real part of your company?And where do today’s coding agents or multi-agent systems fail you most often?
PH 用户
Love the focus on keeping the founders in control. Ai should amplify decision making , not replace the vision and judgment that make a company unique.
I’m Wenhao Yu, founder of Soloop.
Before Soloop, I built products at a large tech company. Our team could solve hard product problems, but we spent too much time waiting for decisions to move through meetings, quarterly reviews, reports, and handoffs.
AI coding tools later made it possible for one person to ship a working product. I could build the first version alone, then faced the work code could not cover: choosing an audience, finding users, reading their feedback, and deciding what to build next.
I built Soloop to give a solo founder a coordinated AI team.
You give the AI CEO a company goal. It makes the plan and coordinates the other agents. The AI CTO builds and iterates from user signals. The AI CMO finds potential users, runs distribution, and brings their responses into the next decision.
While building Soloop, we stopped treating each agent as a standalone assistant. Separate assistants left the founder carrying context between chats and reconciling their plans. We organized the team around one company goal and a daily review. Soloop brings decisions that need judgment back to the founder for approval.
Soloop is early, and we want solo founders to shape it with us.Where does the path between a working demo and a real business break down for you? Which part would you trust an AI team to run?
I’m Qingfeng Meng, CFO of Soloop.
I first knew this company as an investor. At Shuimu Tsinghua Alumni Seed Fund, I worked on investments in more than 30 Tsinghua-founded startups. I later worked on global GTM at Zhipu AI. After the fund invested, I crossed the table and joined the team.
Early-stage investing taught me to treat every important decision as an allocation of capital. That capital includes cash, a founder’s time, and the paths given up by choosing one direction over another. Building, selling, and waiting all have a cost.
I measure an AI team by how much uncertainty it removes each week. Soloop helps a founder turn a company thesis into a focused bet, test it in the market, and bring back evidence before making the next commitment. Most AI tools make an individual task cheaper. Soloop aims to reduce the cost of deciding what the company should do next.
That is the vision I joined: a founder with conviction should be able to build a real company without first assembling a large organization.
My job is to help make the economics of that model work. I’d be glad to hear your stories and explore collaborations with founders, operators, and investors building or backing one-person companies.
I’m Xinyu Shi, CTO of Soloop.
Building Soloop taught me that creating a useful AI team is very different from putting several agents into the same product.
The hard part is not getting an agent to generate code, write a marketing post, or produce a plan. The hard part is making sure every agent understands the same company goal, works from the same context, and turns its output into something the next agent can actually use.
As CTO, I’ve focused on building the system behind that coordination.
When the AI CMO discovers a user need, the insight should not disappear inside a chat history. It should become structured context for the AI CEO to evaluate and, once approved, a clear task for the AI CTO to implement.
That requires more than prompts. It requires shared memory, clear ownership, reliable handoffs, execution environments, approval checkpoints, and feedback loops that help the system improve without taking control away from the founder.
We are still early, and many of the most interesting technical problems are ahead of us: how much autonomy agents should havehow they should recover from failureand how founders can understand why a decision was made.I’d love to hear from other builders:What would make you trust an AI agent with a real part of your company?And where do today’s coding agents or multi-agent systems fail you most often?