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Rate Limiting and Backoff for Reliable API Automations
Learn practical patterns for respecting API rate limits using throttling, retries, and backoff with jitter, so your automations run reliably without creating duplicate work or getting blocked.
Page Builder vs Structured CMS Fields: A Practical Decision Framework
Learn how to decide between freeform page building and structured CMS fields for a marketing site, using a simple decision matrix, a minimal content model, and workflow tips that scale.
Human-in-the-Loop Workflows for AI-Drafted Customer Support
A practical framework for using AI to draft customer support responses while keeping humans in control of accuracy, tone, and policy compliance. Learn a simple review workflow, a scoring rubric, and launch checklists you can reuse.
Build a Technical Baseline for Legacy Software (Before You Change Anything)
A technical baseline is a lightweight snapshot of how a legacy system works, how it behaves in production, and why key decisions were made. This guide shows a practical, small-team way to build one so modernization work is safer and easier to prioritize.
Output Constraints for AI Assistants: A Guardrail Pattern That Actually Scales
Learn a practical pattern for constraining AI assistant outputs using schemas, allowed actions, and validation loops so results stay safe and consistent without heavy infrastructure.
Monitoring LLM Features Without Heavy Infrastructure: Signals, Samples, and Alerts
A practical guide to monitoring LLM-powered product features using lightweight telemetry, targeted sampling, and simple alerting, without building a full MLOps stack.
Markdown vs Rich Text in a CMS: A Practical Decision Framework
A practical framework for choosing Markdown or rich text in your CMS, with decision criteria, common pitfalls, and a rollout plan that works for small teams.
Designing Idempotent Automation Jobs: How to Make Retries Safe
Learn how to design idempotent automation jobs so retries do not create duplicates, double charges, or repeated notifications. This guide covers practical patterns, a concrete example, and a checklist you can reuse.
Operational Logging for AI Automations: A Practical Review Loop
A practical guide to logging inputs, prompts, outputs, and decisions in AI-powered automations so you can debug failures, review quality, and improve safely without storing more data than you need.
CMS Roles and Permissions: A Practical Guide to Preventing Publishing Chaos
Learn how to design simple, durable CMS roles and permissions that keep publishing fast while reducing risk. This guide covers a minimal role set, common permission patterns, a concrete example, and a checklist you can reuse.
A Maintenance-First Roadmap for Legacy Software (Without Freezing Product Work)
A practical approach to planning maintenance so legacy systems stay reliable without endless emergencies or stalled feature delivery. Learn how to define maintenance work, build a backlog, allocate capacity, and track outcomes.
Rubric-Driven Quality Control for AI-Generated Text
Learn how to create a practical scoring rubric that makes AI-generated text predictable, reviewable, and improvable across teams. This guide covers defining requirements, scoring outputs, and operationalizing quality checks without heavy tooling.
Safer Small-Team Automations: Secrets, Dry Runs, and Audit Trails
A practical guide to making small-team automations safer and easier to maintain using secrets management, dry runs, guardrails, and audit trails. Includes a concrete example and a copyable launch checklist.
Write SOPs That Machines and Humans Can Follow
A practical method for turning informal work into clear, testable SOPs that support automation and AI assistants without confusing your team.
Versioning Your CMS Schema: Evolve Content Types Without Breaking Pages
Learn a practical, lightweight approach to versioning CMS content types and templates so you can ship changes safely, migrate data predictably, and avoid breaking published pages.
Configuration-First Automation: Make Small Bots Maintainable with YAML
A configuration-first approach keeps small automation scripts flexible without constant code edits. Learn how to design a simple YAML config, validation rules, and safe defaults so your bots stay reliable as requirements change.
Release Checklists and Rollback Plans: A Small-Team Pattern for Shipping Safely
A practical framework for small teams to ship software changes safely using a lightweight release checklist, staged rollout, and a rollback plan that is tested before you need it.
Designing Feedback Loops for AI Features: Capturing User Corrections That Improve Quality
Learn how to capture user corrections for AI outputs in a structured way that improves quality over time without collecting noisy data or creating operational chaos.
