A new AI startup is taking aim at one of the most persistent problems in modern work software: the gap between planning tasks and actually getting them done. Runner, founded by Charlie Feng, Yitong Zhang, and Kent Fenwick, is building what it calls an AI-powered execution workspace. Rather than focusing on task management or idea generation, the platform is designed to actively carry work across systems and complete it inside the tools teams already use.
The product connects with more than 50 applications, including Gmail, Calendar, Slack, LinkedIn, WhatsApp, and local files. The idea is to give the system enough context across communication and productivity tools to not just suggest next steps, but execute them. That includes preparing meetings, sourcing and organizing leads, and generating follow-ups without requiring users to manually switch between platforms.
In practice, Runner positions itself closer to an automation layer than a traditional productivity assistant. The company says its system is designed to understand context across multiple tools at once and complete multi-step workflows end to end, rather than stopping at drafts or recommendations.
Early traction has come from operators and teams looking to reduce manual coordination work across fragmented software stacks. Adoption so far has been largely organic, driven by specific use cases where teams are trying to eliminate repetitive administrative tasks rather than adopt yet another planning tool.
The company argues that its key advantage lies in the quality of its connectors. Charlie Feng, co-founder of Runner, said, “Most AI tools are still stopping at ideas or drafts. We built Runner so work actually moves through systems and gets completed, not just suggested.”
While many AI tools can generate outputs or summarize information, Runner is built to take action inside connected systems. In side-by-side comparisons on multi-step workflows, the startup claims its advantage becomes more visible in how reliably it can move from intent to execution across different apps.
Looking ahead, Runner is focusing on expanding the depth of its integrations and increasing task autonomy. The roadmap includes more complex multi-step workflow automation, broader team-level capabilities, and systems that can proactively manage work across organizations rather than responding only to user prompts.
If successful, Runner is betting that the next wave of workplace AI will not be defined by better suggestions, but by software that actually finishes the work.
