| Management number | 251696747 | Release Date | 2026/09/26 | List Price | US$8.00 | Model Number | 251696747 | ||
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<b>AI coding tools can get you 70% of the way to a working solution. The other 30% is where your code actually breaks, and where this book picks up.</b><p>You've been there. You prompt an AI agent, get back hundreds of lines of code that <i>look</i> perfect, and spend the next hour hunting down hallucinated APIs, flipped booleans, missing awaits, and security holes the tool planted with total confidence. The tests pass. Production doesn't.</p><p>The problem isn't the tool. It's the workflow. And nobody is teaching it.</p><p><b>The Last 30%</b> gives you the structured methodology that turns AI coding tools from impressive demos into reliable engineering tools. Whether you use GitHub Copilot, Cursor, Claude Code, Aider, or whatever ships next, the workflows in this book will make you dramatically faster <i>without</i> sacrificing the quality your users depend on.</p><p><b>After reading this book, you will: </b></p><p>- Instantly pick the right mode (chat, completion, or agent) for any task, instead of defaulting to whatever your tool shows first<br>- Set up context files that make every AI session 2 to 3 times more productive from the first prompt<br>- Break work into pieces the AI can actually execute well, with verification gates that catch errors before they compound<br>- Spot the seven failure modes unique to AI-generated code, the ones that survive code review and reach production<br>- Run a systematic refinement cycle that hardens AI output into code you'd stake your reputation on</p><p><b>Packed with immediately usable material: </b> </p><p>- A full chapter on context engineering, the single highest-leverage skill in AI-assisted development<br>- Real code examples showing exactly how AI fails, and the detection technique for each failure mode<br>- Three unvarnished project retrospectives with wrong turns, time estimates, and lessons learned<br>- A ready-to-use prompt library, security checklist, and a one-page cheat sheet<br>- A four-week team onboarding plan for engineering leads rolling out AI tools</p><p><b>This book is for you if: </b> You're a working developer, tech lead, or technical PM with deadlines and users. You've tried AI coding tools and sensed there's a gap between what they promise and what you're getting. You want a system, not tips. You want to ship faster <i>and</i> sleep at night.</p><p><b>Not for you if: </b> You're learning to code for the first time, or you're an ML researcher building the models themselves.</p><p><b>Built from three years of production use</b> across every major AI coding tool. Every workflow was tested on real codebases, real deadlines, and real users, not toy demos. This is the book the author wished existed when he started.</p><p><i>Stop debugging AI output. Start shipping with it.</i></p>
| Book format | Paperback |
|---|---|
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | April, 2026 |
| Pages | 146 |
| Subgenre | Computer Science |
| Series title | No Series |
| Number in series | 0 |
| Edition | 1 |
| Publisher | Amazon Digital Services LLC - Kdp |
| Language | English |
| Edu focus | Engineering |
| Features | Hypoallergenic |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.00 x 0.31 x 10.00 in |
| Assembled product weight | 0.58 lb |
| Bisac subject heading | Computers |
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