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Tagged articles

model versioning

5 articles · Page 1 of 1
Data Bricklaying Diary
Data Bricklaying Diary
Oct 12, 2026 · R&D Management

Start with One Scenario or Build Full Ontology? Preventing Pilot Silos

The article advocates starting enterprise ontology with a verifiable business capability like supplier qualification checks, defining object identity, scope, shared definitions, and maintenance responsibilities upfront, then using a second scenario to test reuse boundaries while tracking dependencies for future changes.

Data Governancearchitecture decision recordsdependency tracking
0 likes · 14 min read
Start with One Scenario or Build Full Ontology? Preventing Pilot Silos
Top Architecture Tech Stack
Top Architecture Tech Stack
Sep 17, 2026 · Artificial Intelligence

Evaluating Gray-Scale AI Models: From SVG Tests to Engineering-Grade Verification

The article analyzes gray-scale testing signals for GPT-6 Sol and Opus 5.2, arguing that developers should rely on fixed engineering benchmarks — like SVG generation quality, tool-chain success rates, and multi-layer verification — rather than marketing names or knowledge-cutoff probes to assess model upgrades.

AI model evaluationClaude CodeGPT-6
0 likes · 17 min read
Evaluating Gray-Scale AI Models: From SVG Tests to Engineering-Grade Verification
Frontline Investigation
Frontline Investigation
Aug 28, 2026 · Industry Insights

Beyond Capability Lists: The Hidden Challenge of LLM Project Delivery

This article argues that successful LLM project delivery depends not on model capability lists but on establishing traceable judgment chains covering model versions, knowledge sources, tool calls, and operational accountability, highlighting a four-layer responsibility framework and four key evaluation questions for procurement and governance.

AI governanceJudgment ChainLLM project delivery
0 likes · 11 min read
Beyond Capability Lists: The Hidden Challenge of LLM Project Delivery
Frontline Investigation
Frontline Investigation
Aug 8, 2026 · Artificial Intelligence

Silent LLM Upgrades: When 'Smarter' Models Break Production Workflows

Frequent, unannounced LLM upgrades in industry applications can silently alter decision boundaries, tool usage, and confirmation logic, breaking established processes. The article proposes a four-dimension observation framework and argues for reversible, observable iterations with versioned knowledge, rules, and orchestration to maintain trust and compliance.

AI complianceAI governanceLLM upgrades
0 likes · 12 min read
Silent LLM Upgrades: When 'Smarter' Models Break Production Workflows