The Design-Code Roundtrip That Isn't — Jonathan Gordon, ReWeaver AI
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The Design-Code Roundtrip That Isn’t
Jonathan Gordon tests the promise of lossless movement between design and code, finds drift across five tool setups, and proposes deterministic reconciliation that keeps AI generation inside human-controlled guardrails.
From a talk by Jonathan Gordon
At a glance
Ideas worth remembering
A true design–code roundtrip must be bidirectional, lossless, and provenance-preserving; generating similar artifacts on both sides is insufficient.
The
innerHTMLincident shows why fast code generation still requires inspection: plausible output can conceal security or production-readiness problems.Scanning design and code together can expose omissions that visual comparison misses, such as a dynamic element without an ARIA live region.
Five tested tool setups lost bindings or failed to carry changes into both representations, demonstrating that one-way generation is not yet a lossless roundtrip.
Deterministic guardrails should surround probabilistic generation: apply known fixes, report uncertain findings, and preserve human authority over code, design, and cost.
Unwatched drift compounds over time into maintenance work—the “new tech debt”—so reconciliation must happen continuously and before merge.
A roundtrip must preserve more than pixels
Jonathan Gordon, founder of ReWeaver AI, opens with a small piece of AI-assisted improvisation: after display mirroring hid his speaker notes, Claude extracted them from the slide deck. Whether it extracted them correctly was another question. That uncertainty neatly previews the larger problem: a generated result can look useful without proving that it faithfully preserves its source.
A genuine design–code roundtrip has three requirements. It must move in both directions, preserve fidelity, and carry persistent provenance. If a button appears on a design canvas, the system should know which code produced it; if someone changes that button in the design, the corresponding code should change without losing bindings, behavior, tokens, or other meaning.
That standard is higher than generating a clickable mockup or visually similar component. Design and engineering have historically optimized for different outcomes: design carries product intent, branding, and a vision of what the customer should experience, while engineering must satisfy technical requirements and constraints. Gordon’s more than 30 years building developer tools and working across that handoff never produced a perfectly closed loop. Negotiation could get software shipped, but it could not guarantee that intent and implementation remained identical.
Large language models appeared to remove that organizational split. One model could interpret design intent and write code, suggesting that the loop might finally close “at the speed of inference.” The important question, however, was not whether a model could create both artifacts. It was whether repeated movement between them remained lossless.
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The `innerHTML` moment ends blind acceptance
Gordon tested that possibility by going all in on vibe coding beginning in April 2025. Cursor told him he was in its top 0.1% of usage—an achievement that prompted the conclusion, “I need to spend more time outside.” Underneath the joke was a sustained experiment: move from design to code, move back from code to design, and see whether the pixel-perfect result survives.
The turning point came while generated code streamed past faster than he was reading it. The token innerHTML caught his eye. Because writing untrusted content through that API can create an injection risk, he stopped the agent, asked what it had done, and ordered a revert. The observable change in his workflow mattered more than the individual correction: the code stopped being background output and became an artifact requiring inspection and steering.
Once he began reading again, more issues appeared. The same skepticism then applied to public demonstrations of code-to-canvas workflows. Creating a Figma artboard from a Claude Code prompt looked magical, but successful generation in one direction did not establish a roundtrip. The test had to include the return journey and inspect what disappeared along the way.
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“Show Drift” checks both sides of the handoff
The demonstration harness puts AI-generated code on the left and a design canvas on the right. Either side can serve as the starting point, and an LLM-mediated prompt performs the transformation. In the example, a form becomes a design system represented in both a running application and Figma.
A design system supplies the shared vocabulary: components, tokens, variables, and styles become the basis for constructing software. The example then changes visibly. A company field and an orange button appear, and both the code and design update. That is enough to demonstrate synchronized generation. It still does not prove that the relationship can survive another trip backward.
The Show Drift action changes the question from “Did both sides update?” to “Where do they now disagree or fall short?” ReWeaver scans the code and design together and groups findings across dimensions including design quality, code quality, performance, and design tokens. This treats the rendered result and its implementation as two representations to reconcile, rather than trusting either one as complete.
