In an era where artificial intelligence is reshaping every facet of technology, the conversation often gravitates toward algorithms, data pipelines, and autonomous systems. Yet beneath the surface of these rapid advancements lies a fundamental truth: technology thrives when it remains anchored to human experience. Developers, network engineers, and IT professionals are not just consumers of innovation; they are the practitioners who translate abstract capabilities into tangible outcomes for businesses and end‑users. Recognizing this, forward‑thinking organizations are placing renewed emphasis on capturing the nuanced perspectives of those who work with the tools daily. Market research indicates that companies that actively integrate user feedback into their development cycles see higher adoption rates, reduced churn, and faster time‑to‑market for new features. By creating deliberate spaces for dialogue, firms can uncover hidden pain points, validate assumptions, and inspire solutions that resonate on a practical level. This human‑centric approach does not diminish the power of AI; rather, it amplifies it by ensuring that intelligent systems are built to solve real problems faced by real people. As we explore Cisco’s Share Your Experience initiative, we will see how a structured yet flexible feedback mechanism can bridge the gap between cutting‑edge technology and the everyday realities of the developer community.
Share Your Experience (SYE) represents more than a conventional survey or a digital feedback form; it is a purpose‑built, interactive program that lives at the heart of Cisco’s major conferences. Designed around the principles of design thinking, SYE invites developers, customers, and Cisco specialists to engage in hands‑on activities that reveal genuine insights about current challenges and future aspirations. The initiative moves beyond passive data collection by creating a tactile environment where participants can physically manipulate ideas, vote on priorities, and co‑create potential solutions. Facilitators drawn from user research, developer advocacy, and product engineering guide the sessions, ensuring that conversations remain focused, inclusive, and actionable. By embedding SYE within the bustling conference floor, Cisco leverages the natural energy and concentration of attendees who are already immersed in learning and networking. This setting transforms what could be a routine feedback exercise into a vibrant exchange of stories, sketches, and sticky‑note votes that collectively paint a picture of the community’s collective voice. The ultimate goal is to shift the paradigm from “building for users” to “building with users,” thereby increasing the relevance and impact of Cisco’s technology roadmap.
Picture the DevNet Zone at Cisco Live: amid flashing screens, demo stations, and bustling crowds, a quieter corner emerges where the rhythm slows just enough for meaningful conversation. Here, attendees are invited to jot down their thoughts on small sticky notes and place them on a visual board, using colored dots to indicate their level of agreement or preference. Each note and each dot is a discrete data point, but together they form a mosaic that reflects the varied experiences of network programmability practitioners, API designers, and automation enthusiasts. The physical act of writing and placing a sticky note engages a different cognitive process than typing into an online form; it encourages reflection, reduces distraction, and often leads to more candid expressions of frustration or excitement. Moreover, the public nature of the board—while maintaining anonymity of individual contributors—creates a subtle social proof effect. When participants see clusters of agreement around a particular topic, they gain confidence that their concerns are shared, not isolated. This visual validation can be especially powerful for individuals who have previously felt like outliers in their organizations. The tactile interaction also serves as an icebreaker, sparking spontaneous conversations between strangers who discover common ground through the notes they have placed.
One memorable moment from a past SYE session illustrates the profound human impact of this approach. A network engineer approached the facilitator after placing her vote on a board that measured confidence in using new automation tools. She confessed that, for months, she had believed she was the only one struggling with a particular integration pattern, feeling embarrassed to ask for help in her team meetings. When she saw a dense cluster of voting dots surrounding the same concern, her expression shifted from apprehension to relief. “I don’t feel as lonely anymore,” she remarked, noting that simply observing the collective acknowledgment normalized her experience and gave her the courage to seek guidance. Stories like this underscore a critical benefit of SYE: it transforms abstract feedback into emotional reassurance. By making invisible struggles visible, the initiative fosters a sense of belonging within the broader developer community. This emotional resonance is not a peripheral side effect; it directly influences engagement levels, knowledge sharing, and the willingness to experiment with new technologies. When engineers feel seen and validated, they are more likely to invest time in learning, to share best practices, and to advocate for the adoption of tools that genuinely improve their workflows.
