
Vibe Coding to Engineered Workflow: A Practical Guide to AI Coding Agents
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Context Engineering for Coding Agents: CLAUDE.md, AGENTS.md, and Token Budgets
You correct the agent, it apologizes, and ten minutes later it makes the same mistake. That is not a model problem; it is a memory problem. Here is how the context window works as a budget, what belongs in CLAUDE.md and AGENTS.md, and when to restart a session instead of patching it.
Prompt Patterns for AI Coding Agents: Plan-First, Spec-First, and Anti-Patterns
Most prompt advice treats every task the same. Real tasks are not the same: a typo fix and a payment refactor need different prompts. Here are four patterns, a way to pick between them, copyable templates, and the anti-patterns that quietly wreck a run.
Loop Engineering: Tests as Guardrails and Verification Loops for AI Agents
An agent that has to prove its work catches its own mistakes. One that only has to look right ships them to you. This is how to build the feedback loop: the verification ladder, test-first prompting, and letting the agent iterate to green on its own without weakening your tests.
Git Guide for Vibe Coding as a Product Manager
Master the art of AI-assisted development with this comprehensive guide for Product Managers. Learn how to use vibe coding tools like Cursor, Bolt, and Lovable while maintaining clean Git workflows.
TOON vs YAML: Reduce LLM Token Costs & When to Use Each
Discover how TOON (Token-Oriented Object Notation) can reduce LLM token usage by 30–60% compared to YAML, and learn when to use each format for optimal performance and cost efficiency.