Accessibility provides the concrete failure. The scan finds a dynamic element without an ARIA live region, which means a screen reader will not announce its update to a blind user. ReWeaver offers a fix; after it is applied, the red issue disappears while another blue issue remains. The sequence is inspectable: generation produces an apparently working interface, the scanner detects an omitted accessibility behavior, the user authorizes a correction, and the finding changes state without pretending every other issue is solved.
What relationship does this make visible? The diagram shows why a visual match alone cannot close the loop: both representations must feed a common reconciliation step, and a human must decide what happens to each finding.
One representation of the interface and its behavior.
Code and design are scanned together. Findings can be fixed only after an explicit decision, and unresolved findings remain visible.
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Five tool setups still lose information
Testing five bidirectional tool setups did not produce a complete code–design–code roundtrip. The failures were lossy in different ways: bindings disappeared, or a change survived in the design while the corresponding code did not. These outcomes leave open the possibility that future tools will improve, but they show why a successful one-way demo cannot establish persistent fidelity.
The proposed remedy comes from conventional developer tooling. Compilers, parsers, and abstract syntax trees provide repeatable structure: the same input can be checked against the same rules. Put a probabilistic model before, inside, or after that process and identical outcomes are no longer guaranteed. Deterministic guardrails therefore surround rather than replace AI, checking its artifacts for known mismatches after generation.
Three kinds of drift emerge from this model:
- Representation drift: code and design no longer describe the same component, token, binding, or state.
- Production drift: generated code works nominally but omits qualities such as accessibility, performance, or governance.
- Temporal drift: small unobserved changes accumulate over repeated iterations until the codebase carries a new form of technical debt.
A separate experiment ran 12 iterations over a codebase with a sufficiently complex interface, comparing pure model-led output with output checked and corrected through deterministic guardrails. Gordon reports that pure model output began around 30% fidelity and degraded, while guarded iterations held up better; he also reserves the final stretch for human judgment. The talk does not define the fidelity calculation, show the underlying series, or explain how the stated percentages relate, so it supports the direction of the reported result rather than a measurable effect size.
This changes the unit of concern. Drift in one generation is a review finding. Drift over six months becomes accumulated maintenance work—“the new tech debt.” The danger is not merely that one model response varies, but that variation keeps entering a codebase faster than people notice and reconcile it.
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Human in control, not merely in the loop
The target system is fully bidirectional and lossless: edits travel both ways, all relevant surfaces remain intact, and provenance identifies where each element came from. If a button in Figma originated from a particular line of code, changing the button should preserve that relationship rather than silently creating two independent artifacts.
Deterministic reconciliation then follows an accept-or-refuse rule. When the system knows a valid correction, it can propose that fix. When it knows only that something is wrong, it should report the issue and leave the resolution to a person. Refusal is valuable because uncertainty remains explicit instead of being converted into another plausible approximation.
ReWeaver is described as using a fully local LLM at its core, with optional connections to external models, and as adding no extra token cost in its default configuration. More important than model placement is the control model: the person retains authority over cost, code, and design. Generated changes remain visible, reversible, and ignorable.
That is a stronger role than being summoned only when an agent encounters trouble. “Human in the loop” can still leave the agent directing the process. “Human in control” makes automation subordinate to explicit decisions about what should change and what should ship. Gordon jokingly names the desired result “winny wig”: what you need is what you get.
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Catch drift before anything merges
ReWeaver organizes its checks into nine top-level dimensions of software quality and production readiness. The talk names three in detail. Design consistency checks whether a codebase and its design system still agree. Accessibility gets its own dimension rather than being folded into generic code quality. AI code governance records and controls generated changes as code moves quickly through the system.
The product’s authority remains deliberately bounded. ReWeaver does not independently decide to rewrite the repository. When a user selects Apply the fix, it writes the proposed change visibly; the user can undo it, ignore it, or leave the finding unresolved. The goal is a closed loop that catches drift before merge without turning detection into unreviewed autonomy.
The public playground accepts AI-generated code and returns scan results. Gordon also describes a challenge based on PDR, or production drift ratio, with beta access offered for code scoring below 0.30. The recording does not explain the formula for PDR, so the score is best treated as a product-specific diagnostic rather than a general code-quality metric.
