Posts tagged #aiproductdevelopment
strategy•
AI Unit Economics for Founders: Model Size, Thinking Effort, and Your Margins
Model size sets the price per token; thinking effort sets how many tokens you burn. Here is how founders building AI products can model cost per task before pricing.
product•
What Founders Can Learn from One-Line Corporate Training
A one-line request that produces a finished training video shows how AI products win: remove setup work. Here is what founders building AI can take from the pattern.
product•
Building AI Transcription Products Founders Can Trust
Fluent AI output can quietly rewrite names, numbers and quotes. What founders building AI products should design in so users can trust transcripts.
product•
Why AI Founders Should Build on Existing Company Knowledge
A founder's look at a product pattern worth studying: AI that starts from the knowledge a customer already has instead of asking for another upload. What it means for AI product development.
product•
Context Is the Product: A Founder's Guide to Building AI Features
For founders building AI products, the model is rarely the differentiator. The context your app packs around each prompt is. Here is how to think about it and what to decide early.
product•
Designing AI Products That Say "I Don't Know": A Founder's Guide
Most AI models guess instead of admitting uncertainty. For founders building AI products, designing for honest "I don't know" responses is a trust advantage. Here is how.
agents•
Building AI Agents as a Founder: Why Source-Grounded Beats Prompt-Only
A founder's framework for building AI agents users can trust: ground them in verifiable sources, give them memory, and define a narrow role with guardrails.