Journal
Insights
Notes on AI systems, architecture, and shipping software.
Jul 14, 2026 · 2 min
Building a Moat for AI Products: Data, Workflow, Distribution, and Trust
Why model access is not a moat—and how AI product companies build durable advantage with proprietary data loops, workflow depth, distribution, and trust architecture.
Read →
Jul 14, 2026 · 2 min
AI Product Strategy for Software Companies: Build, Buy, or Embed
Strategic choices for software businesses adding AI—net-new AI products, embedding AI into existing suites, partnering, and portfolio prioritization.
Read →
Jul 14, 2026 · 2 min
How to Improve AI Product Quality: Evals, Feedback Loops, and Human-in-the-Loop
A practical quality system for AI products—offline evals, online feedback, sampling, HITL design, and when to change prompts vs models vs data.
Read →
Jul 14, 2026 · 2 min
From AI Demo to Production Product: The Improvement Roadmap Teams Skip
The stages after a shiny demo: reliability, evals, UX for uncertainty, cost control, security, and ops—so your AI feature becomes a product customers keep.
Read →
Jul 14, 2026 · 2 min
AI SaaS Pricing Models That Work: Seats, Usage, Outcomes, and Hybrid Plans
How to price AI products without lighting money on fire—token pass-through traps, seat vs usage, outcome pricing, free tiers, and enterprise packaging.
Read →
Jul 14, 2026 · 2 min
How to Validate an AI Product Idea Before You Write Code
A founder-friendly validation playbook for AI products: problem interviews, fake-door tests, wizard-of-oz MVPs, willingness to pay, and kill criteria.
Read →
Jul 14, 2026 · 2 min
How to Evaluate and Version Prompts: From Guesswork to a Prompt Library
Build a professional prompt workflow: golden datasets, offline evals, A/B tests, semantic versioning, and ownership so AI features improve instead of randomly drifting.
Read →
Jul 14, 2026 · 2 min
Prompt Injection and AI Security: How to Protect LLM Apps and Agents
Understand direct and indirect prompt injection, data exfiltration via tools, and practical defenses for chatbots, RAG, and agents in software products.
Read →
Jul 14, 2026 · 2 min
RAG and Prompt Engineering: Grounding AI Answers in Your Company Knowledge
How retrieval-augmented generation works with prompts: chunking, citations, refusal behavior, and why “just fine-tune” is often the wrong first step.
Read →
Jul 14, 2026 · 2 min
Prompt Engineering for Business: Marketing, Sales, Support, and Operations
Ready-to-adapt prompt playbooks for GTM teams—campaign briefs, sales emails, support macros, meeting notes, and SOPs without brand or compliance disasters.
Read →