Hands-On Kiro Workshop
Ran a one-day HabileLabs Kiro workshop for the CloudiQS team at the HabileLabs Gurugram office in the last week of August 2026, using real delivery scenarios.
Shipping More Features with Fewer Hotfixes Using Kiro
Macfos Limited, listed on the BSE and based in Pune, runs Robu.in, an online store in India for electronics components, robotics, drone parts and 3D printing, with more than 6,000 products. The store runs on Bagisto (Laravel) on AWS, and a small in-house engineering effort builds and runs it. Catalogue, checkout and supplier-integration changes were coded and tested by hand, which slowed releases and led to frequent hotfixes. In partnership with HabileLabs and powered by AWS, Macfos is scaling Kiro, AWS’s agentic AI development environment, from a pilot to 27 Kiro Power licences. The program runs as a Business Value Realization engagement, so every outcome is tracked against agreed baselines.
Challenge: Manual Releases Were Holding Back a Growing Online Store
- Only about 1.5 production features were released per user each month.
- About 20% of releases needed a fix within 48 hours, putting checkout and catalogue availability at risk.
- About 1 build in 5 failed on its first run, creating repeated rework.
- Only about 20% of modules had current documentation, making every change slower.
- A growing technical-debt backlog was slowing each new release.
- There was no consistent way to measure delivery throughput or the value of AI tooling.
Accelerating Client Delivery with Kiro on AWS
HabileLabs delivered the following initiatives to address CloudiQS’ delivery speed, quality and capacity challenges:
Spec-Driven Development
Turned client requirements into requirements, designs and task lists before any code was written, shortening the time from spec to approved design.
Automated Tests with Agent Hooks
Generated and updated tests and ran checks on every change, so delivery speed rises without raising the change failure rate.
Steering Files for Consistent Standards
Encoded CloudiQS’ engineering standards and AWS patterns, so every engineer’s output follows the same rules across client projects.
Secure, AWS-Native Setup
Set up Kiro Power with AWS IAM Identity Center sign-in, encrypted usage reports in Amazon S3, CloudTrail audit logging and an AWS Budgets alert, all defined as infrastructure as code.
Value Dashboard and Governance
Built a Kiro usage and KPI dashboard so leadership can see licence activation, usage, cost and SDLC cycle time, backed by weekly operational reviews, monthly value reviews and BVR pit stops with AWS.
Targeted Business Impact
The program is on track to deliver the following by January 2027:
Shorter SDLC Cycle Time (Hero KPI)
SDLC cycle time per work item targeted to fall by 30% for Kiro-trained engineers, in steps of 10%, 20% and 30%, recapturing about 17,280 engineering hours a year, or about 9 engineer-equivalents.
More Billable Capacity
Recaptured hours free engineers for client delivery, with steady-state value of about $860,000 a year in billable capacity.
Adoption at Scale
Licensed Kiro engineers growing from 6 to 30.
Faster Design Approval
Time from spec to approved design targeted to fall by 40%.
More Frequent Releases
Deployment frequency targeted to rise by 25%, with the change failure rate never rising above baseline.
Higher Quality and Faster Ramp-Up
Test coverage targeted to rise by 15 percentage points, and new engineers productive within 2 weeks.
Why HabileLabs?
- Problem-First Approach: Started with Robu.in’s release speed and quality 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 presumed.
- Proven Before Scaling: The pilot on Macfos’ own codebase set real baselines before licences grew.
- Gated Investment: Licences expand only when agreed adoption gates are met, so spend follows proven value.
- Governed AI Adoption: Access, standards and approved integrations were agreed before scaling.
Conclusion
Robu.in is moving from manual, hotfix-prone releases to governed, AI-assisted delivery on AWS. More features per month, fewer hotfixes and better documentation protect checkout, support online sales growth and free about 22,500 engineering hours a year.