Chapter Summary: Building with AI¶

Key Takeaways¶

Progress through levels deliberately: Five levels exist—autocomplete, generation, iteration, agents, orchestration. Teams that advance one level every 2-4 weeks succeed. Teams that jump two levels regress within a month. Level 4 agents show 35% task correctness improvement over copilots, but 95% of enterprise multi-agent pilots at Level 5 fail.
Match tool to task, not workflow to tool: Four categories serve different contexts—inline autocomplete for boilerplate, chat for architecture discussions, IDE-integrated for codebase-aware work, CLI agents for autonomous tasks. 49% of organizations use multiple tools intentionally. Yirifi uses three: quick edits with autocomplete, feature work with agentic CLI, architecture in chat.
Own architecture, delegate typing: The Human-AI Development Loop—Decide, Draft, Review, Refine, Finalize—keeps humans on strategy while AI handles execution. Skywork AI completed 6 months of planned development in 3 weeks using this pattern. The 8 patterns (context first, concrete examples, iterative refinement, architecture ownership, test-driven prompting, error escalation, checkpoint commits, ruthless review) close the 43-point gap between perceived and actual productivity.
Recognize failure patterns before they compound: Six patterns—hallucinated APIs, incorrect assumptions, style drift, over-engineering, security blindness, context loss. Of 2.23 million code references, 440,445 hallucinated dependencies; 43% repeated enough for attackers to exploit. The Three-Strike Rule: more context, different approach, then manual takeover.
Prevent debt instead of remediating it: Code duplication increased 8x since AI adoption. Code churn doubled to 7%. Living documentation in prompts reduces naming violations by 60%. Prevention costs 10-20% of budget; remediation consumes 40-60% of maintenance. Schedule 20% of dev time explicitly for debt paydown.

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