New Substack: Slacker Index and the importance of vertical integration for hardware development

The Slacker Index by @BlakeScholl is a key metric for hardware startups. When engineers wait months for parts, startups burn cash and lose momentum. High Slacker Index = death by delays. Low Slacker Index = fast iteration and breakthroughs. This metric separates successful hardware startups from failures. Founders must focus on minimizing their Slacker Index.

"[the Slacker Index] measures how much time your engineers spend not engineering and building, because they’re waiting. Waiting for parts. Waiting for suppliers. Waiting for test windows. A high Slacker Index means brilliant people are stuck in analysis and meetings, terrified of mistakes because the cost of rework is measured in months. A low Slacker Index means fast iteration, risk-taking, and breakthroughs." Great article from Blake Scholl

There's been a lot of talk in the hardware world about the trend toward vertical integration (after decades of outsourcing). But why? One part of the answer is that vertical integration collapses lead times—which enables faster iteration and makes hardware development look more like software. More on this in my latest Substack: https://lnkd.in/gwZczwdf

Quick Productivity Tip: After years of building high-throughput back-end systems at Cisco, one small change that consistently boosts my productivity is investing in command-line and editor automation early. Whether it’s custom make targets, Go build tags, or VS Code tasks that run tests and linting with a single keystroke, a few hours of setup save countless context switches and keep me focused on writing resilient code. My rule of thumb: if I repeat a manual step more than twice a day, I script it. 👉 What’s the smallest automation you’ve added that paid off the most?

The key to 10x productivity with Claud Code is to spin up multiple Claude Code instances. Let one handle implementation while another plans your next feature. Learn to parallelize your entire workflow, and it changes everything.

Kubernetes has rapidly become a cornerstone in managing containerized applications, providing scalability, flexibility, and automation. But Kubernetes alone can’t handle all aspects of the development and deployment lifecycle.

Automate Your Network—Don’t Just Maintain It Manual troubleshooting and repetitive router tasks consume time and introduce risk. With Ansible, you can automate routine network operations—freeing engineers to focus on design, optimization, and higher-value work. Common tasks you can automate with Ansible: • Ping, traceroute, and advanced path detection • Automated error detection and corrective actions • Bandwidth monitoring and trend checks • Port capacity/type verification and inventory • Safe, repeatable router configuration changes The result: faster incident response, fewer human mistakes, consistent configurations, and predictable scaling. Whether you manage a small estate of routers or a large, distributed network, learning Ansible delivers measurable operational gains. Interested in practical examples or a quick runbook to get started? Let’s connect!!!! #Ansible #NetworkAutomation #DevNet #RouterConfiguration #ITOperations

Topic: Kubernetes – Kubelet & Day-to-Day Activities Kubelet Role Runs on every node as an agent. Talks to API Server to know which Pods should run. Ensures containers are healthy & restarted if needed. Reports node & Pod status to Control Plane. Example: If booking service container crashes, Kubelet restarts it. Day-to-Day Kubernetes Work Deploy → Create Deployments/Services via YAML. Scale → Adjust Pods based on traffic (e.g., hotel booking service during holiday season). Monitor → Use kubectl get pods, logs, and dashboards. Debug → Fix networking or container crashes. Secure → Use Secrets, RBAC, ConfigMaps. Manage Resources → Set CPU/memory limits.

## Container Orchestration ## Containers are isolated environments with dependencies. Container Orchestration is the automated management of these containers across a large number of machines (nodes). It involves: 1. Deployment: Launching containers across a cluster. 2. Scaling: Adjusting the number of running containers based on demand. 3. Networking: Allowing containers to communicate with each other. 4. Health Checks: Monitoring and replacing failed containers. 5. Example: The most popular platform for container orchestration is Kubernetes (K8s).