Key takeaways
- Solaris, from video generation company Runway, predicts and renders the next screen directly rather than writing code that a browser then interprets.
- In a comparison test with 250 evaluators, 61% preferred Solaris-generated interfaces on "does it understand the instruction," and 71% on "does it feel natural to use."
- The chain it compresses: idea → get a quote → write a requirements document → develop → revise three times becomes idea → describe it → have something clickable.
- What it cannot yet do: a button must still be the same button on the fifth click. Saved state, accessibility and error recovery are the hard parts of software, and they are not solved.
The wall you hit at RMB 8,000
You have had this thought. You want a small tool to manage members at your shop. A sign-up page for a club. A medication reminder for an elderly relative.
You ask for a quote. Eight thousand yuan, minimum, two weeks' wait.
So you give up and keep struggling along with Excel and a WeChat group.
That wall may genuinely be coming down.
It works backwards from every other AI coding tool
Here is how other AI coding tools operate: write a large amount of code, then let the browser translate that code into the picture you see.
Solaris inverts it. It does not write code. It draws the interface itself, frame by frame. You click, you drag, and it predicts what the next screen should look like and generates that screen directly.
Runway ran a comparison with 250 evaluators. On "did it understand the instruction," 61% preferred the Solaris result. On "does it feel natural to use," 71% did.
What that means in practice: the long chain from an idea to something usable — quotation, requirements doc, development, three rounds of revision — is being compressed into describe it, and have something you can click.
Before anyone announces the death of programming
Some cold water, because that announcement is premature.
Solaris's weakness is visible. A button has to still be that same button after five clicks. Saved state, accessibility support, recovery after an error — the things that look trivial are exactly what makes software hard. Generating one attractive screen is not difficult. Keeping a hundred screens mutually consistent, without losing data or crashing, is.
It is also still an application-based early access programme, not something anyone can use.
A more accurate read:
- What will be replaced: simple interfaces that only need to look right and work — event sign-up pages, internal utilities, dashboard prototypes, in-store ordering screens.
- What will not be replaced soon: systems involving money, multi-user collaboration, long-lived data, or high cost of failure.
Put differently, AI eats first at the small requirements that were too expensive to be reasonable but had to be done anyway. That layer used to sustain a great many small outsourcing teams.
Where the opportunity actually is
The real change is not "fewer programmers." It is that who gets to make a product has been rewritten.
Previously, building a tool required understanding technology or affording someone who did. Afterwards, what determines whether you can build it is how well you understand the scenario. You understand the pain of running a restaurant, so you can build yourself a shift scheduler. You understand the chaos of a parent group chat, so you can build a sign-up counter.
Three directions you can move on immediately:
- Start with your own small annoyance. Do not begin by trying to build a platform. Build one page that solves one problem of yours, and think about others only once you have used it.
- Convert "I understand the domain" into a moat. Once the technical barrier collapses, what remains is who better understands what the user is struggling with. This is a dividend period for industry veterans.
- Do not bet on a new tool before checking whether it is stable. Early products change fast. Prototypes and validation are fine; do not move critical operations onto one yet.
Worth remembering: when the cost of making something approaches zero, what is valuable is no longer being able to make it, but knowing what should be made.
Over the next two years the scarcest person may not be the one who can write code. It may be the one who knows clearly who a thing is for and what pain it removes.
Honest limitations
The preference percentages come from a vendor-run evaluation with 250 participants and have not been independently replicated. Solaris was described as early-access at the time of writing, so availability and capabilities will have changed. The "button must remain the same button" limitation is an interpretation of the state-consistency problem rather than a quoted statement.
Sources: Runway product material and evaluation results; contemporaneous reporting (September 2026). Information only.