AI Works for Me, But I'm More Exhausted

Builders, dopamine and the new end‑to‑end reality

AI has stopped being a neat productivity boost and started doing whole projects end to end. That is the blunt takeaway from a reported conversation published by ifeng (凤凰网) about OpenAI’s Builders Unscripted episode featuring developer Peter Steinberger and host Romain. What began as “AI-assisted coding” has, they say, leapt into agentic engineering: systems that can spec, build, test and even ship parts of an application. Excitement is high. So is fatigue.

Community momentum and the cost of scale

Steinberger described intense bursts of creativity and community interest around his OpenClaw work — it has been reported that almost 1,000 people attended a San Francisco meetup and over 300 signed up for an event in Vienna — and that thousands are already using early builds. Tools and models named in the discussion range from Claude and Gemini to Codex, Playwright and Cloud Code; Steinberger recounted wiring a half‑finished project into an agent loop, watching builds run unattended for hours, and seeing fragile but real results. Reportedly, those moments — when an AI completes a login flow or translates an image in poor network conditions — deliver the “dopamine” that pulls builders back in.

Optimization myths and human limits

Many builders, Steinberger warns, get stuck micro‑optimizing their local setups and feel “more efficient” without meaningful gains. The real leverage, he says, is reworking repositories and collaboration patterns so agents can operate effectively across a codebase. Yet the human cost is visible: Steinberger admits to burnout after years of entrepreneurship and describes the pain of relearning and adapting when a whole toolchain shifts. Agentic workflows speed development, but they also expose new fragilities and demand different engineering discipline.

Why it matters beyond the hype

For Western readers unfamiliar with China’s tech conversation, the ifeng coverage shows a global developer audience wrestling with the same questions: who owns these agentic tools, what standards and safety regimes will govern them, and how will geopolitics — from cloud access to chip export controls — shape who can scale these ideas? OpenClaw’s rapid, community‑driven rise underscores one trend: open, messy experimentation is pushing capabilities forward faster than corporate roadmaps. The question now is less whether AI can build for us, and more whether it will change what it means to be a builder — or simply make us busier and more exhausted in new ways.