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Turning MarketBuzz
from stagnation
to growth.

This wasn’t a technology problem — it was a product-execution and alignment problem. Here’s how I diagnosed it, realigned the teams, and shipped a product into a brand-new ecosystem.

RoleSenior Engineer · Product Lead
CompanyShoutOUT Labs
TimelineMid-2025 → Early-2026
ProductMarketBuzz · Clover → ChatGPT
01 — Context

By mid-2025, MarketBuzz had a strong technical foundation — but it was not growing.

The product was stable, it had an existing user base, and it was already featured in the Clover App Market. Yet revenue was stagnant, retention and engagement were low, and new users struggled to understand the product’s value.

This wasn’t a technology problem. It was a product-execution and alignment problem.

02 — The core problem

Three systemic issues.

After stepping into the Product Lead role, I identified what was actually holding growth back.

01
Team misalignment

Engineering and marketing operated in silos, with no shared weekly goals and features shipping without coordinated go-to-market plans.

02
Weak execution rhythm

No real-time visibility into weekly progress across teams. Execution focused on activity, not impact.

03
Poor onboarding

Hotjar recordings showed users getting lost early. Key insights were buried, and users didn’t reach “aha” moments fast enough.

03 — First move

Diagnose before building.

Instead of immediately shipping features, I paused execution and planned a full-day system-design & strategy workshop with engineering, marketing and sales.

The goals

  • Align everyone on one shared problem
  • Replace assumptions with evidence
  • Create a single unified execution plan

The outputs

  • A shared diagnosis of what was holding growth back
  • 20+ concrete action items
  • A single execution playbook for the next 6 months
  • For the first time — tech and marketing working toward the same weekly targets

This workshop became the turning point.

04 — Operating model

From → To.

Before
  • Time-boxed sprints
  • Tech & marketing silos
  • Shipping features blindly
  • Guessing UX problems
After
  • Feature-driven, outcome-focused execution
  • Shared weekly goals
  • Shipping with GTM + UX intent
  • Data-driven UX via Hotjar
05 — Execution wins

Late 2025.

1 · Major UI/UX overhaul

Revamped dashboards, campaigns and insights based on real user friction; simplified flows and clarified value messaging.

→ Clearer onboarding · faster value realization · improved engagement

2 · Monetizing “Insight Unlock”

Converted a free analytics feature into a revenue-generating product.

→ First paid users · increase in installs · new positive reviews

3 · Entering a new ecosystem — the ChatGPT App

Designed and built a ChatGPT App exposing analytics conversationally — positioning MarketBuzz beyond the Clover App Market. Planned, implemented, tested and submitted within ~2 months.

→ Strategic expansion · new distribution channel without rebuilding core analytics
06 — Architecture

Technical highlights.

ChatGPT integration

  • Designed an MCP-based architecture with clear system boundaries
  • Initiated OAuth flows for the first two MCP tools
  • Connected conversational workflows to existing Clover REST APIs
  • Ensured analytics logic stayed reusable across surfaces

AI-assisted development

Experimented with AI tools to accelerate planning, code generation and refactoring — resulting in faster iteration without sacrificing production stability.

07 — Under pressure

Critical production challenges.

Challenge 01

Clover MFA vs ChatGPT test-account conflict

Clover requires MFA for production accounts; ChatGPT requires test accounts without MFA — discovered late in the submission process and time-critical.

Response: organized an emergency cross-team call, proposed an AWS Cognito-based login flow (already on the long-term roadmap), implemented it with AI-assisted development across 4 repositories, tested web + ChatGPT + staging + production logins, and deployed within 4 days.

Challenge 02

Legacy Clover devices

Clover devices run old Android versions and browsers; the UI broke on modern JS output.

Response: downgraded frontend output from ES6 → ES5, restoring compatibility without sacrificing functionality.

08 — Results

The outcome.

~0%revenue growth within 3 months
~0%cross-team execution efficiency
~0%lift in customer retention
1stChatGPT App submitted & live

Improved onboarding and engagement, stronger cross-functional trust and execution rhythm, and a platform positioned for scalable growth in 2026.

09 — Takeaways

What this demonstrates.

Stepping into ambiguous product problems, aligning teams around shared outcomes, designing scalable architectures, owning production delivery under pressure, and translating business goals into technical execution.

  • Shipping features ≠ growth
  • Cross-team alignment beats individual brilliance
  • AI accelerates development only when fundamentals are solid
  • Onboarding matters more than feature count
  • Weekly alignment prevents long-term drift
Field notes

Writing on Medium & LinkedIn.

I document the journey publicly — sharing lessons, experiments, architectures and insights as I grow from Senior Software Engineer to AI Engineer. These are the themes I keep coming back to.

Theme

Engineering & system design

Event-driven architecture, analytics pipelines, scaling read-heavy systems, and modernizing legacy code without breaking production.

Theme

Leadership & execution

Aligning teams around shared outcomes, execution rhythm, and the difference between activity and impact.

Theme

Product thinking

Why onboarding beats feature count, diagnosing before building, and turning business goals into technical roadmaps.

Theme

The shift to AI

Applied generative AI — RAG, agents, MCP — and what it takes to build reliable, production-grade intelligent systems.

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