Q: What role do you expect AI to play in the future of work, and how is Cody capitalizing on this technology to streamline processes?

MV: The definition of AI has shifted. Automation technology has existed for centuries, but the narrative changed when we started automating cognitive tasks rather than just mechanical ones. The launch of ChatGPT popularized Large Language Models (LLMs) and created immense market hype because it automated everyday tasks in a highly intuitive way. However, true automation is only viable if it is economically sustainable. Large language models require massive amounts of energy to process transactions, which translates into high token costs for computing power, server maintenance, and cooling. If an organization blindly routes every layer of its automation through an LLM due to market hype, the solution will ultimately become more expensive than manual execution. 

Cody resolves this by looking at automation through a strict business lens. We leverage context engineering, prompt engineering, and software architecture to deploy Small Language Models (SLMs). These smaller, targeted text models automate the correct layers of a workflow with the right context, delivering the same experimental value as an LLM but at a fraction of the operating cost. This allows enterprise clients to effectively scale automated workflows.

Q: Frontline workers in sectors like retail, consumer goods, and field operations face unique operational opportunities. What are the primary challenges they encounter today, and how is Cody helping to solve them?

MV: The biggest hurdle for frontline workers is cognitive overload and friction in accessing actionable information. As companies digitalize their back offices, the frontline employee — who must make split-second decisions directly in front of the customer — is often inundated with shifting promotions, personalized offers, and fragmented platform interfaces. They do not have the luxury of sitting at a desk to search through a system. This information asymmetry is worsening because consumers now have mass access to generative AI tools, meaning a customer often enters a store more researched than the sales representative. This creates an uneven, frustrating dynamic for both parties.

Furthermore, frontline workers operate in isolation compared to back-office staff. A developer or an accountant can easily consult a peer or manager when a doubt arises, but a frontline worker cannot halt an operation to ask for coaching. This directly impacts business outcomes and leads to lost opportunities. Cody addresses this by serving as an intelligent, real-time companion. It simplifies data processing and provides workers with the exact operational context they need, giving them the execution confidence required to excel. Our approach is not about absolute human replacement. Physical touchpoints and human relationships remain vital in retail and consumer goods. By eliminating the burden of technical memorization through automated support agents, we allow workers to focus on what matters most: personalizing the customer experience.

AB: We firmly believe that technology is not a tool for absolute replacement, especially for frontline teams. These workers are the face of the brand; the physical world is not going away, and consumers still want a human relationship with the brand in retail and CPG settings. There is an opportunity for organizations to change management practices. We need to communicate that this is an opportunity to increase productivity, not a threat to their jobs. That fear severely bottlenecks technology adoption.

The frontline worker receives a constant stream of complex data and instructions without the benefit of a desk or computer to look things up. When we eliminate that initial friction and anxiety, that is where the magic happens. They begin to see how the technology supports them, lowers their cognitive load, and elevates their performance.

Q: Many organizations struggle to integrate these new technological tools effectively. Where are companies going wrong, and what sets Cody's onboarding and implementation strategy apart from the competition?

MV: The companies struggling or failing today are typically those just starting out who get frustrated by initial mistakes and abandon the process entirely. Missteps are a natural part of technological evolution. The organizations seeing success now are the ones that began experimenting and making mistakes back in 2022 when tools like ChatGPT first emerged, or even earlier with initial NLP models. Anxiety arises when leaders see technology moving at an accelerated pace and choose to retreat to the status quo instead of pushing through the learning curve.

AB: Many companies spend heavily on remote, asynchronous training platforms or rigid LMS setups, but that learning is not effective because it lacks practical execution. The best way for training to stick is by grounding it in real-world cases with constant on-the-job support. Furthermore, corporate training has historically been entirely technical. In this new era, technical tasks will be increasingly automated, which means corporate investment needs to pivot toward developing soft skills, like relationship building, communication, and adaptability.

MV: Because of high turnover rates on the frontline, corporate education is too often treated as an expense rather than a forward-looking investment, since the return is lost when an employee leaves. This is where Cody changes the paradigm through intelligent agents. By embedding contextual training into digital agents that interact with the workers, the technology itself absorbs the workflow data and operational intelligence. Since the software never resigns, that knowledge remains a permanent organizational asset, creating a highly efficient, bidirectional learning environment between human teams and AI.

Q: Looking ahead, what are Cody's main priorities, upcoming projects, or strategic objectives for the remainder of this year? How will you measure success for 2026?

AB: We already achieved many milestones in 2026. Beyond standard growth metrics, success is measured by the deep trust our enterprise clients are placing in us as we become the core engine orchestrating their frontline workflows. Our immediate focus is continuing down this path, expanding our product features to make AI adoption even more seamless and allowing companies to design and scale their own use cases with minimal configuration costs or specialized technical barriers. Our goal is to consolidate our leadership in Latin America and establish our expansion into the US market.

MV: Having built a stable and robust operation with a loyal client base, we see a massive opportunity to globalize what we have built. To fuel this next phase of international expansion, we are structuring a capital raise. Securing the right investment partners will allow us to take this cutting-edge operational platform, proudly developed in Mexico, to enterprise markets worldwide.