Tutorial Running Delivery

Running delivery

The practical core: the twelve steps, bolts and boards, cutting delivery time, reviewing AI-written code, setting and proving the bar, launching safely, cost, guardrails, governance, drift and postmortems.

13 lessons · about 85 minutes · Boards, bolts, launches and the bill

Every lesson opens on the site, where the pictures are live and the text is searchable: start this track ↗, or pick a lesson.

#	Lesson	What it covers	Time
1	How to Run an Agentic AI Project: A Step-by-Step Playbook	Twelve steps from a vague request to an AI agent in production that someone can defend: who owns each step, what it produces, and what is never delegated.	7 min
2	Bolts vs Sprints: Planning Work When AI Writes the Code	When AI builds a story in hours, a two-week sprint leaves it idle. How to plan in bolts: one unknown each, cut by dependency, integrated the same day.	6 min
3	How to Set Up a Kanban Board for an Agentic AI Project	A project board for AI agent delivery: evidence as the exit rule for every column, risk bands as swimlanes, and WIP limits set by review capacity.	7 min
4	Cut Delivery from Months to Weeks: What Shrinks, What Won't	AI makes building fast; delivery is more than building. What compresses, what compresses only by design, what never compresses, with the arithmetic for each.	7 min
5	How to Review AI-Generated Code: By Risk, Not by Diff Size	When agents write most of the code, review is the bottleneck. How to band changes by what they touch, route readers by band, and halve a review queue.	6 min
6	How Accurate Does an AI Agent Need to Be? The 3-Step Answer	An AI agent's accuracy bar comes from money, not a round number: divide the damage of a wrong answer by the saving of a right one, per slice.	7 min
7	Is 82% Good Enough? How to Prove an AI Agent Meets Its Bar	A score from a test set is an estimate with a width. How to report the lower bound, count the cases a slice still owes, and give a verdict a sceptic accepts.	6 min
8	Shadow Mode and Canary Releases for AI Agents, Step by Step	How to launch an AI agent safely: run it in shadow beside the people doing the job, cut over at 5% per action, widen on evidence, and rehearse the way back.	7 min
9	Why Your AI Agent Costs 4× the Estimate, and How to Fix It	An AI agent's bill rarely has one cause: context, model tier, cache and retries multiply. How to find each in the per-call log and fix them in order.	7 min
10	AI Agent Guardrails That Hold: Why a Prompt Is Not a Control	A limit in a prompt can be talked past; a limit in a tool's signature cannot. Six controls that make an AI agent's boundaries real, with a test for each.	7 min
11	AI Governance Gates That Don't Slow Delivery: The Five Gates	Five gates govern an AI agent from idea to wide use: intent, plan, behaviour, release and expansion. Who owns each, and the evidence each one needs.	6 min
12	AI Drift: How to Catch the Defect With No Error Message	AI drift is behaviour changing with no deploy and no error. Why accuracy alerts arrive late, what to watch instead, and the two thresholds that catch it.	6 min
13	Postmortems for AI Incidents: Find the Missing Control	An AI incident postmortem asks which enforced control would have made it impossible, not who was careless. Five moves, from the layer table to the brief.	6 min

← Methods decoded · All tracks · By role →

Teaching it? Session 5 · Plan and review · Session 6 · Prove and ship · Session 7 · Govern and scale in the Cohort Kit turn this track into ninety-minute sessions.

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