The durable lesson is not that AI should leave the workflow. Generation stays. What changes is the surrounding discipline: inspect both design and code, preserve provenance, use deterministic checks for properties that can be checked, refuse uncertain automatic repairs, and keep the person who owns the product in control of the final change.
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Resources
From the talk
Explains the deterministic scan-and-decision workflow, the nine drift dimensions, and the Production Drift Ratio; the site also provides a scanner for trying AI-generated frontend code.
Related talks
- BDD, ADR, PRD, WTF: Capturing Decisions for Humans and AI Alike — Michal Cichra, Safe Intelligence
Extends the deterministic-guardrail idea with architecture records, executable behavior specifications, import linters, Git hooks, and CI checks.
- Guide, Verify, Solve: The Engineering Discipline Agentic Development Demands
Develops a complementary workflow for verifying agent-generated code through automated checks and quality gates rather than trusting generation speed.
- The Z/L Continuum: Should AI Engineers Still Read Code?
Explores the same oversight question raised by the `innerHTML` incident: when to inspect generated code directly and when system-level verification can carry more of the burden.
Read the complete timestamped transcript
- 0:01
[music]
- 0:12
Hello everyone. I'm Jonathan Gordon. I'm
- 0:16
a founder of Reweaver AAI, a new
- 0:18
company, you know, on the scene, let's
- 0:20
say. I want to share one thing with all
- 0:21
of you that was really fascinating. So,
- 0:23
I I plugged in my laptop and I realized
- 0:27
I had to mirror. So, I no longer have my
- 0:29
speaker notes. So, I went into Claude
- 0:31
and I said, "Can you extract my speaker
- 0:33
notes from my slide deck, please?" And I
- 0:35
had my speaker notes now.
- 0:38
I love AI.
- 0:41
The suspense was killing me. I was
- 0:43
talking to Claude
- 0:45
now. Who knows if it got it right. I
- 0:46
don't know. Whatever. Um, so I also
- 0:49
realized that my title slide buried the
- 0:50
lead. I shouldn't have put it up. Um,
- 0:53
but nonetheless, let's play with this.
- 0:56
So, uh, yeah, my name is Jonathan. Um,
- 0:59
I'm here to talk to you about the design
- 1:00
code roundtrip that isn't.
- 1:04
And I guess probably the best thing to
- 1:06
do first is to explain what I think a
- 1:09
design code roundtrip should be. Um the
- 1:13
design code roundtrip is a full loop
- 1:17
between design and engineering in both
- 1:21
directions without any loss of fidelity
- 1:26
and with a persistent provenence. So it
- 1:28
knows exactly where everything came
- 1:30
from. You know that perfect dream world
- 1:33
that we live in where there is no drift
- 1:37
in between the gaps of design and code.
- 1:42
Um, today's tools, design is amazing.
- 1:45
It's incredible. It's magic. It's I ask
- 1:47
for something, I get it. It's clickable.
- 1:49
It's interactive. It's amazing to me.
- 1:52
But nobody really looks at the code
- 1:54
anymore, it seems. And so, I kind of
- 1:57
want to go there. I want to go into that
- 1:58
space.
- 2:00
Whoops. Of course, I have to get my
- 2:02
mouse to the right location. There we
- 2:04
go. Um, a little bit about me.
- 2:07
past 30 plus years um I've been building
- 2:10
and designing coding tools developer
- 2:13
tools idees at these companies um so
- 2:18
I've spent a lot of time with as a
- 2:20
designer I've spent a lot of time with
- 2:22
design and engineering teams trying to
- 2:24
understand
- 2:26
how do we do that handoff well how do we
- 2:28
hand off from design to code how do we
- 2:31
get what we wanted to be delivered to
- 2:33
the customer um it was never a perfect
- 2:36
science We never got it. We never found
- 2:39
that magic sauce that just made
- 2:42
everything come together where intent
- 2:45
matched the outcome.
- 2:47
Um, but I developed techniques. I
- 2:50
negotiated with engineers. I brought
- 2:52
them out for drinks. I made them my
- 2:53
friends. Um, I got things delivered to
- 2:57
customers.
- 2:58
But the the loop was never closed. Um,
- 3:01
and it's because our outcomes diverged.
