Mace Innovations
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Development Report

April 2026:
520 Commits of Momentum

A look at our April engineering velocity โ€” 520 commits across 15 active projects, led by iterative refinement and steady new-feature work.

Shawn Fultz
Shawn Fultz
Co-Founder, Mace Innovations
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520
Commits
15
Projects
177K+
Lines Added
1,937
Files Modified

๐Ÿ“Š Executive Summary

April 2026 delivered 520 commits across 15 active projects, adding an estimated 177,000+ lines of code. The month skewed toward iterative refinement โ€” roughly 41% of commits โ€” as we hardened recently shipped features and tightened the details through our AI co-development workflow.

Activity was deadline-driven, averaging 17 commits per day but peaking at 124 commits in a single day at month-end. Work spanned compliance and policy tooling, financial calculators, support ticketing, and marketing collateral โ€” across a C#, TypeScript, Python, and Shell stack.

๐Ÿง  AI Usage & Efficiency

4.28B
Tokens Processed
4.14B
Read from Cache
96.9%
Cache Hit Rate
10.8M
Output Tokens
6
Claude Models

Of April's 4.28 billion tokens, 4.14 billion were read straight from cache โ€” a 96.9% cache-read ratio. Much of that runs on Claude's 1M-token context window: large codebases stay resident in cache and get re-read hundreds of times instead of recomputed on every call. That cache-read ratio is the heart of our cost efficiency โ€” it's what makes operating at this token scale economical.

Opus 4.7Opus 4.6Haiku 4.5

๐Ÿค– AI-Powered Co-Development

Our development process is fundamentally different from traditional software engineering. We don't work from detailed specificationsโ€”instead, we co-develop with AI, iterating rapidly through ideas and implementations.

What might traditionally be called "bug fixes" are really iterative refinementsโ€”the natural result of building software collaboratively with AI assistants where the first implementation is a starting point, not a final product.

This approach lets us move faster, experiment more freely, and deliver features that truly match user needs rather than predetermined specifications.

๐Ÿ”ง Work Breakdown

๐Ÿ”„
212
Iterative Refinement
๐Ÿš€
143
New Features
๐Ÿ“
111
General Updates
โš™๏ธ
17
DevOps / Config
๐Ÿงช
16
Testing
๐Ÿ“š
4
Documentation

๐Ÿš€ Where the Work Landed

  • โ†’Compliance and policy tooling โ€” policy document management with role-based access controls
  • โ†’Financial calculators โ€” payment, credit, rate, and seller-credit workflows
  • โ†’Support ticketing and shared inbox โ€” ticket handling, replies, and reliable email delivery
  • โ†’Marketing collateral generation โ€” flyers, logos, and imagery with mobile-friendly layouts
  • โ†’Admin portal โ€” user management, granular permissions, and access control
  • โ†’Print and document layout improvements across output types
  • โ†’Batch processing and automated backups

โœจ Refinements & Hardening

  • โœ“UI polish across buttons, modals, cards, and page views
  • โœ“Email deliverability and reply handling improvements
  • โœ“Mobile responsiveness across key surfaces
  • โœ“Data mirroring and cross-system synchronization
  • โœ“Sensible default states and configuration handling

๐Ÿ’ป Technology Focus

Files modified this month, grouped by area of the stack:

Frontend372
Documentation89
Config76
Other49
Data/ML24
Backend19

๐Ÿ“ฆ Project Distribution

Activity spread across 15 active repositories out of 142 total in our organization. Top contributors by commit volume:

1
Project 1
Iterative Refinement
112
commits
2
Project 2
General Updates
96
commits
3
Project 3
Iterative Refinement
82
commits
4
Project 4
Iterative Refinement
73
commits
5
Project 5
General Updates
66
commits
6
Project 6
Iterative Refinement
47
commits

๐Ÿ”ฎ Looking Ahead

April set the table for a much larger May. As we scale up, our focus areas include:

  • Building out our internal multi-agent development platform
  • Deeper CI/CD automation across preview, staging, and production
  • Expanding automated code review and quality gates
  • Continued investment in client dashboards and integrations
  • Performance and cost optimization across the stack

Want to learn more about our engineering practices?

Read: Context Architecture Deep Diveโ†’