Applied AI Enablement · Buyer & Hiring Playbooks
Playbooks
Plain-language implementation guides for founders, operations leaders, L&D directors, and hiring managers putting agentic workflows and LLM quality gates into daily production.
Hiring an Applied AI Enablement Lead: A 30-60-90 Day Playbook for Team Adoption
What an Applied AI Enablement Lead actually ships in the first 90 days: workflow audits, self-checking agent pipelines, cross-family quality gates, and staff playbooks that turn shelfware seats into daily output.
Enterprise AI Workflow Audit Checklist: Ranking Tasks by Payoff, Risk & Checkpoints
A practical four-step checklist for auditing team operations before writing automation code: mapping real inputs, pricing silent errors, placing human checkpoints, and killing low-payoff pilots early.
Self-Reviewing Agentic Workflows: Designing Pipelines Non-Technical Teams Trust
How to replace fragile single-shot prompts with four-stage self-checking workflows: deterministic Python pre-gates, narrow drafting nodes, cross-family critics, and SHA-verified audit receipts.
LLM-as-a-Judge Calibration: Stopping Self-Bias, Verdict Flips & Silent Truncations
How to calibrate LLM-as-a-Judge panels against human expert baselines: binary decomposed rubrics, cross-vendor panels, golden-set agreement checks, and catching silent HTTP 200 truncations.
SOP-to-SCORM AI Pipeline: Compiling Policy Docs into Verified LMS & QTI Modules
How corporate L&D and compliance teams turn static SOPs and runbooks into ADL SCORM 1.2 packages, QTI 1.2 item banks, 300-DPI guides, and narrated 1080p lessons with 0% policy drift.
6-Rung LLM Cost & Latency Routing: Cutting Enterprise Token Spend Without Losing Quality
Why a tiny fraction of agent calls burn 80% of your API bill, and how a 6-rung policy router shifts routine checks to zero-token Python hooks and fast mid-tier models.
AI Curriculum & QTI Assessment Quality Control: Blind-Solver Checks & Zero Answer Leaks
Engineering-grade quality control for EdTech and enterprise assessment pipelines: catching ambiguous distractors, standards drift, hint answer leaks, and broken math rendering before students see them.
Two-Week AI Workflow & QC Sprints: Moving Stalled Pilots into Daily Team Use
How founders and operations leaders use a fixed-scope two-week sprint to audit one high-friction bottleneck, deploy a self-checking workflow with human checkpoints, and keep the runnable QC harness.
Live 3-Model Edge Pipeline · Try It On Your Stack
Test an open role or broken workflow right now.
Paste a job description or a messy team process. Three separate model families on Cloudflare Edge AI decompose the friction, wire a 4-node self-checking workflow with human checkpoints, and audit single-judge blindspots in ~6 seconds.