⚡ R&D AI-Helper: Editable Engineering Sheet & Antigravity Autonomous Engine

● Live Editable Cells

Directly edit any task cell, lead engineer, Linear tag, stage, progress %, or CI test notes below. The ⚡ Antigravity / AI Actions engine allows you to analyze code telemetry, solve sprint optimization problems, generate test harnesses, and adjust requirements dynamically.

Assigned Engineer
Romit Bhingradiya
🔴 Medal: Action Required (0 Commits)
🔴

Personal Performance Audit: Action Required (Oct 1–7 Cycle)

Standard: Output-Based Verification · Zero Credit for Unpushed Local Work
Weekly Escrow Held
Audit Finding: You billed 12h 00m ($84.00) on Upwork for Kommerce-1, but 0 commits exist in GitHub on feature/kommerce1-connectors. Holding 12 hours of code locally without pushing violates engineering policy.
🚀 How to Push Kommerce-1 Work Today (Required):
git checkout -b feature/kommerce1-connectors
git add .
git commit -m "feat(kommerce-1): implement multi-store connectors & catalog schema sync"
git push origin feature/kommerce1-connectors
📹 Release Gate Video Deliverables:

Upload the Kommerce-1 Gate 3 walkthrough video (2–3 mins Loom) demonstrating live multi-store catalog sync in the staging UI to unblock weekly escrow approval.

Work Diary — Romit Bhingradiya

Role: Lead Engineer · Kommerce-1 / Kbot R&D Timezone: America/Los_Angeles (PST) Working window: 09:00-18:00 · 8.0 h target
Attribution coverage 96% (4% unattributed)  ·  Last active: 16:14 PST
⚡
Performance-Based Model (No Seat-Warming Time-Counting Required)
Daily Rate Formula: Completed Items ÷ Requested Items = Rate Today
Requested Today
16 Tasks
÷
Completed & Measured
14 Delivered
=
Rate Today
87.5%
Tracking Hours · Today
6.8 h logged
85% of 8.0 h target  ·  -1.2 h remaining  ·  projected 8.4 h by EOD
R&D Activity · Today
Commits to main14 + 3
Pytest test suite310/310 100% PASS
Jest unit tests19/19 Green
Linear tickets closed6 + 2
PRs reviewed & approved4 + 1
Test coverage94% + 2
Code review SLA1.2h Fast
Weighted Score · Engineering Sprint KPI (7 Components)
88 of 100
Scoping & Schema Types 30% × 1.00 = 30.0
Core API Routes & Logic 20% × 0.95 = 19.0
Automated Jest/Pytest CI 15% × 1.00 = 15.0
Linear Ticket Commit SHA 15% × 0.90 = 13.5
Mainline Merge & Deploy 10% × 0.85 = 8.5
Antigravity Velocity Multiplier 5% × 1.00 = 5.0
Code Review Timeliness 5% × 0.96 = 4.8
Raw × attribution 0.96 95.8 × 0.96 = 88.3
⚡ AI-Helper Note · Antigravity AI Engine
Hours tracking 6.8 h on current pace with projected 8.4 h by EOD. All 14 completed deliverables cryptographically matched with Git commits and Jest/Pytest results. Pytest 310/310 tests pass green with 0 regressions. Velocity multiplier 0.68Δ earned top tier score. 2 remaining tasks are Gate 1 & Gate 2 execution runs, progressing on schedule.
About Workforce · kbot-workforce-video.html  |  Live version · kbot-workforce-daily-export.html
Rendered 2026-10-06 · Illustrative data, verified telemetry
🔄 End-to-End Engineering Sprint Progression Funnel
Real-Time CI/CD Telemetry
Stage 1 (20%) Arch & Types
Scoping & Schema
4 Modules
DB schemas & TypeScript interfaces defined
Stage 2 (40%) Core Coding
API Routes & Logic
18 Endpoints
Core service layer and controller handlers built
Stage 3 (60%) Automated CI
Jest Unit & Integration
19/19 Green
Regression test harness executed with zero failures
Stage 4 (80%) PR & Proof
SHA Trace & Linear [M3-88]
5 Commits
Cryptographic commit SHA attached to Linear ticket
Stage 5 (100%) Deploy
Mainline Merge & L4 Live
1 Host Deploy
Merged to origin main, Linode auto-deployed
📋 Engineering Sprint & Task Work Report ● Live Editable
📊 Analyze Sprint & CI Telemetry
💡 Optimize Sprint Path & Bottlenecks Smart
📝 Summarize Sprint Work Report
⚙️ Adjust Sprint Scope & Milestones
✨ Ask Antigravity Copilot...
Task / Module Name Lead Dev Linear Ref Lifecycle Stage Progress Track CI / Latency Telemetry Action
[KOM-101] Kommerce-1 Console Defect Resolution Romit Bhingradiya [KOM-101] Stage 1: Pending Push (0%)
0% (Push Required)
 Resolve sync loop exceptions & console errors
[KOM-102] Kommerce-1 Pytest 310 Automated Suite Romit Bhingradiya [KOM-102] Stage 1: Pending Push (0%)
0% (Push Required)
 310/310 Pytests passing green
[KOM-103] Kommerce-1 Store Catalog Schema Validator Romit Bhingradiya [KOM-103] Stage 1: Pending Push (0%)
0% (Push Required)
 Run validate_catalog for Shopify/Amazon
[KOM-104] Kommerce-1 Multi-Store Connectors & Catalog Sync Romit Bhingradiya [KOM-104] Stage 1: Pending Push (0%)
0% (Push Required)
 Local branch unpushed · Shopify/Amazon schema sync
[KOM-107] Kommerce-1 Gate 3 Walkthrough Demo Videos Romit Bhingradiya [KOM-107] Stage 1: Video Demo (0%)
0/1 Video (Pending)
 2-3 min Loom walkthrough video required
⚡ AI Daily Engineering Action Planner 4 Action Items Pending

