Case Study

Web3 + AI Trading Platform

Transforming Maiga.ai from Fragmented Vision to a Scalable DeFAI Product

Fractional CTO engagement
Strategic + technical leadership

Key Outcomes

40%

Faster product delivery

30-40%

Engineering cost savings

3 Phases

Clear roadmap from chaos

Scalable

Foundation for autonomous agents

Background

Maiga.ai is a DeFAI (DeFi + AI) platform that builds AI-powered trading agents for crypto users. The core vision is to make advanced trading intelligence accessible to everyday traders through agent-assisted analysis, signals, and future automated execution.

The Challenge

When I joined as Fractional CTO, the team faced several challenges:

✗

No technical leadership to shape product direction

✗

Broad, unfocused vision across multiple AI and Web3 ideas

✗

Unclear token utility and incentive design

✗

Slow, inconsistent development cycles

✗

No scalable architecture to support future autonomous agents

What They Needed

They needed strategic clarity, architecture discipline, and a roadmap that investors would trust.

My Solution

Strategic leadership across product, architecture, tokenomics, and team delivery

Product & Roadmap Direction

Streamlined vision into focused three-phase roadmap: AI signal & analytics agents → Community & creator ecosystem → Autonomous agents with on-chain execution. Gave founders execution clarity and realistic adoption path.

Architecture for AI + Web3 Agents

Designed modular system supporting AI inference pipelines, on-chain data processing, token-gated features, and future agent automation. Prevented 6–12 months of future rework.

Token Strategy (MAIGA + Proof of Trading)

Aligned token utility with product usage: Trading activity → token rewards, Token staking → premium agents access, Token gating → sustainable demand. Strengthened long-term token economy.

Hiring & Delivery Framework

Helped review/select developers, set engineering standards, introduce sprint discipline & documentation, build repeatable delivery workflow. Increased execution speed without extra headcount.

Focused Three-Phase Roadmap

From scattered ideas to clear execution path

Phase 1
AI Signal & Analytics Agents
Fastest time to market
Phase 2
Community & Creator Ecosystem
User-driven agent marketplace
Phase 3
Autonomous Agents
Secure, on-chain execution

Results & ROI

Measurable impact across delivery, costs, and strategic positioning

40% Faster Product Delivery

Clear scope + modular architecture allowed the team to release first AI agent product significantly faster

30–40% Engineering Cost Savings

Eliminated unnecessary features, reduced rework, allowed mid-level developers to execute confidently

Stronger Token Narrative

Tying token utility to real usage (Proof of Trading) improved investor confidence and long-term sustainability

Scalable Foundation for Autonomous Agents

Architecture supports future automation, wallet-based interactions, on-chain execution without major refactors

Founder Alignment & Strategic Clarity

From scattered ideas to disciplined roadmap, weekly decision-making rhythm, clear DeFAI market positioning

"

Soon helped turn our big vision into a clear, executable plan. His guidance across architecture, product, and token strategy saved us months of time and a significant amount of engineering cost.

Maiga.ai Founder

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