DevEx & Philosophy

Three ways Amplifier reduces API costs: prompt caching (90%), model selection (12x), and loop architecture (10x at scale).

Behavioral control through context injection, tool moderation, and visual feedback. /plan, /review, /explore - one command changes everything.

Structural enforcement of mode transition sequencing in the Amplifier modes system. How the framework ensures disciplined behavioral transitions and prevents mode state conflicts.

A mindful, decomposition-first approach to AI-assisted development. 4-5 planning turns, then one "go do it" turn. Ephemeral workspaces, implicit validation.

Structurally enforced disciplined development. Jesse Vincent's Superpowers methodology (43k+ stars) with Amplifier's mode tool policies, 5 specialist agents, 6 workflow modes, and 7 recipes with approval gates. Agents literally can't skip design, TDD, or review.

Live skills from obra/superpowers for continuous methodology updates, all 6 modes enriched with latest anti-rationalization and architecture guidance, recipe hardening with retry and staged composition, and leaner skill footprint (7 → 2 bundle-owned).

AI-augmented design research that asks "what is the user's brain doing?" instead of "what category is this?"

Adding expert perspective to automated validation. Document generation with design intelligence.

Building AI validators that actually work. When your validator agrees with the model 100% of the time, it's not validating — it's rubber-stamping. The rule that changed how we think about AI quality gates.

Lessons learned in developing multi-agent orchestration systems.

How one developer shipped 22 production features in a single day with AI-assisted development.

Building reusable, template-based Amplifier skills — a methodology extracted from the scaffold-new-service pattern.

A validation framework for verifying that AI specialists correctly implement their intended behavior.

How instruction design improved specialist chain reliability from ~40% to >90% without writing code.

Five principles and four quality tests for writing READMEs that work for humans and AI alike. Paste your README into an AI — if it misrepresents your project, the README isn't clear enough.

A single brainstorming session that redefined how we think about building with AI. What happens when you use AI for the messy, creative work before the first line of code.