Why AI-First Product Development is the Future
My thesis on why the future of software development starts with AI agents, not IDE plugins. MicroSaaSBot is proof of concept.
17 posts tagged with "ai"
My thesis on why the future of software development starts with AI agents, not IDE plugins. MicroSaaSBot is proof of concept.
How I built a multi-agent bug bounty hunting system with evidence-gated progression, RAG-enhanced learning, and safety mechanisms that keeps humans in the loop.
Announcing MicroSaaSBot—the AI system that takes ideas from validation to deployed MVP with minimal human intervention. It built StatementSync in one week.
The full pipeline from 'I have an idea' to 'it's live on Vercel with Stripe billing.' Every phase explained with the real StatementSync timeline.
The validation phase that prevents building products nobody wants. Market research, persona scoring, and the go/no-go decision that saves weeks of wasted effort.
Deep dive into MicroSaaSBot's multi-agent architecture: Researcher, Architect, Developer, and Deployer agents working in sequence to ship SaaS products.
How I validated a bookkeeper pain point and shipped a working SaaS in 7 days using MicroSaaSBot. The story of StatementSync from idea to production.
The case for keeping humans in control when building AI-powered security tools. Full automation sounds impressive until your reputation tanks from false positives.
Master Claude Code with quality gates, context management, and evidence-based workflows. The comprehensive guide to building with AI that doesn't break.
ADHD's dopamine-seeking behavior drives continuous learning and early adoption. This 'shiny object syndrome' is actually technology scouting for the AI era.
Why I chose multi-agent architecture over monolithic scanners, and how evidence-gated progression keeps findings honest. Part 1 of 5.
Why mandatory human review protects researcher reputation better than any algorithm. Building AI that knows when to stop. Part 5 of 5.
The psychology of skipping verification and how forced evaluation achieves 84% compliance. Evidence-based completion for AI-generated code.
The workflow that prevents context amnesia. Dev docs let Claude pick up exactly where it left off after compaction. Here's the system.
A two-gate mandatory system that blocks implementation until quality checks pass. Here's how it works and why 'should work' is banned.
Loading less context upfront makes AI more effective. Here's the 3-tier system that cut my Claude costs while improving output quality.
RAG combines LLMs with real-time data retrieval to provide accurate, up-to-date responses. Learn how RAG works and why it matters for AI builders.