The hottest Workflow Automation Substack posts right now

And their main takeaways
Category
Top Technology Topics
Bite code! 1712 implied HN points 14 Dec 25
  1. Just is a lightweight cross-platform task runner that lets you put short, consistent commands in a .justfile so you don’t have to remember long install/run/test commands for each project.
  2. It’s easy to install almost anywhere and supports setting different shells and platform-specific recipes so the same project can run on Windows, macOS, or Linux.
  3. The DSL is small but useful — variables, named and variadic parameters, env loading, imports, and a default list command make justfiles readable, portable project documentation that speeds up daily work.
Database Engineering by Sort 23 implied HN points 28 Oct 24
  1. Sort is now on the AWS Marketplace, making it easier for businesses to manage data changes. This means users can quickly add Sort to their systems.
  2. Sort helps streamline data change management with a simple process for proposing and approving changes. It makes it easy for teams to fix errors or update records without hassle.
  3. Every data change is logged by Sort, creating a clear history of what changes were made and why. This feature ensures full transparency and helps maintain high data quality.
bolt.observer 0 implied HN points 11 May 23
  1. Automated workflows can simplify liquidity management on lightning nodes
  2. Submarine swaps help address liquidity challenges with on-chain and off-chain funds
  3. Auto swaps are proactive actions set by node operators to maintain desired liquidity levels
OSS.fund Newsletter 0 implied HN points 11 Dec 25
  1. Keep a deterministic "spine" that owns final decisions, accountability, and traceability, and treat GenAI as a sidecar that proposes or drafts but never makes binding choices.
  2. If an action creates legal obligations, liabilities, or regulated communications, the spine must execute it; tasks that involve reading, summarizing, drafting, or routing can live in the sidecar under supervision.
  3. Make evaluation continuous: use pre-deployment tests, shadow mode, production monitoring for drift and errors, and strict change control with versioning and rollback to keep the system safe.
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Digital Native 0 implied HN points 13 Jan 26
  1. AI should be invisible to users: they don’t care about model names or specs, they care that the tool fits smoothly into their existing workflows and has an intuitive UI.
  2. Build AI that meets people where they already work by plugging into familiar tools and minimizing change; integrations and playbooks can act like a junior analyst to cut busy work and speed approvals.
  3. Capture context, decisions, and approvals (a context graph) with human-in-the-loop workflows so the system learns durable precedents over time and enables safer, increasing automation.