Yesterday, I attended the AI × Marketing Meetup organized by eChai Ventures in Ahmedabad. Unlike many AI events that focus only on new tools, this meetup centered around a practical question:
“How can AI help marketing teams work faster, smarter, and create better customer experiences?”
The discussions revolved around AI-native marketing, customer personas, buyer journeys, automation, and building faster execution processes. Instead of replacing marketers, the speakers emphasized using AI to remove repetitive work so teams can spend more time on strategy and creativity.
Speaker Session 1
Khyati Brahmbhatt: Director of Product & Growth – Rocket
Khyati shared how Rocket approaches marketing as an AI-native company. Rather than using AI only for content generation, the focus is on integrating AI throughout the customer journey.
One of the key discussions was around customer personas and buyer journeys. AI can help marketers understand different audience segments, personalize communication, and improve engagement at every stage of the marketing funnel.
Key Takeaways
- Understanding customer personas is still the foundation of good marketing.
- AI helps create more personalized customer experiences.
- Mapping the buyer journey becomes easier with AI insights and automation.
- AI works best when combined with human understanding and business context.
Highlight
Good marketing starts with understanding people. AI simply helps us do it faster and at scale.
Speaker Session 2
Udit Goenka- Udit Goenka’s session was focused on one simple idea: AI is moving so fast that learning and experimenting have become more important than mastering a single tool.
He encouraged everyone to build their own AI workflows by combining different AI agents, open-source projects, and automation tools instead of depending on just one platform.
AI Tools & Libraries Mentioned
During the session, Udit introduced a few tools and platforms that marketers and builders can explore:
- AgentSkill.io – Build and manage AI agent skills and workflows.
- OpenRouter – Access multiple LLMs from different providers through a single API.
- Bird (Open Source) – An open-source AI project for building AI-powered applications.
- AI Agents Deployment – Using AI agents to automate repetitive business and marketing workflows.
He also emphasized that the AI ecosystem is evolving every week, so staying curious and experimenting is more valuable than trying to find one “perfect” AI tool.
Staying Ahead of AI Updates
One practical advice from Udit that I really liked was how he stays updated with the latest AI developments.
His approach is simple:
- Read Reddit regularly, as many AI updates and community experiments appear there before becoming mainstream.
- Follow relevant AI founders, builders, and researchers on X (Twitter) to stay informed about new launches and trends.
- Stay connected with people in the AI community through LinkedIn and other social platforms to learn from real-world experiences.
- Experiment with new tools yourself. If a tool improves your workflow, keep using it. If it doesn’t add value, move on and try something else.
This highlighted an important mindset:
Don’t chase every AI tool. Instead, continuously test, learn, and build a workflow that works for you.
Key Takeaways
- AI agents can automate repetitive workflows and improve execution speed.
- Open-source AI tools are becoming more powerful and accessible.
- Learning through experimentation is more valuable than only consuming AI news.
- The AI landscape changes quickly, so staying connected with the community helps you discover practical use cases before they become mainstream.
One Thought That Stayed With Me
One of the hosts from House of Starts shared a simple but powerful message:
Because of AI, you build fast, fail fast, learn fast, and grow fast.
This perfectly summarized the mindset required in today’s AI era. Speed is no longer just about development—it also applies to learning, experimentation, and marketing execution.
My Author’s Note
One point that strongly resonated with me is that AI is much more than a content-generation tool.
The real opportunity lies in automation and execution.
Instead of spending time on repetitive tasks, we can automate processes that don’t require constant human attention. This allows teams to focus on strategic thinking, creativity, and solving real business problems.
A practical example from my own work is SEO automation.
We publish more than 30 news articles and blogs every day. Earlier, checking every page for missing on-page SEO elements was a manual process. We have now automated this workflow. Instead of reviewing every article individually, the system alerts us only when an important SEO element is missing. This saves time and allows the team to focus on improving quality instead of repetitive checking.
As leaders and marketers, an important question to ask is:
“Which repetitive task can we automate today so our team can spend more time on meaningful work?”
Suggestions by AI
Based on the discussions during the meetup, here are a few practical suggestions:
- Start with one repetitive marketing workflow before trying to automate everything.
- Use AI to support research, content reviews, reporting, and quality checks.
- Keep humans involved in strategic decisions and customer communication.
- Regularly experiment with new AI tools to identify what genuinely improves your workflow.
- Measure the impact of AI by tracking time saved, faster execution, and better customer experience rather than simply counting the number of AI tools used.
Final Thoughts
The biggest takeaway from this meetup wasn’t about discovering another AI tool.
It was about changing the way we work.
AI is helping teams execute faster, reduce repetitive work, and create more personalized customer experiences. The organizations that succeed will not necessarily be those using the most AI tools, but those that thoughtfully integrate AI into their everyday workflows.
AI Disclaimer: Some sections of this field note were assisted by AI for writing and structuring. The content has been reviewed, refined, and validated by the Twin Owl Team to ensure it reflects the discussions and key takeaways from the meetup.
Also Read: Field Notes: Atlassian Community Meetup 2026 — AI Is Becoming a Teammate, Not Just a Copilot
