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Vitalii Khomenko argues that AI-assisted engineering can shift the bottleneck in product development: when implementation speeds up, the work of translating a finished Figma design into code may become the part teams wait on. His proposed answer is not to abandon Figma, but to use it for visual exploration and make code-based components the final delivery artifact. That is his experience-based argument, not a measured finding that applies to every product team.
Why Khomenko says the design handoff is becoming a bottleneck
In an October 2, 2026, opinion article for SitePoint, Khomenko describes a familiar sequence: designers develop polished screens in Figma, then engineers interpret those screens and recreate their decisions in code. He argues that this handoff made more sense when implementation took longer. If AI-assisted engineering accelerates implementation, the visual-to-code interpretation step can become a new source of delay.
Khomenko puts it this way: “The design handoff is quietly becoming the thing everyone is waiting on.” He also says, “The manual workflow inside Figma simply isn’t keeping up with AI-boosted engineering.” These are his observations, not conclusions supported in the article by measured handoff times, a before-and-after study, or comparative data across teams. The diagnosis is most relevant to teams whose engineering work has sped up while their design and handoff process has not.
What workflow Khomenko proposes instead
Use Figma to explore
Figma still has a role in Khomenko’s proposal. He sees it as the place to establish visual direction, explore layout, and decide what a product should look and feel like. His distinction is between using a design tool to explore and treating a completed file as the final implementation specification.
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Deliver implementation-ready components
For delivery, he recommends code-based components, ideally organized in prepared libraries that engineering can build from directly. The goal is to reduce the extra interpretation and recreation between a settled design decision and its implementation. Khomenko summarizes the change as: “Figma is still the right place to explore what something should look and feel like,” but “handing over a Figma file and asking engineering to implement it is now the slow path. Delivering in code is the fast path.”
This is a proposed direction, not proof that code delivery is always faster. A component library has to fit the product’s engineering stack, remain maintainable, and preserve the intended design. If a team lacks the skills or infrastructure to build and maintain such components, adding code delivery could create work rather than remove it.
What founders and product leads can change
Khomenko’s recommendations focus on when design judgment enters the process and what teams expect at handoff:
- Bring experienced design judgment into problem definition. Involve senior designers early enough to shape the problem, rather than asking them only to polish a solution after key decisions have been made.
- Separate exploration from delivery. Agree on when the team is exploring visual possibilities and when it is preparing implementation-ready work.
- Set a clear handoff expectation. Where it fits the team’s capabilities, make code-ready components part of delivery rather than assuming engineering will recreate every design decision from a Figma file.
- Keep the broader creative remit visible. Khomenko does not say design should become code generation. Brand, motion, and marketing work remain part of the creative role alongside design engineering.
- Adapt the process to the team. He says, “Each team’s workflow is really custom at this stage.” His article describes an evolving practice, not a standardized playbook.
How to judge whether this shift fits your team
Khomenko’s article does not compare products or report results from competing workflows. Teams considering a change can evaluate their own process against a few practical questions:
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- Is the delay actually in translating design decisions, or elsewhere in review, prioritization, implementation, or approval?
- Would code-based delivery reduce interpretation, or simply move work earlier in the process?
- Can the engineering stack support reusable components that designers and engineers can review together?
- How will the team check that implementation preserves visual quality, interaction, and brand intent?
- Who will maintain the components as the product and its tools change?
These questions help distinguish a handoff problem from a broader delivery problem. If the team cannot identify translation as a meaningful source of delay, changing the artifact alone may not address the cause.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What Khomenko’s argument does—and does not—establish
SitePoint identifies Khomenko as Principal Designer at Orizon Design and founder of Fluente LLC, and reports more than 250 client engagements across agency and embedded in-house work. That engagement count is presented as biographical information; the article does not provide underlying data for it. His experience informs the argument, but it does not make the proposed workflow a universal rule.
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The article’s central case is narrower: where AI-assisted engineering has made implementation faster, teams may need to reconsider the time and effort spent interpreting and rebuilding design files. Figma remains useful for visual exploration; code-based delivery is Khomenko’s suggested response for the implementation stage. He does not claim that all engineering is now fast, that every team needs the same process, or that visual design should be replaced by coding.
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