Stop treating AI like a magic wand. Start treating it like a junior dev that needs a structured workflow.
When you throw a complex requirement into a single prompt, you're asking the AI to architect, code, and review simultaneously. It fails because of context dilution.
This framework is Chapter 4 of the Senior Dev Accelerator.
The 'Context Dump.' Feed the AI your existing patterns, limitations, and tech debt. Let it ask you 5 questions before it writes a single line of code.
Request a technical specification, not code. Review the AI's plan for edge cases, performance bottlenecks, and architectural alignment.
Execute in small, verifiable chunks. No mega-prompts. Learn the "strangler fig" approach to prompt execution for 100% accuracy.
Critique the AI like a senior dev reviewing a junior's PR. Use automated testing and systematic validation loops to catch hallucinations.
"The Discovery Phase alone saved me 3 hours yesterday. I used to just paste error messages; now I feed the AI the 'Why' before the 'What'."
"Phase-based coding is the difference between a senior dev and a prompt engineer. My code quality is indistinguishable from manual work."
"I finally stopped getting random hallucinations. The Implementation Phase techniques make Cursor feel like it's actually in my head."
Large Language Models have "reasoning loss" as prompt length and complexity increase. By splitting work into phases, you maintain 100% focus on the specific logic at hand, drastically reducing hallucinations.
In the first 10 minutes, yes. In the total project time, it's 3-5x faster. Most devs waste hours 'fixing' AI code that was built on a bad foundation. Phased prompting ensures the foundation is perfect.
Absolutely. These are mental models, not tool-specific hacks. Whether you're using Cursor's Composer, GitHub Copilot, or raw Claude/GPT-4o, the phases remain the gold standard for senior output.
The Prompting Phases framework is just 1 of 12 chapters designed to turn you into an AI-accelerated senior engineer.
Get Instant Access ($79.99)