This was a campaign run in December 2025 to test the ability to deploy an entire documentation workflow daily using only AI and without any manual intervention. See the final results here.
Day 22 of 31
Introducing the article-spec-pack pipeline that powers this entire campaign.
Live Day 02Swap the sci-fi shorthand for a working definition of AI you can actually use.
Live Day 03Why AI works differently than every other tool you useāand why that matters.
Live Day 04Four copy-paste AI prompts for developers, project managers, creatives, and learners.
Live Day 05AI doesn't know what it doesn't know. Learn to spot hallucinations, bias, and verify facts.
Live Day 06AI has no long-term memoryālearn to manage context windows and keep the model on track.
Live Day 07Structure your prompts with Context, Role, Instruction, and Task Format for professional outputs.
Live Day 08Make the model think before it talks using CoT, RAG, and ReAct to handle complex work without hallucinations.
Live Day 09A practical framework to match models to the job across speed, depth, and cost tradeoffs.
Live Day 10Use AI as a critical thinking partner to falsify assumptions and debug faster.
Live Day 11Durable principles for working with AI so you can adapt as models and tools change.
Live Day 12A three-stage view of pre-training, fine-tuning, and RLHFāand what each stage explains about hallucinations and overconfidence.
Live Day 13Multimodal AI in real workflows: screenshots, diagrams, and evidence-first prompting.
Coming Soon Day 14How to turn a generic first draft into something specific using constraints and proof artifacts.
Coming Soon Day 15Design prompts like interfaces: inputs, constraints, outputs, and verification.
Coming Soon Day 16Turn messy threads into briefs, compare options, and run pre-mortems that catch failure early.
Coming Soon Day 17Practical guardrails: prompt injection fences, tool contracts, and evidence-based answers.
Coming Soon Day 18A clear gate for when to use AI, when to keep humans in charge, and when to say no.
Coming Soon Day 19How to design safe agents with scopes, receipts, and verification habits.
Coming Soon Day 20How to make your AI workflows durable: interfaces, evals, and a āplan, patch, proveā loop.
Coming Soon Day 21Sometimes you just need a quick fixāfast levers to pull for immediate output upgrades.
Coming Soon Day 22A useful frame: math over mind-readingāa mental model that matches how the machine actually behaves.
Coming Soon Day 23MoE is one of the most important scaling ideas in modern language models.
Coming Soon Day 24Long context doesn't remove the need for structureāit increases it.
Coming Soon Day 25Most AI problems that feel like "model quality" are really systems problems.
Coming Soon Day 26You tested with three prompts, it looked greatāthen you shipped without evals.
Coming Soon Day 27Retrieval doesn't make the model truthfulāit gives it more plausible text to be wrong with.
Coming Soon Day 28You give a model a toolāthen one day it does the thing you did not mean.
Coming Soon Day 29In incident response, the goal is a sequence of safe, reversible steps that reduce uncertainty.
Coming Soon Day 30The goal is docs that behave like a product: versioned, reviewable, and tested against reality.
Coming Soon Day 31Final reflection (manual release).
Coming Soon