Weekly Backlog Triage for Small Teams: A Simple Ritual That Keeps Scrum Useful
A practical weekly backlog triage routine for small teams that keeps work visible, reduces thrash, and turns vague requests into shippable tickets without a heavy process.
Webhook Hygiene: Designing Reliable Triggers for Small Automations
A practical guide to designing webhooks that stay stable and debuggable as your automations grow, including event contracts, security, retries, and replay.
API Contract Tests for Small Teams: Keep Integrations Stable Without Heavy Tooling
Learn a lightweight approach to defining and testing API contracts so small teams can evolve services without breaking integrations.
Confidence Labels for AI Outputs: A Practical Pattern for User Trust
Learn how to add confidence labels and review paths to AI-generated text so users know what to trust and what to verify. Includes a lightweight scoring rubric, UI patterns, and a rollout checklist.
From Cron to Queue: Making Scheduled Automations Reliable as You Grow
Learn how to evolve simple cron jobs into a queued, observable workflow with retries, backpressure, and clear ownership. This guide includes a migration plan, checklist, and common pitfalls for small teams.
Red Teaming Lite for LLM Features: A Threat Modeling Checklist You Can Actually Use
A practical, lightweight method to identify failure modes in LLM features before launch using threat modeling, a focused test checklist, and clear ownership.
A Lightweight Evaluation Plan for AI Writing Assistants
A practical, small-team method to evaluate AI writing assistants using a tiny test set, a clear rubric, and repeatable review steps that improve quality without heavy tooling.
Acceptance Criteria for LLM Features: Turning Vague Quality into Testable Checks
A practical way to define, test, and monitor LLM feature quality using clear rubrics, small representative test sets, and pass/fail checks that fit small teams.
A Small-Team Playbook for AI-Assisted Meeting Notes People Actually Trust
A practical workflow for generating meeting notes with AI while keeping them accurate, searchable, and safe to share. Includes a lightweight rubric, common mistakes to avoid, and a copyable checklist for small teams.
Deprecation Budgets: A Practical Way to Control Technical Debt
A deprecation budget is a simple planning tool that reserves recurring time to remove old code, dependencies, and workflows before they become emergencies. This guide explains how to set one up, track it, and use it to keep small systems maintainable.
Headless vs Traditional CMS: A Decision Guide for Small Teams
Learn how to decide between a headless CMS and a traditional, page-based CMS by comparing workflows, costs, performance, and team skills. Includes a practical checklist and common pitfalls to avoid.
How to Run a CMS Content Inventory That Actually Improves Your Site
A practical method for auditing pages in any CMS, defining fields, and making decisions to keep, merge, update, or remove content without breaking navigation.
Event-Driven vs Scheduled Automations: How to Choose the Right Trigger
Learn how to choose between event-driven and scheduled automations using clear decision criteria, a concrete example, and checklists that reduce missed updates and surprise failures.
Preview-First Publishing: A Practical Draft-to-Publish Workflow for Any CMS
Learn a simple, durable draft-to-preview-to-publish workflow you can implement in almost any CMS to reduce mistakes, speed up reviews, and make content changes predictable.
The Strangler Fig Pattern: Modernize Legacy Software One Slice at a Time
Learn how the Strangler Fig pattern helps small teams modernize legacy systems safely by moving functionality incrementally, reducing risk while improving maintainability and delivery speed.
Editorial Guardrails in a CMS: Validation Rules, Workflows, and Checklists for Reliable Publishing
Learn how to add editorial guardrails to your CMS using field validation, roles, and lightweight workflows so content stays consistent without slowing your team.
A Definition of Done That Prevents Rework (A Practical Template for Small Teams)
A practical way to design a Definition of Done that reduces rework by turning your team’s real delivery risks into a short, testable checklist you can keep updated.
Human-in-the-Loop Review for AI Customer Support Drafts: A Practical Workflow
Learn how to design a human-in-the-loop workflow that lets AI draft customer support replies while humans retain control over accuracy, tone, and risk. This guide covers review levels, queues, checklists, and common pitfalls.
Content Briefs as Data: A Field-Based Template for Consistent AI-Assisted Articles
Turn your content brief into structured fields so humans and AI can produce consistent articles, reuse assets, and reduce editing time. This post walks through a practical “brief schema,” a concrete example, and a checklist you can copy.
