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Leverage Record: March 12, 2026

About the author: I'm Charles Sieg, a cloud architect and platform engineer who builds apps, services, and infrastructure for Fortune 1000 clients through Vantalect. If your organization is rethinking its software strategy in the age of AI-assisted engineering, let's talk.

Thirty tasks across seven projects. Infrastructure provisioning, multi-platform feature development, a complete site template redesign, PDF parsing improvements, MCP server conversions, and a full SEO overhaul. The tfadm MCP server conversion hit 133x, the highest single-task leverage factor I have recorded.

About These Records
These time records capture personal project work done with Claude Code (Anthropic) only. They do not include work done with ChatGPT (OpenAI), Gemini (Google), Grok (xAI), or other models, all of which I use extensively. Client work is also excluded, despite being primarily Claude Code. The actual total AI-assisted output for any given day is substantially higher than what appears here.

Task Log

# Task Human Est. Claude Sup. Factor Sup. Factor
1 Convert infrastructure management tool to MCP server (19 tools, 2 resources, 3 prompts) 40h 18m 5m 133.3x 480.0x
2 Consolidate compute architecture and write 10 serverless handlers with design documentation 24h 25m 5m 57.6x 288.0x
3 Implement ELO-based scoring level system across shared UI library and 3 client applications 24h 25m 8m 57.6x 180.0x
4 Build decision fatigue compensation model with service layer, schemas, router, and 8 MCP tools 16h 18m 5m 53.3x 192.0x
5 Multi-platform mastery tracking view across 3 client applications with shared UI patterns 12h 15m 3m 48.0x 240.0x
6 PDF parser: multi-column detection, font metrics, italic handling, skill category merging 20h 25m 5m 48.0x 240.0x
7 Certification-to-domain mapper with 80+ static patterns across 10 providers and 42 tests 12h 15m 3m 48.0x 240.0x
8 Modern site template design: 20+ template files with 900-line SCSS, dark mode, scroll animations 16h 22m 5m 43.6x 192.0x
9 Multi-platform enrollment abandonment with confirmation modals across 3 clients 6h 10m 3m 36.0x 120.0x
10 Feature view implementation for iOS (7 files: persistence, phase, state, view, routing, dashboard) 4h 8m 3m 30.0x 80.0x
11 Feature view implementation for web with full page component and indicator 4h 8m 3m 30.0x 80.0x
12 Feature view implementation for desktop (6 files with module CSS and wiring) 4h 8m 3m 30.0x 80.0x
13 Mastery tracking screen for desktop (new screen, CSS, routing) 6h 12m 3m 30.0x 120.0x
14 Mastery tracking page for web (persistence, component, CSS, wiring) 6h 12m 5m 30.0x 72.0x
15 iOS onboarding flow with file upload and branching path selection 4h 8m 3m 30.0x 80.0x
16 Research and compile hands-on labs master list across 13 certification exams 16h 35m 5m 27.4x 192.0x
17 Full SEO overhaul: OG tags, Twitter Cards, JSON-LD, canonical URLs, sitemap, RSS auto-discovery 8h 20m 5m 24.0x 96.0x
18 Container orchestration configs for 2 services (16 files: task defs, security groups, load balancer rules, DNS, IAM) 6h 15m 3m 24.0x 120.0x
19 Infrastructure stack with 8 configurations, target, version, and deployment for workloads API 6h 15m 3m 24.0x 120.0x
20 Analyze existing infrastructure-as-code and map to new configuration system with gap analysis 4h 10m 2m 24.0x 120.0x
21 Desktop onboarding flow: file upload and review with branching path selection 3h 8m 3m 22.5x 60.0x
22 Update backend MCP server to streaming HTTP transport with retry logic 1.5h 4m 3m 22.5x 30.0x
23 Write comprehensive system documentation with data schemas, fatigue model, and query reference 3h 8m 2m 22.5x 90.0x
24 Enrollment abandonment feature for iOS (auth client, state management, dashboard) 1.5h 4m 3m 22.5x 30.0x
25 Mastery tracking view for iOS (7 files: persistence, phase, state, view, routing) 4h 12m 5m 20.0x 48.0x
26 Enrollment abandonment feature for web application 2h 6m 3m 20.0x 40.0x
27 Fix 24 test failures across 3 service test suites with test infrastructure repairs 4h 12m 2m 20.0x 120.0x
28 Onboarding flow with file upload and path selection across 3 clients 8h 25m 5m 19.2x 96.0x
29 Enrollment abandonment feature for desktop across 6 files 1.5h 5m 3m 18.0x 30.0x
30 Convert 3 MCP servers from stdio to streaming HTTP transport with connection pooling 4h 18m 5m 13.3x 48.0x

Aggregate Stats

Metric Value
Total tasks 30
Human-equivalent hours 270h (33.8 working days)
Claude wall-clock time 426m (7.1h)
Supervisory time 114m (1.9h)
Tokens consumed ~2,443,000
Weighted avg leverage factor 38.0x
Weighted avg supervisory factor 142.1x

Analysis

The tfadm MCP server conversion stands out at 133.3x. That task involved wrapping an existing infrastructure management tool with 19 MCP tools, 2 resources, and 3 prompts. The high leverage came from the mechanical nature of the work: each tool followed the same pattern, and the AI could stamp them out without much variation. A human would have spent the better part of a week on the boilerplate alone.

Multi-platform feature rollouts continued to drive volume. Three separate features (release notes view, mastery tracking, enrollment abandonment) each got deployed across iOS, web, and desktop clients. The per-platform leverage ranged from 18x to 30x, but the aggregate tasks (all 3 clients at once) hit 36x to 48x because the AI could carry context across platforms and adapt patterns without re-learning the architecture.

Infrastructure work clustered around 24x: container orchestration configs, infrastructure-as-code analysis, and stack provisioning. These tasks involve a lot of cross-referencing documentation and generating repetitive configuration files. Lower leverage than pure code generation, but still significant given the precision required.

The lowest factor was 13.3x for the MCP transport conversion. That task required understanding three different server implementations and their connection models, then making architectural decisions about retry logic and connection pooling. More thinking, less typing.

The modern template redesign at 43.6x was notable: 20+ Jinja template files plus a 900-line SCSS stylesheet with full dark mode support and scroll animations, produced in 22 minutes. A front-end developer would spend two full days on that.

Let's Build Something!

I help teams ship cloud infrastructure that actually works at scale. Whether you're modernizing a legacy platform, designing a multi-region architecture from scratch, or figuring out how AI fits into your engineering workflow, I've seen your problem before. Let me help.

Currently taking on select consulting engagements through Vantalect.