- 3:04
engineering had one set of requirements,
- 3:07
technical constraints, design had a
- 3:09
vision for the future, a new rebranding,
- 3:11
whatever. So, this has existed, you
- 3:14
know, dare I say, for decades.
- 3:16
Um, then along comes AI
- 3:21
and LLM and prompting ourself into a
- 3:24
fully running application. In a sense,
- 3:28
now we have one intelligence that
- 3:30
understands design intent and the same
- 3:33
intel in intelligence can write code. So
- 3:37
I thought to myself, oh my god, I think
- 3:39
we might be able to close this loop. At
- 3:42
the speed of inference, we could close
- 3:43
this loop. And so I was curious. Um, I'm
- 3:48
curious by nature. So I went all in.
- 3:52
That's my GitHub before vibe coding
- 3:55
happened on the left on on my left on
- 3:58
your whatever. Um then after so I think
- 4:03
everybody probably gets a sense of what
- 4:05
my life was like from April 2025. And if
- 4:08
you want to scroll till today it's it's
- 4:11
even more so. Um, I got this email from
- 4:14
cursor one day that said I was in the
- 4:16
top 0.1%
- 4:18
of usage of cursor
- 4:21
and I thought to myself, I need to spend
- 4:23
more time outside.
- 4:28
Then there was a bill. Um,
- 4:31
but at the time it was the $20 deal and
- 4:33
I kind of, you know, monitored, but
- 4:35
every now and again I'd pay for a little
- 4:37
bit more, get another hit. Um,
- 4:41
and this was my life vibe coding from
- 4:44
that point in April
- 4:46
until today. Um, I'm trying to figure
- 4:50
out can I go from design to code? Can I
- 4:52
go from code to design? Can I build a
- 4:54
tool to go from design to code and code
- 4:56
to design a full round trip without any
- 5:00
loss of fidelity? That pixel perfect
- 5:02
dream that we have. Um, I remember
- 5:06
vividly uh one day I was, you know, just
- 5:10
hammering away at the keyboard, just
- 5:12
vibing my way. I was really feeling the
- 5:14
vibe. And, uh, this wall of text was
- 5:18
coming by and I was completely ignoring
- 5:19
it and code was being written, just
- 5:22
watching that come by. And I remember
- 5:25
seeing a statement that was an inner
- 5:27
HTML statement.
- 5:29
And I remember from way back when that
- 5:33
inter HTML was a security vulnerability
- 5:35
that people can actually inject into in
- 5:37
HTML and I stopped it. I said, "Wait a
- 5:40
minute, wait a minute." to my LM, "Wait
- 5:42
a minute, what did you just do?" And it
- 5:45
explained to me what it did and it was
- 5:46
very proud of itself. And and I said,
- 5:49
"Revert that. Do this instead." Blah
- 5:50
blah. And I got into this mode of like,
- 5:53
"Oh, maybe I need to steer this thing a
- 5:55
little bit better. Maybe I can't just go
- 5:56
blindly in. Maybe I need to look at the
- 5:58
code now.
- 6:00
And I've looked at a lot of code in my
- 6:01
life. So I went ahead and went in and
- 6:03
looked at the code and I Whoops. I'm
- 6:07
sorry. I clicked too ahead and I found I
- 6:10
found issues. And so I went a little bit
- 6:12
deeper
- 6:14
when the industry started to tell me
- 6:17
that they had solved the round trip
- 6:20
that you could go a true roundtrip
- 6:23
workflow. You could roundtrip between
- 6:25
code and canvas. I think folks in the
- 6:27
room might remember back in February,
- 6:29
no slam on anthropic or Figma, there was
- 6:33
this demo that showed going from cloud
- 6:36
code into Figma. And it was magic. It
- 6:39
was incredible. I couldn't believe you
- 6:40
could build a Figma artboard from a
- 6:43
prompt in Cloud Code. And then I had to
- 6:46
go deeper and I had to look deeper in
- 6:47
the same way that I looked at vibe
- 6:49
coding. Like, is this real? Is the hype
- 6:50
real? So I went deeper and then more
- 6:53
announcements were made all the way up
- 6:55
until last week when Figma config
- 6:57
announced that code is now material.
