Thoughts, articles, and resources on software development, SaaS, and digital growth.
The researcher is not being replaced by AI. They are being amplified. Why the best AI research tools make you look smarter, not redundant, and why research begins and ends with human judgment.
Embedding a user's question and searching for similar text sounds right. For formal documents like regulations, contracts, or technical standards, it systematically retrieves the wrong content. Here is the problem, and a technique that solves it.
Most AI research tools get the pipeline backwards. They apply language models to raw, unfiltered data and call the output intelligence. Here is why sequence matters more than model quality, and what a well-ordered pipeline looks like in practice.
Dashboards are easy. Orchestration is hard. When your intelligence data lives in Notion, Reddit, Typeform, and PDFs simultaneously, keeping it aligned is an engineering problem, not a product one. Here is how we build the central nervous system.
Legacy scrapers break silently. Filings change structure. APIs deprecate fields. Reliable intelligence requires pipelines that detect these failures automatically and trigger corrective action before a human notices the gap.