
Build Daily
Tinley Park · July 18, 2026Signals
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What the builders I follow just shipped — newest first, decoded through what I’m building. The read, the take, why it matters.
- Neo4j: Technical Deep Dive: Preparing Your Context Graph for GenAIWhat it covers
- Knowledge Graphs and GenAI
- GraphRAG Implementation
- Agentic Workflows
- Insel Spital Bern: From Free Text to Knowledge Graphs: Swiss Medication & Procedure MappingWhat it covers
- Data Harmonization
- Neo4j Knowledge Graph
- Interactive Visualization
- GraphRAG in Python: Agentic AI with Knowledge GraphsWhat it covers
- Intro
- GraphRAG Theory
- Environment Setup
- BASF: Utilization of knowledge graphs to consolidate biological context for non-model plantsWhat it covers
- Plant Twin Overview
- Data Integration
- Collaboration with Neo4j
- KWS Saat: From Graph to Gene: Knowledge Graphs and AI for Explainable Gene DiscoveryWhat it covers
- Knowledge Graph Integration
- Link Prediction
- Generative AI
- Neo4j: Augmented AI: Building Contextual Intelligence with Knowledge GraphsWhat it covers
- AI Pilot Failures
- GraphRAG Introduction
- Knowledge Graphs in AI
- Amalgo: Financial returns from Context Graph & AI that reduces QA investigation durationsWhat it covers
- GraphRAG Overview
- Knowledge Graph Construction
- Hybrid Retrieval Method
- Bayer: Knowledge graph reasoning and GraphRAG for early target discoveryWhat it covers
- Graph Reasoning
- GraphRAG
- Reducing Hallucination
- Codex vs Fable: Which AI Agent Picked the Better Problem?What it covers
- Same brief, two different outcomes
- Why agent scale changes the workflow
- Fable's preflight build
- The Connected Startup Episode 2: IciteWhat it covers
- The Problem with Traditional Security Tools
- The Insight Behind Icite
- Graph Technology as a Solution
- A 3-person team vs 50-person agency #AI #FutureOfWork #agencyWhat it covers
- The End of Size as a Signal
- Small Teams vs Big Agencies
- The New Competitive Edge
- Neo4j: Shaping the future of manufacturing with connected data and Neo4jWhat it covers
- Shop-floor visibility
- Supply chain and order optimization
- Requirements and engineering traceability
- Building Automotive Parts Intelligence using Graph Memory for Supply Chain ResilienceWhat it covers
- Supply Chain Risk in Automotive Parts
- Vector Search Limitations
- Dual-Store Architecture
- Reply: Scaling Context Graphs: From architecture to real-world impactWhat it covers
- Knowledge Transfer Risk
- Limitations of RAG
- Graph Architecture
- SIEMENS: From unstructured fragments to portfolio intelligenceWhat it covers
- Data Fragmentation
- Knowledge Graph Construction
- Conversational Search
- AIRBUS: See what others miss: Revealing hidden risks in Airbus’ supply chain with Graph intelligenceWhat it covers
- Supply Chain Fragility
- AeroTrace Dashboard
- Process-Flow Heatmaps
- The real problem with AI #aiagents #Claude #OpenClaw #productivityWhat it covers
- The Integration Burden
- AI Tools Are Fragmented
- The Real Bottleneck
- 192GB of VRAM in One PC… The Cheap WayWhat it covers
- Dual-Intel GPU Setup
- 192GB VRAM Feasibility
- Cost vs. NVIDIA Alternatives
- Fable 5 And GPT-5.6 Don't Need Better Prompts. They Need A Clean Setup.What it covers
- I Overbuilt My AI Harness
- The Hidden Cost of Harness Bloat
- Rule 2: Blame the Right Layer
- GLM 5.2 is great ... but #AI #GLM #Claude #OpenAI #AnthropicWhat it covers
- GLM 5.2 Performance
- Cost Efficiency
- Adoption Paradox
- France Is Ditching Windows (The Distro They Picked Surprised Me)What it covers
- France's Windows to Linux Migration
- The US Cloud Act and Data Sovereignty
- NixOS in French Digital Affairs
- The $200K AI Job That Didn't Exist Last YearWhat it covers
- Next AI goldrush
- Chegg died
- Everything flipped
- You can build your AI's memory just by talking. Here's the catch. #AI #aiagents #AImemoryWhat it covers
- AI Memory Build via Conversation
- Rapid Progress in AI Capabilities
- The Danger of Misinterpreted Intent
- Your Next AI Subscription Shouldn't Be ChatGPT 5.6 Or Fable 5. It Should Be Both.What it covers
- Model choice by work pattern
- Sol's high score, low 'big model smell'
- OpenAI vs. Anthropic: different training philosophies
- How To Stay Relevant as an AI/ML EngineerWhat it covers
- Intro
- Personal Background
- Is Learning AI/ML Still Worth It?
- Claude is quietly taking over your company's data #AI #Claude #Anthropic #data #enterpriseWhat it covers
- Data as Competitive Edge
- Claude in Slack
- Context Lock-In
- Your Roadmap Is Why You're Losing to AI-Native Teams.What it covers
- Why AI-native companies ship faster
- Moving coordination into code
- The 15 commandments as an operating system
- Claude Code + Clay Makes Lead Generation Actually FunWhat it covers
- What We're Building
- The Data Problem vs The Tool Problem
- Why Clay and the Waterfall
- With AI, going slow is the dangerous move #AI #productivity #mindset #technologyWhat it covers
- The Bike Analogy
- AI and Speed
- The Myth of Safe Slowness





