- 7:00
Does that mean there is no even handoff
- 7:03
that exists anymore? Um so I'm
- 7:06
monitoring trying to keep up. Things are
- 7:08
happening at warp speed.
- 7:11
But they said the roundtrip was solved
- 7:13
and I started messing around and
- 7:16
realized it wasn't. And so I want to
- 7:18
share with all of you
- 7:21
a harness that I built. Whoops. Oh, wait
- 7:24
a minute. Local host, where are you?
- 7:27
Local host,
- 7:29
come back to me, local host. Okay.
- 7:33
I don't know what I don't know what just
- 7:34
happened there. And now I'm afraid to
- 7:36
restart this. Um, okay. I think we're I
- 7:38
think we're okay. Um, I created this
- 7:40
harness. And what this harness is is on.
- 7:44
I'm going to say left. I hope everybody
- 7:46
is that your left. It is your left.
- 7:48
Okay, good. [laughter]
- 7:50
On your left is code that was generated
- 7:52
by AI. This is this is all real what
- 7:54
you're seeing here. Generated by AI and
- 7:58
on your right is a design. Be it a
- 8:02
canvas that that I created in Figma, be
- 8:04
it something I created in Sketch. It's
- 8:06
not really relevant what the sources are
- 8:09
here, but the reality is I'm trying to
- 8:11
illustrate a round trip. And so a round
- 8:14
trip you know starts with code or starts
- 8:16
with design and it has a prompt
- 8:18
associated with it. So some some LLM I
- 8:22
call off and I say in this instance I
- 8:24
want to take this form and I want to
- 8:26
build a design system from it. So there
- 8:27
there are tools that do this that can
- 8:29
extract code and build design systems
- 8:31
from graphical canvases. And so I can do
- 8:35
that. And it updated the code and
- 8:38
created some styles. And it also
- 8:40
actually created um a design system that
- 8:43
works in runtime here. So this is like a
- 8:45
a real app that got built that is also
- 8:48
living in Figma. So there's a link up
- 8:50
here. I won't go there, but trust me, so
- 8:53
we can say stable. If I click that link,
- 8:55
it would go to Figma and show me the
- 8:56
full-blown design system that was built.
- 8:58
And a design system for those that don't
- 9:00
know is composed of components and
- 9:03
tokens and variables and styles that all
- 9:07
are used as a basis for building
- 9:09
software from. So code and design
- 9:11
together, you know, really work well
- 9:13
when there's a design system and there's
- 9:15
a code base that understands it. Now
- 9:18
move back and forth. You throw something
- 9:20
over here and you say, "Okay, I want to
- 9:21
build an orange button." And I've added
- 9:24
a company field and an orange button.
- 9:26
The code is updated. The design is
- 9:27
updated. This is awesome. Could I go
- 9:30
back? Maybe. Um, but I have a button up
- 9:33
here called show drift.
- 9:35
So, show drift is rewaver AI working
- 9:39
right now. And this is real rewaver code
- 9:42
for the first time introduced to the
- 9:44
public ever. And if I click show drift,
- 9:48
I'll see a list of issues that got
- 9:49
generated from both the code and the
- 9:52
design at the same time. There are
- 9:55
across several different dimensions that
- 9:57
you can see here. Design quality, code
- 9:59
quality, performance, design tokens,
- 10:02
etc. One of the ones of note that I find
- 10:05
really important from my perspective is
- 10:07
at Microsoft I worked on accessibility
- 10:11
and I learned a lot about what it means
- 10:12
to build an accessible software system.
- 10:15
And I I want to be honest with all of
- 10:17
you. I was very frustrated when I first
- 10:18
saw LMS come out and they generated code
- 10:20
that was inaccessible period out of the
- 10:22
box. I thought what models weren't
- 10:25
trained on accessibility.
- 10:27
Um, and I was reminded 20 years ago when
- 10:31
you know engineers needed to be trained
- 10:32
on accessibility. So here we are again
- 10:34
now training LLMs instead of engineers
- 10:37
on accessibility.