A Simple Workflow Architecture for Reliable Nightly Automations
Learn a practical, small-team architecture for nightly automations that stays reliable as requirements change, with clear steps for retries, logging, and failure handling.
Refactor, Replatform, or Rewrite: A Decision Matrix for Small Teams
A practical framework to decide whether to refactor, replatform, or rewrite a system—using a lightweight decision matrix, concrete signals, and a checklist small teams can apply without overthinking.
Sampling and Spot Checks: Monitoring AI-Generated Content at Scale
A practical way to monitor AI-generated content quality using sampling, clear review criteria, and lightweight feedback loops—without reviewing every single item.
Token Budgeting for LLM Apps: Control Cost, Latency, and Quality
A practical framework for setting and enforcing token budgets in LLM features so you can keep costs predictable, responses fast, and output quality stable as usage grows.
Idempotency, Retries, and Dead Letters: A Practical Pattern for Reliable Automations
Learn a durable automation pattern that prevents duplicates, handles transient failures gracefully, and preserves failed work for review using idempotency, retries, and a dead-letter queue.
CMS Migration Without Drama: A Field-by-Field Mapping Method
Learn a practical, field-by-field method for migrating content between CMS platforms with fewer surprises. This guide covers inventorying content, defining a canonical model, mapping transformations, running staged migrations, and keeping operations stable afterward.
Audit Trails for Automations: Make Bots Explainable and Debuggable
A practical guide to building audit trails for automated workflows so you can answer what happened, why it happened, and what to do next—without digging through scattered logs.
How to Design a Content Model That Scales
A practical framework for modeling content in a CMS so pages, APIs, and workflows stay flexible as your site grows. Learn how to define types, fields, relationships, and governance without overengineering.
How to Standardize AI-Written Customer Emails Without Sounding Robotic
A practical system for consistent, accurate AI-assisted customer emails: define voice and policies, use modular reply components, add lightweight review, and improve with a simple feedback loop.
Runbooks for Automation: How to Keep Bots Maintainable
A practical guide to writing lightweight runbooks for automation workflows so failures are easy to diagnose, fix, and prevent. Includes a runbook template, monitoring tips, and an incident process that works for small teams.
Automating Release Notes with GitHub and AI (Without Making a Mess)
Learn a maintainable workflow for generating clear release notes from GitHub activity using AI, with lightweight standards and quality checks that keep the output accurate and readable.
Maintenance-First Software Strategy: Keep Small Systems Healthy Without a Rewrite
A practical maintenance-first approach for small software products: define health, prioritize the right upkeep work, and build simple routines that prevent slow-burn failures without triggering a rewrite.
A Practical Playbook for Reliable API Integrations in Small Systems
A step-by-step playbook for building API integrations that fail gracefully: clear contracts, safe retries, idempotency, and lightweight observability so small teams can reduce breakage without overengineering.
How to Build a Team Prompt Library That Stays Consistent Over Time
A practical system for creating, organizing, and maintaining reusable AI prompts for a team, with versioning, quality checks, and rollout tips that prevent prompt drift.
Webhook Automation Patterns: Making Integrations Reliable Without Overengineering
A practical guide to building dependable webhook integrations using idempotency, retries, queues, and monitoring—without turning a simple automation into a full platform.
Designing an Approval Workflow for AI-Assisted Publishing
A practical guide to designing an approval workflow for AI-assisted publishing, including stages, checklists, and lightweight automation so content stays accurate, consistent, and safe to ship.
From Inbox to Knowledge Base: An Automation Workflow for Support Teams
Learn a practical, low-maintenance workflow to turn repeated support questions into a searchable knowledge base using lightweight automation and careful AI drafting.
A Practical Blueprint for Modernizing Legacy Software Without a Full Rewrite
Learn a step-by-step approach to reduce risk in legacy modernization using safety nets, incremental patterns, and disciplined planning—without freezing feature work.
Quality Control for LLM Workflows: Guardrails, Checks, and Evals
A practical, evergreen checklist for making LLM-powered workflows reliable: define quality, add guardrails, run automated checks, and measure performance with small eval sets before you scale.