AI Writing Systems: From Draft to Publish — Reliable Prompt Engineering & Production Workflows
A practical guide to building repeatable, auditable AI writing systems that take content from draft to publish. Covers core principles, recommended prompt structure, a step-by-step production workflow, and rigorous quality-control techniques including evaluation, monitoring, and common failure modes.
Using AI to Get Hired Ethically: A Practical, ROI-Focused Playbook for Jobseekers and Freelancers
A realistic guide to using AI to get hired ethically — who benefits, business models you can offer, step-by-step execution, costs, timelines, compliance risks (EEOC/FTC/LinkedIn), and the metrics that prove ROI. Includes tool-cost ranges, disclosure best practices, and recovery steps if things go wrong.
Build an AI Course People Finish: A Practical, ROI-Focused Playbook
A business-first guide to designing, pricing, and delivering an AI course that students actually complete. Covers cohort vs self-paced models, step-by-step execution, realistic costs and timelines, compliance (GDPR/COPPA/WCAG), production and platform fees, conversion benchmarks, and the metrics you must track to measure ROI.
AI Marketing Playbook: Practical 2026 Guide to Build Monetizable AI Marketing Workflows
A practical AI marketing playbook for 2026 that shows marketers how to design, test, and monetize AI-driven campaigns. Learn step-by-step workflows, required tools and data, measurable KPIs, common failure modes, and how to control risk so AI improves outcomes without creating customer friction.
AI industry outlook: Signals to Track for 2026 — Verified trends, drivers, and what to monitor
A careful, evidence-led review of the AI industry outlook: verified trends (open models, multimodal progress, enterprise scaling challenges), the forces behind them (compute, data, standards), areas of expert disagreement, practical implications for teams, and a prioritized watchlist of measurable signals and metrics.
AI compute costs: current trends in compute, costs, and efficiency
This evidence-led analysis examines how AI compute costs are shifting today — driven by new accelerator generations, software efficiency (quantization, distillation, sparse models), benchmarking results, and rising energy demands — and separates well-documented signals from open uncertainties relevant to engineering and procurement decisions.
Safety and Misuse: Deepfakes, Fraud, and Abuse — An Evidence-Based Compliance Guide
A neutral, evidence-based overview of risks, regulatory responses, and practical compliance steps for Safety and Misuse: Deepfakes, Fraud, and Abuse. Covers definitions, detection limitations, U.S./EU/UK approaches, recent federal and state measures, and recommended controls for organizations handling synthetic media risks.
AI for Sales & CS: Practical Systems — Build Reliable, Revenue-Focused AI Workflows
A practical, step-by-step guide to designing and running AI systems for sales and customer success. This article covers what to solve, an actionable implementation workflow, required tools and data, common mistakes, mitigation for hallucinations and compliance, and FAQs to help you deploy AI that measurably improves rep productivity and customer outcomes.
AI for E-commerce: Practical Workflows to Drive Growth and Streamline Operations
A practical guide to implementing AI for e-commerce that focuses on repeatable workflows: data preparation, recommendation engines (embeddings + vector stores), personalization orchestration, experimentation, and operational controls. Includes tools, step-by-step tasks, risks, and monetization-focused use cases for growth and operating efficiency.
AI for Engineering & IT: Practical Automation Playbook for DevOps, SRE and Platform Teams
A hands-on guide to applying AI for Engineering & IT to automate routine DevOps, SRE and platform tasks. Learn concrete workflows for AIOps incident triage, AI-assisted IaC and automated unit-test generation, required tools, step-by-step setup, risks, and measurable guardrails to adopt automation safely.