ProductGive an LLM the table of contents before you give it embeddings
Ex-Microsoft engineer reading every public tender in Romania
DataDriven serves tender documentation to AI assistants as structured markdown with an explicit table of contents and chapter hierarchy, and retrieval walks that structure first, using semantic search as a supplement rather than the foundation. Mihai distrusts embeddings-only RAG for long official documents, where a naive similarity search returns fragments stripped of the context that gives them legal meaning. Guided navigation, find the right chapter, then read it properly, mirrors how a careful human reads a contract, costs fewer tokens, and fails more predictably. The broader point for anyone building on LLMs is that documents already contain an information architecture, headings, sections, numbering, and throwing it away to chunk-and-embed is destroying signal you paid to OCR. Preserve structure, navigate it explicitly, and reserve embeddings for the queries structure cannot answer.
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Mihai NegreaRead the source documents, because official classifications lie
Public tenders in Romania carry official CPV codes, a taxonomy of roughly 10,000 subcategories, and Mihai found the labels wrong often enough to be dangerous, including food accessories classified under laptops. So DataDriven ignores the metadata and reads the actual tender documentation, OCRing PDFs and scans, then classifies everything against a hand-built taxonomy of about 180 categories that mirrors how companies really describe their work. That is the product's core advantage: competitors who filter on the official codes inherit the errors, and their users miss winnable contracts. Whenever your product sits on top of someone else's data, ask whether the labels are trustworthy or just convenient. Going to the primary source is expensive, which is exactly why doing it becomes a moat.
Mihai NegreaAn AI translation layer can shrink a database migration from months to days
Migrating from Cosmos DB to MongoDB is the kind of project that haunts a solo founder, so Mihai turned it into a verification problem instead of a rewrite. He had Claude build a translation layer for his queries, then ran the old Cosmos path and the new Mongo path in parallel, with automated validation comparing outputs until the two systems agreed on everything. Once parity held, the cutover was boring, and the whole thing took two to three days. The pattern generalizes beyond databases: when replacing a load-bearing component, do not aim for a heroic big-bang rewrite, aim for a shim that lets old and new run side by side while machines check the diff. AI assistants are unusually good at generating exactly this kind of mechanical translation code that nobody wants to write by hand.
Mihai NegreaAsk for thirty characters at signup and do the setup for the user
DataDriven's onboarding asks one thing: at least 30 characters describing the tenders you care about. AI converts that sentence into monitoring criteria, so the first login shows relevant results instead of an empty dashboard and a configuration wizard. Behavior then tunes the filters automatically, thumbs up and down, saves, navigation. Some users resist even that single question and want to see the app first, but Mihai holds the line, because without the sentence the first session shows noise, and the first session is where churn is decided. The general principle: do not make users configure your product, make them describe their problem in their own words, then configure it for them. One honest question plus AI setup beats a five-step wizard that gets skipped.
Mihai NegreaDesign the company around the life you need, even if that means no cofounders
Mihai came out of a burnout at Microsoft with a hard constraint: he needed to remove obligatory human contact from his working life for a while. So he designed the company around that constraint, no cofounders, no employees, full control over every product decision. The standard advice says find a cofounder, split the load, hire early, but standard advice optimizes for growth, not for the founder staying functional. A company shaped around your actual capacity is one you can run for years; a company shaped around a template is one you abandon. Constraints like health, energy, and tolerance for people are real inputs to company design, not weaknesses to overcome. Decide what you need to stay in the game, then build the business that fits inside it.