Generated automatically by analyzing active pull requests, failed tests, and upcoming milestone cutoffs:

🔬 Complete Jest Test Suite for Work Diary Module
Target: tests/unit/workforce-work-diary.test.ts · Target 100% pass ratio
🏷️ Tag Linear [M3-88] in Zoom Bot Commit & Verify SHA
Required for objective pre-flight signoff and 5% KPI metric
⚡ Check Task Budget Velocity Ratio ($\Delta = 0.68$)
Actual: 7.5h vs Budget: 11.0h · Metric #4 on target for 15% credit
🚀 Push Mainline Merge to Origin Main before 17:00 Cutoff
Triggers automated Linode host-build deploy to kasercorp.com
⚙️ 7-Item R&D Performance & Velocity Simulator 100% Weight Total
99.3
R&D SCORE
🥇 Gold Medal Performer
Task Budget Velocity: 0.68Δ (7.5h / 11.0h)
5 Commits Verified 19/19 CI Tests Pass
1. AI-Progress Match (Sprint Plan Alignment) 30% Weight · 100%
2. Target Met (Sprint Milestone Delivered) 20% Weight · 100%
3. Code Performance (CI/CD Automated Test Pass) 15% Weight · 100%
4. Time Meets Requirement (Velocity Δ = actual/budget) ★ Special #1 · 15% Weight · 95.5%
5. Schedule (On-Time Delivery @ 17:00 Cutoff) 10% Weight · 100%
6. Linear Requirement Met (Issue Tag Reference) 5% Weight · 100%
7. Three-Way Agreement Signed (Pre-Flight Signoff) ★ Special #2 · 5% Weight · 100%
📐 Linear Insights Metrics vs. Kaser Autonomous R&D Measurement Architecture
Architecture Specification

Why Kaser R&D Workforce keeps Linear's UX primitives (Teams, Cycles, Projects, Tasks, Workflow States) while replacing the human-scored measurement layer with autonomous AI telemetry.

📊 Linear's Built-in Measurement Metrics (Insights)

# Linear Metric What It Measures Kaser Autonomous R&D Evolution
1 Cycle completion rate % of issues scheduled for a cycle that got closed by cycle end AI-Weighted Deliverable Completion (% against verified commits & tests)
2 Throughput Count of issues closed per cycle / week / day Verified Task Output per Day (backed by Git SHAs & PRs)
3 Velocity Sum of story-point estimates closed per cycle (if teams estimate) 3-Way Signed Hours & Dynamic AI Weights (0–100 Daily KPI)
4 Scope added / removed mid-cycle Issues added or deferred after the cycle starts (sprint-churn) Autonomous Daily Scope Rebalancing via AI To-Do Arrangement
5 Lead time Time from issue created → done Linear Issue Creation → PR Verified Lead Time Telemetry
6 Cycle time Time from started → done (excludes backlog wait) Active Working Window & Time Log Duration per Work Block
7 Issue age How long each open issue has been sitting in its current state Stalled Deliverable Alerting & Priority Weight Escalation
8 Workload per assignee Count / point-sum of open issues per person Daily Capacity vs. Assigned AI Weight Budget (8h / 100 pts)
9 Burndown / burnup Remaining or completed scope plotted over cycle days Release Gate Readiness Burnup (Gate 1 QA → Gate 2 Defect → Gate 3 Demo)
10 Triage queue depth Unassigned incoming issues waiting on triage Autonomous Issue Ingestion & AI-Triaged Priority Labeling

⚠️ Characteristics of Linear's Model

  • Count- or point-based, not hours-based: No built-in time logging; requires 3rd-party add-ons.
  • Volume-centric: Closing more trivial issues yields better numbers.
  • Human-planned: Humans groom backlogs, estimate points, and manually plan cycles.
  • Human-scored: Retrospectives and appraisals are subjective meetings.
  • No code-quality dimension natively: Review turnaround and defect escape need LinearB/Jellyfish.
  • No "did you follow the plan" dimension: 20 random closed issues count the same as 20 planned ones.

✨ Why Kaser Keeps Linear's Shape but Swaps Measurement

Linear's primitives (teams, cycles, projects, tasks, workflow states) are kept for developer UX familiarity. The measurement layer is replaced by:
  • Hours (actual ÷ required, 3-way-signed) instead of story points.
  • AI-arranged daily to-do list instead of human-authored sprint grooming.
  • AI-measured completion against multi-modal evidence (commits, PRs, issue updates, time logs, doc edits) instead of human retro scoring.
  • Code performance & Release Gates as first-class KPI components (via GitHub signals, automated pytest suites, and demo walkthrus).