We started the day early, energized, excited, and determined to give every organization an experience that would help them walk away achieving what they came for. As participants began arriving we distributed goodies, and asking everyone to write down their name, organization, and three things you can talk to them about outside of work. After all, we were going to spend two days building… who wants to talk only about work? 😄
Organizations joined us from Mumbai, West Bengal, Bihar, and a few other regions, and that diversity alone set a beautiful tone for the day. The energy they walked in with was palpable and reminded us of the spirit we saw at our first Launchpad in Delhi. If Delhi taught us the importance of community and collaboration, Mumbai took it a step further with sheer curiosity and energy.
A Warm Start: Icebreakers & Pilot Fundamentals
Sneha kicked things off with an engaging icebreaker, a simple but powerful way to spark conversations, bridge similarities, and ease everyone into the collaborative spirit of Launchpad.
We then moved into a session on pilot fundamentals:
- What is a pilot
- Why running a pilot matters
- What should you test in a pilot
- And how measuring the pilot helps reiterate
- Example of how SNEHA ran its first pilot
This was followed by an inspiration demo session where participants explored chatbots like Nayi Disha, SNEHA Didi, Civis, and a video walkthrough of TAP Buddy to understand how design, tone, and even small UI decisions impact user experience.
Even though they had not yet been introduced to chatbot flow-building, they were able to evaluate the chatbot purely from a user experience perspective.
They pointed out multiple insightful gaps and opportunities in the conversation design, for example, the bot accepting typed text instead of a location pin when asking for a user’s location, or the impact of flow length on the user experience (too long, too short, too many steps, etc.). Their observations clearly showed that they were already thinking from the point of view of end users and not just builders. This discussion set the foundation for the two-day workshop, sharpening everyone’s understanding of how simple and user-friendly conversation design influences the quality and usability of a chatbot.
By the end of this session, Sneha had created a checklist of Do’s and Don’ts, and participants walked away with their own inspiration lists to reference while building.
Designing the Blueprint: Canvas, Flow Mapping & Visualization
Next, we introduced a Design Canvas, a guided template that helped each organization map out:
- Their chatbot’s objective
- Target audience
- Context and culture
- Expected outcomes
- Pilot goals
Once their strategic blueprint was set, teams grabbed chart paper and sketch pens and got visual. They mapped out their entire chatbot conversation, from introduction and consent to registration, content delivery, and feedback loops.
There’s always something powerful about seeing ideas come alive on paper. It creates clarity. It builds confidence. And it sets a foundation for everything that follows.
After mapping their flows, teams shared them with others at their table and received quick feedback, two things they did well, and one suggestion to improve. It helped everyone refine their chatbot flow before moving to the platform.
From Paper to Platform: Glific Basics & Hands-on Building
Aishwarya then introduced the fundamentals of the Glific platform, connecting the paper prototypes to how they translate on the actual system, and introducing some Glific vocabulary that would soon become second nature to everyone. 😄
We followed this with a fun quiz and a match-the-following activity that took everyone back to their school days, and the room lit up with the same spark and enthusiasm of being back in a classroom again.
Tanu led a hands-on guided build where participants created consent and registration flows, adapting them to their own use cases. This session gave them a strong head start before diving into their independent work time.
We ended Day 1 with a group photo and feedback.
And the loudest request? – “More work time.” – Which, thankfully, was exactly what Day 2 was all about.
Day 1 closed with an average rating of 4.2, which indicated a strong start.
Day 2: Scaling Skills, Building Bots & Turning Ideas Into Systems
It began with a insightful talk by Atharva from Civis, who shared how their chatbot grew to reach 4+ lakh users, with conversations initiated organically, not pushed. You can read more about it here. His insights on starting small, designing thoughtfully, experimenting boldly, and learning constantly connected strongly across the room.
GSheet Integrations & AI in Action
Next, we explored Google Sheet integrations by first understanding the difference between qualitative and quantitative data. From there, we moved into how Gsheets can be used within Glific, writing data into Sheets and validating user responses. Tanu then led a guided build session, helping organizations set up workflows they could immediately use in their pilots.
We then transitioned to AI within Glific, using AI Assistants for answering queries based on peoples asks, for smarter and personalizded interactions.
Organizations working on AI-heavy use cases were grouped together, and Aishwarya led a guided build to help them bring these ideas to life.
Heads Down, Hands On: Building with Purpose
Work time truly came alive on Day 2. Some organizations:
- Refined flows they had started the previous day
- Built new flows from scratch
- Connected their chatbot to Sheets
- Tested and improved user journeys
- Applied AI nodes to enhance content or logic
By the end of the day, every participant had a functioning chatbot prototype they built themselves, and the pride was undeniable.
They were imagining scenarios far beyond the demo. Some explored ideas like integrating payment gateways to automate financial processes that directly connect to the problems their organizations are trying to solve.
They were not just thinking about building a chatbot, they were thinking about building systems. Questions emerged about automation and efficiency, such as whether user data can be collected through a single form rather than in multiple smaller steps. This instinct toward optimization so early in the learning process showed tremendous potential.
They weren’t just building chatbots. They were designing systems.
The Highlight: Prototype Presentations
The energy in the room transformed during prototype presentations.
Participants presented with ownership, clarity, and joy, reflecting their journey from idea to prototype in just two days.
And the best part? Other organizations didn’t just watch. They tested each other’s chatbots, shared thoughtful feedback, and celebrated every win.
The room turned into the kind of learning space we strive to build, one grounded in community, openness, and shared growth.
Closing Reflection
These two days reminded us why we do what we do.
To witness:
- Learning
- Collaboration
- Creativity
- Problem-solving
- And the spark that comes when people build something of their own
Launchpad became more than a workshop. It became a space filled with shared purpose, exploration, and innovation.
And as every participant walked out with a working prototype and the confidence to take it forward, we left deeply grateful to be part of their journey.
Mumbai continued the spirit we saw in Delhi, but with even more collaboration, sharper questions, and a powerful sense of ownership. We can’t wait to see how these organizations take it forward from here.
Like every cohort, Mumbai also gave us valuable learnings that will help us refine and strengthen future Launchpads. Some of the key takeaways include:
- Sharper time management: A packed agenda meant a few sessions stretched beyond expected timings. Adding clearer buffers and tighter transitions will help participants get maximum value without feeling rushed.
- Protecting lunch hour as real downtime: Many continued working through lunch because they were excited to build. While the energy was incredible, a protected break helps everyone recharge for the second half of the day.
- Running AI and non-AI tracks in parallel: On Day 2, parallel tracks worked extremely well for different levels of readiness. Making this structure explicit from the start can reduce FOMO and give participants more clarity.
These insights, combined with the enthusiasm of the cohort, leave us feeling even more committed to creating smoother, more energizing learning experiences ahead. With the momentum this group has shown, we can’t wait to see what they build next.