2X MORE DELIVERY AT LOWER SQUAD COST FOR A LEADING BRAZILIAN BANK

An AI-first delivery model increased throughput by 1.7x, improved development speed by 3.4x, and achieved 94% test coverage in the first sprint of Agent Mode, measured against a six-month historical baseline.

INTRODUCTION

Scaling software delivery without scaling team size requires a different operating model.

A leading Brazilian bank wanted to move from effort-based delivery to a value-throughput model while reskilling teams for AI-first engineering. The objective was to increase throughput, reduce cycle time, and maintain quality with a leaner squad structure.

CI&T redesigned the workflow around specification, orchestration, and human validation of specialized agents. Powered by CI&T Flow, the model automated refinement, code generation, and testing while keeping people responsible for critical validation.

The result was 2x throughput, a 3.4x faster development cycle, and 94% test coverage, with 90% of test scenarios automated.

THE CHALLENGE: SCALING DELIVERY WITHOUT SCALING COST

The organization needed to increase throughput and reduce squad cost while moving from effort-based delivery to a value-focused model.

Throughput Constraints

The existing effort-based model limited how much value each squad could deliver, creating pressure to increase output without expanding team size.

Manual Development

Coding and validation depended heavily on manual work, limiting cycle-time improvements and creating opportunities for AI-assisted automation.

Team Readiness

Scaling the new model required reskilling teams to specify, orchestrate, and critically validate AI-generated work.

THE SOLUTION

CI&T introduced an AI-first delivery model that shifted teams from manual coding to specification, agent orchestration, and critical validation, with automation across refinement, development, and testing.

Spec-Driven
Delivery

The team used specification-driven development to strengthen backlog refinement and create clearer inputs before coding. AI then supported code and test generation, helping reduce manual effort and accelerate execution.

Agent
Orchestration

Specialized agents supported technical refinement, user story development, code generation, and testing. People remained responsible for critical validation while agents handled repeatable execution.

Team
Enablement

New AI champions were trained to sustain and evolve the model, preparing the delivery team to scale the approach across additional squads.

THE IMPACT

The AI-first model increased throughput, shortened development cycles, and maintained quality while supporting a leaner squad structure.

HIGHER THROUGHPUT

Throughput
increased by 1.7x

From 27.0 to 45.5 function points per sprint

Measured in the first
sprint of Agent Mode

FASTER DEVELOPMENT

Development cycle
became 3.4x faster

Development cycle time improved by 70%

AI accelerated refinement, coding, and testing

QUALITY AND EFFICIENCY

94% test coverage

94% test coverage
90% of test scenarios automated

90% accuracy in
AI-generated code

TECHNOLOGIES USED

CI&T
FLOW

CI&T Flow Enterprise AI Management System supported intelligent agents across refinement, development, and testing, helping teams increase throughput while maintaining human validation.

AGENTIC
DELIVERY

A human-supervised agentic model automated key delivery activities while shifting engineers toward specification, orchestration, and critical validation.

SPEC-DRIVEN
DEV

A specification-driven approach strengthened backlog refinement and provided clearer inputs for AI-supported code generation, testing, and delivery.