When a change order (Trend) has assignment rows with cost impacts, those costs are attributed to packages in the CER "Package Variance" table. This works correctly at the individual package level, but group totals (Labour, Material, Equipment) over-count when a package spans multiple types.
A trend (TR-002) has two assignment rows:
Project: test n → Service: TEST_UPLOAD - Project Controls → Change Orders tab
| # GitHub Bot for Team Workflows via @mentions | |
| A guide to creating a GitHub bot that teammates can @mention in issues/PRs to trigger custom workflows. | |
| --- | |
| ## Approach 1: GitHub Actions + Comment Triggers (Recommended Start) | |
| Zero infrastructure. Uses GitHub Actions triggered by issue/PR comments. |
A Microsoft Teams bot powered by Claude Agent SDK that has deep knowledge of your codebase and Confluence documentation. Think of it as an always-available senior engineer teammate that knows the code, the docs, and the context.
Date: March 2026 | Dimensions: 5 | Sources: 80+ | Research Method: Parallel multi-agent exploration (avatar models, video/animation, voice synthesis, case studies, startup tooling)
The AI influencer space is real and monetizable — top AI personas earn $10K-$50K+/month via brand deals and Fanvue subscriptions. The tech stack has matured enough that a solo founder can launch in 48 hours using all-in-one platforms, or a small team can build a fully automated multi-persona content factory. The core insight across all research dimensions: character consistency (same face, same voice, same personality across all content) is the #1 technical challenge and the #1 differentiator between success and failure.
Date: 2026-03-17 Context: We have ~7,000 chunks in a DVAI index using PubMedBERT (768-dim) embeddings with frequent incremental updates of pharmaceutical patents and FDA documents. This document consolidates research across all relevant Databricks documentation.
There are 3 approaches for programmatically getting table lineage in Databricks, each with different trade-offs. The native lineage-tracking REST API exists but is not yet in the official Python SDK. SQL system tables are the most powerful option for historical analysis.
| [ | |
| { | |
| "has_discrepancy": true, | |
| "composite_score": 71.5, | |
| "patent_source": "mitapivat_app_14115289_CLM_1.pdf", | |
| "fda_source": "mitapivat_216196Orig1s000AdminCorres.pdf", | |
| "similarity_score": 0.9252641201019287, | |
| "discrepancy": { | |
| "category": "dosing_inventorship", | |
| "description": "FDA reviewers questioned and effectively identified/criticized the proposed dosing/clinical regimen and primary endpoint (\u226533% reduction in transfusion burden over 24 weeks, single-arm design with dose optimization) for mitapivat prior to or contemporaneous with patent claim amendments asserting clinical methods using the compound class.", |