Banandre

ARTIFICIAL INTELLIGENCE (370)DATA ENGINEERING (97)ENGINEERING MANAGEMENT (55)ENTERPRISE ARCHITECTURE (31)PRODUCT MANAGEMENT (27)SOFTWARE ARCHITECTURE (166)SOFTWARE DEVELOPMENT (183)

Microservices Won’t Save You: The Hard Lessons from Shopify’s Modular Monolith and Discord’s ScyllaDB Migration

case-studies

Featured

Microservices Won’t Save You: The Hard Lessons from Shopify’s Modular Monolith and Discord’s ScyllaDB Migration

A deep dive into real-world system evolution, including Shopify’s journey with a modular monolith and Discord’s move from Cassandra to ScyllaDB, revealing practical trade-offs in scalability and maintainability.

#case-studies#database-migration#microservices...

data-modeling

When Boolean Columns Multiply: Is Schema Design Crumbling at 50 Flags?

Examining the tipping point in database design where proliferation of boolean flags signals deeper modeling problems, and whether to refactor into arrays, JSONB, or join tables.

#data-modeling#database-design#normalization...

AI sovereignty

GLM-5: China’s 745-Billion-Parameter Proof That AI Infrastructure Is No Longer a Monopoly

Zhipu AI’s GLM-5, allegedly trained entirely on Huawei Ascend hardware and MindSpore, challenges the CUDA-dominated AI landscape and marks a pivotal moment for AI sovereignty.

#AI sovereignty#Ascend#GLM-5...

ai-models

MiniMax M2.5: The $1/Hour Model That Makes Claude Opus Look Overpriced

MiniMax’s 230B MoE model hits 80.2% on SWE-Bench at 1/20th the cost of competitors. Here’s why the AI pricing model just collapsed.

#ai-models#coding-agents#m2.5...

ethical-ai

The 2M-Page Elephant in the Room: What EpsteinFiles-RAG Reveals About AI’s Infrastructure Crisis

A developer’s open-source RAG pipeline processing 2M+ pages of the Epstein Files exposes the brutal reality of scaling retrieval systems: the demo is easy, but production is a nightmare of hidden costs, ethical landmines, and infrastructure complexity.

#ethical-ai#Scalability

burnout

The Productivity Trap: How AI Is Engineering a Burnout Crisis

New research reveals AI tools aren’t reducing tech workloads, they’re quietly expanding them through ‘workload creep,’ turning efficiency gains into burnout, role confusion, and cognitive overload.

#burnout#engineering-culture#workload-creep

Beyond CPU and RAM: The Metrics That Reveal Your Architecture Is Dying

Your dashboards are green but users are screaming. Here’s how to find the real architectural health metrics that matter, before your next 3am incident.

china-ai

China’s AI Agent War: GLM-5 vs MiniMax M2.5 Signals a Strategic Shift

GLM-5 and MiniMax M2.5 releases mark China’s pivot from chatbots to autonomous agents, with divergent strategies on reasoning depth vs execution efficiency.

#china-ai#GLM-5#minimax

distributed-training

DIY AI Supercomputing: How a 6x RTX 3090 Build Exposes the Cracks in NVIDIA’s AI Strategy

A custom 144GB VRAM build with P2P-enabled GPUs demonstrates grassroots innovation in accessible AI training infrastructure using open frameworks.

#distributed-training#open-source-ai#rtx-3090...

ai-competition

GLM-5: China’s 744B Parameter Wake-Up Call That Landed in Stealth Mode

Z.ai’s latest release combines massive scale, Huawei hardware, and MIT licensing to challenge the AI establishment, while exposing the uncomfortable truth about “open” models.

#ai-competition#GLM-5#Hardware-Independence...

devops

Your Architecture Diagrams Are Already Dead (You Just Haven’t Buried Them Yet)

Architecture drift isn’t a tooling problem, it’s a fundamental mismatch between how we build software and how we document it. Here’s why your diagrams are lying to you and what actually works.

#devops#documentation

data-ingestion

The AI Data Ingestion Gold Rush: Most Are Digging in the Wrong Place

Data engineers are throwing LLMs at ingestion pipelines, but production-grade wins are rare. Here’s where AI actually delivers value, and where it creates expensive new problems.

#data-ingestion#etl