Tutorial Running Delivery - akash-coded/aws-bedrock-agentcore-strands GitHub Wiki
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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