UISEE Launches Coding Harness Platform ZaoFu

2026-07-21

Now that Claude Code, Codex, and OpenCode can

already complete code generation tasks efficiently, what does the future hold

for AI Coding Agents? On July 17, Wu Gansha, Co-founder, Chairman and CEO of

UISEE, attended the 2026 Singularity Intelligence Product Conference co-hosted

by CSDN and the Singularity Intelligence Research Institute. From the

perspective of a physical AI product manager, he shared in-depth thoughts on

entrepreneurship in the era of AI large models, and announced the open-source release of the Coding Harness

Platform independently developed by UISEE — ZaoFu.

What Problem is ZaoFu Actually Solving?

"ZaoFu" derives from the legendary

charioteer in ancient Chinese mythology who skillfully commanded eight steeds.

The name embodies UISEE's core insight about AI Coding Agents: "A fast

horse does not guarantee that the carriage will reach its destination

steadily."

True

delivery is not a single prompt, nor does it end when code is generated.

From idea to deliverable software, goals must converge, tasks must be

decomposable, context must remain intact, status must be visible, evidence must

be traceable, failures must be recoverable, and memory must be inheritable.

Each of these aspects is as important as "writing code" itself, yet

none of them are addressed by Coding Agents.

In future-oriented AI Native organizations, what is

truly missing is not more powerful agents, but the ability to organize agents

into a software delivery system. This is precisely why ZaoFu was created — ZaoFu is not building a "faster

horse"; it aims to be the greatest charioteer.

As an outcome-oriented Coding Harness Platform

designed for real-world software delivery, ZaoFu focuses on goals, rhythm, status, and results,

enabling different agents to excel at what they do best. It does not replace

any AI Coding Agent; instead, it provides them with a schedulable, observable, and governable Harness team engineering

framework, truly integrating agents into the engineering delivery closed

loop.

Starting from Idea, Issue, and Refactor, ZaoFu

continuously advances goals, tasks, code, tests, and evidence toward delivery,

completing the systematic capability from idea to deliverable software.

ZaoFu's Three Core Mindsets

The triad of "GOAL defines completion, HARNESS organizes execution, LOOP continuously

approaches completion" constitutes ZaoFu's core product mindset,

corresponding to goal standardization, agent boundary governance, and

long-range execution closed loop, respectively.

Starting with goal definition, GOAL aims to turn intent into provable outcomes. It drives

multi-agent collaborative discussions via IM to generate PRDs. Each GOAL

encompasses four key elements: expected outcomes, scope boundaries, acceptance

evidence, and gap-driven progress, transforming vague ideas into reviewable,

acceptable goals.

Through

HARNESS, execution is organized and engineering boundaries are maintained,

organizing Tasks, Roles, Agents, code, tests, and evidence into a governable

engineering system with boundaries, contracts, evidence, and governance. Agents

can analyze, suggest, and initiate actions, but critical state changes cannot

bypass the Kernel and must leave traceable evidence and audit trails.

LOOP continuously converges based on feedback, enabling

long-range execution through continuous observation, diagnosis, verification,

recovery, and review until deliverable outcomes are achieved.

Additionally, ZaoFu supports three workflows: PRD,

Issue, and Refactor — whether redefining products, temporarily fixing bugs or

iterating on features, or refactoring software — all with continuous delivery

tracking.

Accelerating Physical AI Industrialization with AI Native

As autonomous driving moves toward a scaled

subscription model, AI plays a crucial role throughout the entire lifecycle. In

the development phase, it enables low-cost, platform-based, and standardized

product design; in the deployment phase, it enables rapid, customized

out-of-the-box delivery; in the operations phase, it enables data-driven

O&M, minimizing costs and maximizing availability.

由造父生成的智慧港口业务模拟场景

ZaoFu's implementation in the autonomous driving

business has created unparalleled value for UISEE. Teams, people, agents, code,

tests, and evidence continuously flow around tasks, while Web, CLI, Channel,

and Feishu provide entry points for collaboration, observation, and controlled

actions. The Tasks Board uniformly carries the delivery status of PRD, Issue,

and Refactor, making task progress a

shared truth for the team. From Workflow Stage to every Agent Attempt, the entire execution process is visible in

real time, and every agent action is traceable. Through deep integration

with Feishu driving the complete closed loop, people and multiple agents clarify ambiguous issues through roundtable

discussions, forming reviewable PRDs before entering task execution.

由造父生成的智慧城市业务模拟场景

To achieve an end-to-end closed loop from

requirement definition and task decomposition to continuous delivery, and to

further enhance R&D efficiency and organizational leverage, a Coding

Harness Platform like ZaoFu is indispensable.

ZaoFu is now officially open source. Everyone is

welcome to use it.