- 10:39
So found issues. Um, here's an issue
- 10:42
where
- 10:44
has no Arya live region. So it won't be
- 10:47
announced by screen reader. A blind user
- 10:49
using this won't get an announcement
- 10:50
about this element. So Rewaver found
- 10:53
that and Rewaver says it can fix it and
- 10:57
Rewaver fixed it. Now the red went away,
- 10:58
but there's also a blue issue here as
- 11:00
well. Um so Rewaver stacks up issues and
- 11:04
you know basically scans scans the code
- 11:06
and scans the design and produces u
- 11:10
guard rails to a sense but also a way to
- 11:12
fix the code and make it better.
- 11:16
So I did that across multiple dimensions
- 11:18
um you know with the intention of seeing
- 11:21
if anybody had solved the drown the the
- 11:23
roundtrip problem
- 11:25
and it didn't go well. Uh I never got
- 11:29
really the full round trip. So I really
- 11:31
tried hopefully this slide tells you I
- 11:33
tried five different tool setups trying
- 11:36
to do code design code roundtrip both
- 11:39
directions birectional
- 11:41
lots of lossy issues uh you know
- 11:45
bindings were lost um design change
- 11:48
survived but code didn't
- 11:50
I'm not going to say we're not going to
- 11:52
get there um but even if we do get there
- 11:55
and we're able to do this I wonder if
- 11:58
we'll get fully there And maybe we need
- 12:01
tools like Reweaver. I shouldn't say
- 12:03
maybe, we do need tools like Reweaver to
- 12:06
help us understand the drift.
- 12:10
So that whole experience for me really
- 12:12
highlighted something from my past. Um I
- 12:15
had I had built a lot of software
- 12:16
development tools, designed and built
- 12:18
software development tools and developer
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tools in their nature are deterministic.
- 12:24
You write code, you compile it, you get
- 12:26
an SA a it it'll every time you run that
- 12:29
code, you'll get the same result. When
- 12:31
you put AI in the middle of that or in
- 12:33
the front of that or the end of that,
- 12:35
you're not going to necessarily get the
- 12:37
same outcomes. Now, there are tools that
- 12:40
will help you understand, rewaver being
- 12:41
one of them, that there's a mismatch.
- 12:43
There's drift there and we need to be
- 12:46
aware of drift. Drift lurks in the dark.
- 12:50
You need to look at the code. You need
- 12:51
to find the drift. You need to fix the
- 12:52
drift. And you do that with
- 12:54
deterministic guardrails around the AI.
- 12:57
The AI is still there. So I ran another
- 13:00
experiment, 12 iterations on a codebase
- 13:03
with complex enough UI to it. And I did
- 13:06
one where it was just pure AIE, just LLM
- 13:09
all the way. And it degraded a little.
- 13:11
It degraded a little bit, but it started
- 13:14
at 30% quality, 30% fidelity, 30%, you
- 13:18
know, true pixel perfection.
- 13:20
And then I put it on top of
- 13:22
deterministic guardrails where we found
- 13:24
the issues, we fixed the issues. You
- 13:27
can't get to a hundred because that 10%
- 13:30
is human judgment, human
- 13:33
decision-making. So the human is still
- 13:35
there in this equation.
- 13:38
Um,
- 13:40
so what is it today? Uh, today I I would
- 13:44
call it we're locked into AI. And that's
- 13:46
okay. We'll go there. We'll embrace
- 13:47
that. But we're locked into AI for
- 13:50
design to code. We're locked into AI for
- 13:52
code to design, looping, chat bots, what
- 13:55
we call span the chain workflows where
- 13:57
you jumping across tools. And there's
- 13:59
always token costs to be aware of, of
- 14:01
course. So in this world, the agents are
- 14:04
in control and the humans in the loop.
- 14:06
I'd like to propose something else.
- 14:08
Before I do, there are three blind spots
- 14:10
we need to be aware of. One is the model
- 14:12
itself. It's going to you can ask it
- 14:14
questions. It'll give you answers, but
- 14:16
it's nondeterministic. It's
- 14:18
probabilistic.