The empathy cultivated through SYE operates on a reciprocal loop. While Cisco gains deep insights into the real‑world challenges faced by its users, participants simultaneously benefit from exposure to diverse perspectives and expertise. As they walk through empathy‑mapping exercises, prototype‑building games, or card‑ranking activities, developers encounter the thought processes of product managers, designers, and fellow engineers from different geographic regions and industry verticals. This cross‑pollination of ideas often sparks inspiration that participants can bring back to their own projects. For instance, a developer struggling with API versioning might learn about a novel deprecation strategy employed by another team, while a network architect could discover a simplified monitoring dashboard concept that originated in a completely different product line. The collaborative atmosphere also lowers hierarchical barriers; senior engineers find themselves listening to newcomers, and vice‑versa, creating a culture where every voice carries weight. By the end of a SYE session, attendees frequently report not only having contributed valuable feedback but also having gained new skills, fresh perspectives, and a renewed sense of motivation. This win‑win dynamic reinforces the value of investing in human‑centric feedback mechanisms, showing that the time spent in facilitated dialogue yields dividends for both the organization and its community.
The insights harvested from SYE do not remain confined to the conference walls; they flow directly into Cisco’s product development pipeline. Product managers, engineering leads, and designers from teams spanning Meraki, Catalyst Center, ACI, Nexus Dashboard, and Crosswork Network Controller staff the SYE booths, ensuring that the feedback they hear is immediately contextualized within their respective domains. After each event, the aggregated notes, voting patterns, and qualitative observations are synthesized into reports that are shared with the broader portfolio. These reports influence concrete decisions such as feature prioritization, user‑interface refinements, and the allocation of engineering capacity. For example, repeated feedback about inconsistent error messages across API endpoints prompted a dedicated initiative to standardize error‑handling conventions, resulting in a more predictable developer experience. Similarly, requests for richer sandbox environments led to the expansion of devnet‑hosted labs that now offer pre‑configured topologies for rapid prototyping. By closing the loop between community input and product action, Cisco demonstrates a commitment to continuous improvement that is grounded in empirical evidence rather than speculation. This approach not only enhances product quality but also builds trust, as users see their suggestions materialize into tangible upgrades.
Historically, a major focus of DevNet’s outreach has been the promotion of API‑driven automation as a successor to legacy CLI‑based workflows. Through countless SYE interactions, the team has gathered a wealth of data on where developers encounter friction in this transition. Common themes include API inconsistencies—such as differing parameter naming conventions across similar endpoints—which increase the cognitive load when building integrations. Error‑handling challenges also surface regularly, with developers reporting vague or missing error codes that complicate troubleshooting. Gaps in documentation, ranging from outdated examples to missing coverage of edge cases, further hinder adoption. Additionally, feature functionality sometimes lags behind user expectations; for instance, a webhook might lack the payload flexibility needed for a particular use case. By surfacing these issues in a structured, repeatable format, SYE enables product teams to quantify the impact of each pain point and address them systematically. The feedback has directly informed the creation of API style guides, versioning policies, and interactive documentation tools that aim to reduce ambiguity. Moreover, the iterative nature of SYE means that as improvements are rolled out, subsequent conferences provide fresh data to validate whether the changes have resolved the original concerns, establishing a virtuous cycle of refinement.
As the technological horizon shifts toward AI‑enhanced workflows, the developer community faces a new set of questions that echo the early days of API adoption. Many professionals acknowledge the potential of artificial intelligence to automate complex decision‑making, optimize network performance, and unlock predictive insights. Yet they also express uncertainty about where to begin, how to integrate AI models into existing automation scripts, and which tools or platforms can be trusted for production‑grade workloads. The transition from deterministic API calls to probabilistic AI inferences introduces nuances such as model drift, data provenance, and explainability—concepts that may lie outside the traditional skill set of a network engineer. Furthermore, the rapid proliferation of AI‑related offerings can lead to analysis paralysis, making it difficult to discern genuine value from hype. Recognizing these hesitations, DevNet has positioned SYE as a conduit for capturing the community’s evolving needs in real time. By asking targeted questions about AI use cases, desired levels of automation, and comfort with emerging paradigms like Model Context Protocol (MCP) servers and AI agents, the initiative seeks to map the landscape of readiness and resistance. The resulting insights will inform the creation of resources that lower the barrier to entry, ensuring that AI augmentation feels like a natural extension of existing workflows rather than an alien disruption.
