Recently, after chatting with a few friends and spending over ten hours a day immersed in coding agents, one feeling has become increasingly clear: this wave of AI is not one revolution, but two.
The Programming Track Has Been Talked About Enough
The first track is programming and productivity. Coding agents, AI office assistants—the entire workflow of white-collar workers in cognitive processing and software creation is being reshaped. There's been plenty of discussion on this track, and I've written about it before, so I won't elaborate.
A few figures to give a sense of scale: GitHub's statistics say AI has written 26.9% of production code, developers using AI save an average of 3.6 hours per week, and the number of merged PRs has increased by 60%. But there are also countervailing voices—a randomized controlled trial by METR found that core contributors to 16 large open-source projects actually slowed down by 19% after using AI tools, even though they felt 20% faster. When facing complex, large codebases, AI hasn't reached the point where you can use it mindlessly and expect good results.
My own gut feeling is that when you know exactly what you want, a coding agent can indeed boost efficiency by an order of magnitude. The key phrase is knowing exactly what you want.
The Other Track, Probably Underestimated
The second track is content creation. Text-to-image, text-to-video, image editing—what's happening in this direction is no less intense than on the programming side.
ByteDance's Seedance 2.0 is a watershed moment.
Released in February, API opened at the end of March. Artificial Analysis benchmarks gave it an Elo of 1269, surpassing Google Veo 3, Sora 2, and Runway Gen-4.5. Not just slightly ahead—a tier above. It can generate up to 20 seconds of 1080p video in one go, with music, dialogue, and sound effects synchronized, no post-production dubbing needed. Camera movement, lighting, and character actions can all be precisely controlled.
A friend of mine who works on AI short dramas said there are tons of teams in the industry sitting on tens of millions in cash waiting to use it. The day the API opened, my social media feed exploded with entrepreneurs in that space—short films made with it were everywhere, and the quality was on a completely different level from before.
The cost shift is staggering. Previously, a 25-minute episode of Japanese animation cost roughly 1 to 3.2 million RMB. A single episode of Attack on Titan was about 1.1 million RMB, and Jujutsu Kaisen was similar. Now a 3-minute AI short film costs 400 to 1,200 RMB. The per-minute cost has dropped to a few tenths of traditional methods. In blind tests, 73% of viewers couldn't tell the difference.
Another friend runs a small live-streaming e-commerce team and told me content production costs have dropped to one-tenth of what they were, while speed has increased tenfold. Previously a content creator cost over 10,000 RMB per month; now the same output costs an order of magnitude less. Demand completely outstrips supply.
Imagine one person spending a few thousand RMB and one week to make a 20-minute anime short. Previously impossible. Now the shape of it is already clear—text-to-video has reached its "ChatGPT moment." Once the path is found, cost reduction is only a matter of time. That's AI's rhythm: someone blazes a trail, and cheaper solutions inevitably follow, because at its core it's software, something that can be continuously iterated with data and training.
The Two Paths Are Diverging
I recommended a friend try using a coding agent. He said he hasn't had the energy to look into it lately—not because he isn't smart, but because all his time and passion are going into content creation. Every day he's figuring out how to build pipelines with the latest tools, how to express ideas at low cost. I thought about it: why should he study coding agents? That's not his direction.
The reverse is also true. I spend over ten hours a day in coding agents; if you asked me to study content-creation pipelines, I wouldn't reach that level anytime soon.
In my previous post I wrote about the divergence between Builders and Promoters. This time the feeling is more concrete: these two paths differ not just in role but also in tools, skills, and the passion required. There is overlap, but the intersection is shrinking while the divergence is widening.
This means it's not just people building products who are undergoing massive change. Those passionate about expression—content creators—will soon receive tools of the same magnitude. If you have a strong urge to express something about a topic, for the cost of a few dozen RMB and half a day's time, you can make a one-minute short video. Smartphones and TikTok (Douyin) already lowered the barrier to filming video once; next, that barrier will drop by another order of magnitude.
Agent to Agent: Meetings Are Dead
Both paths share a common downstream effect: they are changing how people interact with one another.
A friend asked me: if AI is getting this powerful, wouldn't it be safer for me to go back to face-to-face fields—sales, investor relations, supply chain?
I'm not so sure.
I now see meetings as an extremely inefficient format. I record an audio clip, AI transcribes it and organizes it into a document, and the information density exceeds that of a two-hour meeting. The other side uses an agent to digest the document and extracts the key points in minutes. What I accomplish in five minutes might take two hours of meetings just to get the full picture.
The efficiency gap is 100x. That's not hyperbole.
The infrastructure is rapidly taking shape. Google released the Agent-to-Agent protocol (A2A) last year, backed by over 50 companies including Salesforce, SAP, and PayPal. Anthropic's MCP lets agents plug into various tools and data sources. Earlier this year, the Linux Foundation launched the Agentic AI Foundation, with OpenAI, Anthropic, Google, and Microsoft all joining; by February, over 100 enterprises had followed. Gartner predicts that by the end of this year, 40% of enterprise applications will embed AI agents, up from less than 5% last year.
Your agent and the other party's agent analyzing, relaying information, and coordinating tasks in the background will be far more professional than two people chatting face-to-face. Agents don't need small talk; they don't need two weeks to build trust. They can synthesize judgments from all verifiable information, which is more reliable than listening to someone speak for two minutes and thinking, this person seems okay.
What E-Commerce Eliminated
This reminds me of e-commerce.
Before e-commerce, all transactions were face-to-face. To buy something, you had to meet the seller, build a relationship, and judge each other. The seller's social skills and personal charisma were critical to closing a deal.
E-commerce arrived. Products are roughly the same, so you compare prices, read reviews, and place an order in ten minutes. You don't know the seller, you've never met them, and they don't even know you bought from them. The B2B space is the same—buyers have completed 57% to 70% of their purchasing research before contacting sales, and 67% of the purchasing journey happens online.
E-commerce didn't eliminate retail. Physical retail still accounts for 81.6% in the US. But it restructured the relational logic of transactions—face-to-face social skills went from essential to nice-to-have.
Agent-to-agent will bring a similar but much stronger wave. When the efficiency gap is 100x, people will choose the more efficient option in many scenarios. It's not that humans no longer matter; it's that business matters now have a better channel.
Stop Talking Business on the Court
There's a side effect I think is quite positive: human relationships will become more pure.
Before, you played ball to talk business, and you had dinner to discuss partnerships. Face-to-face was the most efficient form of business communication, so socializing and commerce were always intertwined. You didn't go play ball just because you loved the game; you went because the court was where you could meet people you wanted to know.
What if agents handle the business side? Then playing ball is just playing ball. Socializing is just socializing. You no longer have to maintain unwanted relationships in settings you don't enjoy.
Intimacy, entertainment, interests—these needs will be stripped out of business contexts. It's not that they aren't important; it's that they can finally just be themselves.
Go Find It
Two revolutions are unfolding simultaneously, each demanding deep investment of time.
The pattern I've observed is simple: people with passion spend ten hours a day immersed in it and master every tool. Those without passion open it occasionally, and the gap quickly becomes orders of magnitude. The leverage of AI is right there; whether you can pry it loose depends on whether you're willing to keep applying force.
Whether you're building products or creating content—go find the thing you can't stop doing.