- 14:19
There will be drift in the moment when
- 14:21
you're writing code. Drift will surface,
- 14:23
but drift over time is the pain that
- 14:26
you'll be experiencing for the next six
- 14:28
months because drift over time is the
- 14:31
new tech debt and it's going to pile
- 14:34
itself
- 14:36
gloriously over your codebase. Um, we
- 14:40
want to do something about it. So here's
- 14:44
where we think it isn't meaning what it
- 14:47
could be what it should be fully
- 14:50
birectional
- 14:51
edit both ways lossless all surfaces
- 14:54
preserved so if you go from code to
- 14:56
design and design to code nothing's
- 14:58
breaking weirdly for you provenence is
- 15:00
carried where did this start from what
- 15:03
line of code wrote this button
- 15:07
I see this button in Figma I want to
- 15:09
change it I need to change that code or
- 15:11
Somebody needs to change that code. We
- 15:14
have to control the drift. It's
- 15:16
deterministic reconciliation at its
- 15:18
core. So with deterministic guardrails,
- 15:21
and I'm happy to talk after if folks are
- 15:24
interested in what I mean by that,
- 15:26
accept or refuse. So if they know
- 15:30
there's a fix, they will fix it. If they
- 15:32
don't know there's a fix, they will tell
- 15:34
you there's an issue, but you need to
- 15:36
fix it.
- 15:38
And with Ruby Weaver, there's zero extra
- 15:40
token costs. So, we're fully local LLM,
- 15:44
but if you want to open up Claude or
- 15:46
whatever and connect to us, you can. But
- 15:48
at its core, and our core principle is
- 15:50
the human is in control always. In
- 15:54
control of cost, in control of code, in
- 15:56
control of design, because that's what
- 15:58
we've been doing for decades.
- 16:01
We've been in control. We don't need to
- 16:03
lose control. And I'm not saying loop
- 16:05
isn't good, but human in control is I
- 16:07
think a little more aspirational
- 16:10
because at the end of the day, what you
- 16:12
need is actually what you get. I call it
- 16:16
winnywig. Can I use that winny wig?
- 16:20
So what are we building at its core?
- 16:22
What we're building are nine dimensions
- 16:25
of deterministic guardrails.
- 16:28
Inside of this is a lot of stuff, but
- 16:30
these are our top level um software
- 16:33
quality, software production readiness
- 16:35
dimensions. Design consistency being
- 16:38
core. Of course, when you have a design
- 16:40
system and the code isn't consistent
- 16:41
with it and vice versa, we need to fix
- 16:44
that. So, there's a lot of design
- 16:45
consistency
- 16:47
um work that's going into the the
- 16:49
foundation. Accessibility is its own
- 16:52
dimension. um maybe selfish of me but I
- 16:55
think it's core
- 16:57
uh AI code generation too or AI code
- 17:00
sorry governance AI code generation
- 17:02
governance is another really critical
- 17:04
piece because the code is just flying
- 17:06
through the system and we need to govern
- 17:08
that code now we're not going to change
- 17:10
the code rewaver actually doesn't write
- 17:12
code you write code reweaver will do
- 17:16
what you want it to do so if you say
- 17:18
apply the fix it'll write the code for
- 17:20
you can see the code being written You
- 17:22
can say never mind undo. You can ignore
- 17:25
it. So at the end of the day, catch what
- 17:27
drifts in a closed loop before anything
- 17:30
merges. That's the goal.
- 17:33
You can try it out with your own code
- 17:34
today. Right now, you can go to reweaver
- 17:37
AIPplayground
- 17:38
and we built kind of a similar harness
- 17:40
to what I built there where you can put
- 17:42
your AI generated code on the left on
- 17:45
the left. You can scan it and get your
- 17:48
results for that code. There's also a
- 17:51
fun little challenge on that page. If
- 17:53
you can get AI to generate code that
- 17:56
gives you a score lower than30
- 17:59
PDR,
- 18:01
which is production drift ratio, will
- 18:03
get you a frontline seat on the beta,
- 18:06
but you'll also get yourself showcased
- 18:08
at the bottom on the crawl. So, give it
- 18:10
a shot. Take a look. Um, meanwhile, I'm
- 18:14
looking for people to join our beta.
- 18:15
We're going to basically blast out mid
- 18:18
July hopefully.
- 18:20
Um so would love for you to join if
- 18:22
you're interested um to make the product
- 18:24
better to sanity check us. Um basically
- 18:28
that's it and you can also reach me
- 18:31
online or outside happy to talk more.
- 18:34
Thank you.