Previous SYE cycles have already yielded concrete assets that developers can leverage today. One notable outcome is the Code Exchange AI repository, a curated collection of scripts, sample projects, and reference implementations that demonstrate how to invoke AI services within Cisco‑centric automation pipelines. These resources range from simple Python snippets that call a hosted language model for log analysis to more advanced examples that integrate computer vision APIs for visual inspection of network hardware. Complementing the code samples is the MCP server catalog, which enumerates trusted Model Context Protocol servers that expose AI capabilities through standardized interfaces. By providing a vetted list of endpoints, along with documentation on authentication, rate limiting, and data schemas, the catalog reduces the guesswork involved in selecting a reliable AI backend. Both assets emerged directly from recurring themes in SYE feedback: a desire for trustworthy, copy‑paste‑ready examples and a need for clarity on where to find dependable AI services. The iterative improvement of these resources continues as new feedback arrives, ensuring they stay aligned with the latest models, security best practices, and evolving developer preferences. In this way, SYE not only identifies gaps but also actively participates in filling them, creating a feedback loop that accelerates community enablement.
For the upcoming Cisco Live Las Vegas, the Share Your Experience booth has been upgraded to a hybrid tactile‑digital experience that preserves the beloved hands‑on elements while introducing a layer of gamified interactivity. Attendees will still find the familiar sticky‑note walls and voting boards, now complemented by touchscreen stations that present dynamic polls, scenario‑based quizzes, and drag‑and‑drop prototyping canvases. The gamification layer awards points for completed activities, which can be visualized on a leaderboard, fostering a friendly spirit of competition without sacrificing the collaborative ethos. This blend acknowledges that modern developers are accustomed to rich digital interfaces while still valuing the tangible, sensory engagement that physical artifacts provide. The digital components also enable real‑time aggregation of quantitative data, allowing facilitators to instantly spot trends and adjust the flow of conversation on the fly. Qualitative insights, meanwhile, continue to be captured through open‑ended sticky notes and facilitated discussions, preserving the depth that numbers alone cannot convey. By marrying the strengths of both modalities, the upgraded SYE aims to maximize participation richness, ensuring that every visitor—whether they prefer pen‑and‑paper or pixel‑based interaction—can contribute meaningfully to the dialogue.
At this year’s DevNet Zone, the conversation will zero in on three interconnected themes that are shaping the next generation of network automation: API quality, AI adoption, and integration strategies. Regarding API quality, participants will be invited to share specific instances where inconsistencies, insufficient error handling, or missing documentation impeded their projects, as well as to suggest concrete improvements that would make APIs more predictable and developer‑friendly. On the AI front, the booth seeks real‑world use cases—ranging from anomaly detection in traffic patterns to intelligent configuration recommendation engines—and wants to understand the hurdles teams encounter when trying to move from experimentation to production. Special attention will be given to the emerging ecosystem of Model Context Protocol servers and AI agents: attendees can ask what these technologies are, how they differ from traditional APIs, and what practical steps are required to harness them effectively. Integration strategies will explore how to weave AI‑powered components into existing automation orchestrator workflows, manage versioning of AI models, and ensure observability across hybrid API‑AI pipelines. By gathering detailed, context‑rich responses on these topics, Cisco aims to produce targeted guidance, reference architectures, and tooling updates that directly address the community’s most pressing uncertainties.
Whether you are attending Cisco Live Las Vegas in person or following the event remotely, there are actionable ways to make your voice heard and to benefit from the insights generated by Share Your Experience. If you are onsite, visit the DevNet Zone, engage with the sticky‑note walls, try the gamified touchscreen activities, and don’t hesitate to strike up a conversation with the facilitators—your perspective could be the missing piece that shapes the next feature release. For those unable to attend, keep an eye on the DevNet blog and the Code Exchange portal, where the outcomes of SYE sessions will be posted in the form of summary reports, updated sample code, and new MCP server listings. Consider applying the lessons learned: review your own API contracts for consistency, experiment with an AI‑enhanced script using the provided examples, and share your results with internal teams or community forums to propagate best practices. Ultimately, the most effective strategy is to treat feedback not as a one‑off event but as an ongoing habit—regularly seek out opportunities to contribute, stay curious about emerging technologies, and leverage the collective wisdom of the community to navigate the complexities of the AI‑augmented future. By doing so, you help ensure that innovation remains both powerful and profoundly human.