How ButtonShift Is Solving the Creative Chaos in Hybrid Workflows

In an age where creative teams are expected to deliver faster, better, and across multiple channels, the tools meant to empower them often end up slowing them down. Most project management platforms were built for engineering or operations—not for the fluid, iterative, and often messy nature of creative work. Enter ButtonShift—a purpose-driven platform designed to remove chaos from creative collaboration. By bringing feedback, workflows, and approvals together in one place, ButtonShift aims to restore what truly matters: creativity.

In an exclusive interaction with CiOL, Deepankar Das, co-founder and CEO of ButtonShift, shares insights on the evolving landscape of creative collaboration, the future of AI in creative workflows, and how ButtonShift is redefining productivity for modern teams. 

Interview Excerpts Below:

What is the single most persistent operational problem creative teams face today that general project management tools fail to address—and how have you seen this evolve with hybrid work?

General project management tools are great but are meant for geeks and not creative teams. It’s important to simply understand the difference between project status and asset status. It’s great to be managing tasks, dependencies & deadlines, but if you do not understand the evolving nature of a creative asset, then your project status is simply a manually keyed-in ‘static’ status not reflective of the actual dynamic status of the asset. And hybrid work has actually made the need for real-time asset state awareness an existential necessity. Let’s take, for example, an Insta reel being reviewed and tweaked till it takes final shape. The lack of a unified source of truth for the asset state means teams default to sharing via Slack attachments, email, or cloud folder links, creating a massive version control sprawl.  And top this up with each version having its own set of feedback and comments from various stakeholders, which again have to be dealt with using WhatsApp, email threads and/or document notes. This chaos is what general PM tools, designed only for managing linear tasks, simply cannot track or resolve.

What creative teams need is a simple tool where assets change hands with a click of a button, versions are automatically measured and traceable, and a tool where articulating and understanding feedback isn’t a drain of one’s mindspace but seamless & smooth; a tool where project management is minimal in nature, letting the creative brains be creative instead of uncomfortably attempting to be geeks in setting things up.

Managing high-resolution media at scale is a known bottleneck for creative platforms. How do you see the industry balancing storage costs, latency, and fidelity over the next 3–5 years?

This can be a problem but not as significant as for streaming platforms. The need for high fidelity mostly arises once an asset has seen through the most difficult phase, which is reviews, feedback and approvals. So, the solutions have to be fidelity on demand; for example, a user may work on a lower-fidelity version for most parts of the workflow and only burst to the full-fidelity file for final review and export.  As far as balancing storage costs, latency and fidelity are concerned, solutions will have to be modelled around AI and the cloud-edge continuum, where the core strategy will be to work with compression to maintain user experience and reserve high-cost, high-fidelity only for critical needs.

With creative teams relying on tools like Adobe, Figma, and Slack, what does the industry need—deep, bi-directional integrations or a more unified standard? What lessons have emerged from failed integrations?

 I think it depends on the purpose here. Bi-directional integrations will be critical for real-time collaboration and consistency of information, but I feel it also creates power centres and a monopoly. A unified standard allows any tool, regardless of the provider, to easily plug into a centralised workflow. It is more democratic and gives an opportunity to startups to create specialised tools that can reliably interact with industry giants like Adobe and Figma. And if we were to take lessons from failed integrations, take Adobe and Figma, for example, the failure reinforces the value of Figma's independence in pushing the boundaries of collaborative design. It is a reminder that the industry benefits from a diverse, competitive tool ecosystem that must communicate via open, reliable APIs.

Generative AI is entering every stage of creative production. Which parts of the workflow are most likely to be automated, and where should humans always remain in control?

Generative AI is possibly reshaping the creative production workflow, primarily by automating the repetitive, high-volume, and time-consuming aspects. It does enhance efficiency and helps scale content creation, but let me ask one question: Would something be creative if it were repetitive? Wouldn’t it be called monotonous then?

Human creativity is driven by emotion, intuition, and lived experience, and AI models lack a purpose or the ability to define the purpose of a ‘creative asset’, let alone associate it with a long-term mission, keeping cultural goals or emotional resonance in mind. Take, for example, a creative director can use generative AI to make a film, but he needs to be creative at first. It’s not the other way around. This is where the distinction will be created. So, I think while AI solves some problems for us, we humans must define the right problem for it to solve.

In a distributed, freelancer-driven ecosystem, how should platforms enforce licensing rights, provenance, and compliance without slowing down creativity?

Unable to answer this in detail, but my short take is not to make any of it a separate administrative hurdle; instead, embed licensing/compliance into processes so that they blend into creative workflows.

When enterprises adopt creative workflow platforms, which metrics truly reflect ROI—time saved, reduced rework, faster approvals, or something else? Where is the disconnect between buyers’ KPIs and creators’ needs?

From an ROI perspective, yes to time saved, reduced rework, faster approvals, all of them. However, to understand this better, one needs to look at creative scaling differently from any other mathematical scaling. Creative minds cannot be multiplied, unlike products. So, for creativity to scale, the creative mind needs to free up. And for that to happen, the creative workflow needs to exist without getting in the way.

To enterprises, ROI matters, as do time saved, reduced rework, etc., which are direct measurable results of using creative workflow platforms like ButtonShift. However, the significant yield comes from increased ‘creative’ mindspace that impacts the quality of assets produced. There are cases where teams have witnessed a 200% jump in productivity of video editors after using ButtonShift, but to me, the real gain is in the quality of creative assets going up, the stuff that actually makes a customer click or keeps a client happy. So, if your creative workflow platform is helping you by getting out of your way, you are in for gaining much more than ROI.

Looking at the next wave of digital-first enterprises, what structural changes—skills, tools, or business models—will creative teams need to stay efficient and competitive in an AI-driven economy?

In simple terms, I see the future in creative teams making a subtle shift from ‘making’ to ‘directing’. I definitely see a shift required from isolated tools to integrated tools with an AI stack, because the critical skills are no longer technical proficiency with a single tool, but rather the abilities that AI cannot replicate, things like creative judgement & curation, conceptualisation, etc.

Many businesses will still need human-generated assets, but most will simply need strategic consulting instead of production. Just like prompt engineers now, maybe we’ll see creative strategists (humans) supported by AI soon. So, the most competitive creative teams will aggressively adopt AI for automation and augmentation, freeing up human capacity for non-replicable tasks.