Case study · Technology · AWS
SAS Tech Studio Optimizes Engineering Costs by Scaling Kiro to 63 Developers
SAS Tech Studio, a technology company with 250+ developers, set out to optimize engineering costs by getting more capacity and better code quality from its existing team before adding 200+ planned hires.
- Kiro users growing from 24 to 63 developers
- About 3× modeled return on the Kiro investment
- Feature lead time targeted from 15 to about 11 days
Targeted results by December 2026
25%
of developer time targeted for recapture, or 10 hours per developer per week
~14.5 FTE
of added engineering capacity at full adoption
≤6
escaped defects per release targeted, down from 8
50%+
of pull requests targeted to be built with Kiro assistance, up from 20%
The Challenge
Routine work and rework were driving up engineering cost. With upcoming development demand rising, small inefficiencies in the software lifecycle were multiplying across the organization.
Routine work
Developers spent a large share of each week on routine work: breaking down requirements, boilerplate code, unit tests and documentation.
Lost context
Time was lost understanding unfamiliar code and rebuilding context across repositories.
Rework
Code-level errors and repeated bugs created rework and inconsistent quality.
Hiring cost
Upcoming development needs pointed to 200+ new hires, increasing engineering cost.
No measurement
There was no consistent way to measure productivity, quality or the value of AI tooling.
No AI governance
No organization-wide AI governance model existed for code and IP usage.
Kiro on AWS
The Solution
In partnership with HabileLabs and powered by AWS, SAS Tech Studio is scaling Kiro, AWS’s agentic AI development environment, from 24 to 63 active developers. The program runs as a Business Value Realization engagement, so every outcome is tracked against agreed baselines.
Problem-First Discovery
Ran a leadership discovery in July 2026 to map pain points across speed, quality, repeated bugs and hiring cost. Kiro was selected as the best fit after the customer compared options in the market.
Spec-Driven Development
Turned feature requests into requirements, designs and task lists before any code was written, reducing misunderstandings and rework.
Automated Tests with Agent Hooks
Generated and updated unit tests and documentation on every code change, so quality keeps pace with speed.
Steering Files for Consistent Standards
Encoded SAS Tech Studio’s coding standards and architecture rules, so every developer’s output follows the same patterns.
Enablement and Champions Program
Delivered a HabileLabs Kiro workshop and an AWS Kiro workshop in Gurugram, followed by hands-on onboarding, role-based labs, office hours and Team Lead Champions who coach their peers.
Value Dashboard and Governance
Built a Kiro Utilization & Cost Dashboard so leadership can see adoption, usage, cost and exceptions by team, backed by a CTO-led steering committee and regular reviews against baselines.
Targeted Business Impact
The program is on track to deliver the following by December 2026.
25%
Engineering Cost Optimization (Hero KPI)
25% of developer time targeted for recapture, or 10 hours per developer per week, creating about 14.5 FTE of added capacity at full adoption. The program models about a 3× return on the Kiro investment.
200+
Smarter Hiring
The added capacity helps deliver upcoming work with the current team and optimize the 200+ planned hires, with no headcount reduction assumed.
24 → 63
Adoption at Scale
Active Kiro users growing from 24 to 63 developers.
15 → ~11
Faster Delivery
Feature lead time targeted to fall from 15 to about 11 working days.
8 → ≤6
Higher Quality
Escaped defects per release targeted to fall from 8 to 6 or fewer, with quality never dropping below baseline.
20% → 50%+
Kiro-Built Pull Requests
Share of pull requests built with Kiro assistance targeted to grow from 20% to 50% or more.
Why SAS Tech Studio Chose HabileLabs
Problem-first approach
Started with SAS Tech Studio’s cost and delivery pain points, not the product.
AWS expertise
AWS Advanced Tier Services Partner with the AWS AI Services Competency.
Business Value Realization
Every target has a baseline, an owner and a review cadence, so value is measured, not assumed.
Hands-on enablement
Training, Champions and coaching move teams from trial use to daily practice.
Measurement built in
A purpose-built dashboard, combined with surveys, time studies and delivery data, shows where the value is created.
Governed AI adoption
Security, code and IP guardrails were agreed before scaling to more developers.
