Own the definitional queries teams ask before they turn a plain-English question into something an AI actually runs against a database.
Target query: what is SQLFix
SQLFix turns a plain-English question into a dialect-aware SQL query with a plain explanation, then screens it with a deterministic safety ruleset for injection, unguarded writes, and dialect errors. It is a drafting and review aid, not a guarantee of correctness.
refs: https://www.postgresql.org/docs/current/ · https://owasp.org/Top10/A03_2021-Injection/
Target query: how to write SQL from plain English
Describe your question, optionally paste a schema, pick a dialect (Postgres/MySQL/SQLite/BigQuery), read the explanation, and review the safety findings before copying. The screen flags destructive and injectable patterns; it does not guarantee the query is right.
refs: https://dev.mysql.com/doc/
Target query: common mistakes in AI generated SQL
The recurring errors are a write with no WHERE, SQL injection from string concatenation, wrong dialect syntax, and ambiguous joins. SQLFix flags the dangerous ones; review still matters because it does not guarantee business-logic correctness.
refs: https://owasp.org/Top10/A03_2021-Injection/ · https://www.postgresql.org/docs/current/
Target query: best SQL generator tools
Pick on dialect support, plain-English explanation, safety screening, and exportable audit. A deterministic screen that flags unguarded UPDATE/DELETE is the dimension free chat drafts skip — and the one that matters near production data.
refs: https://www.sqlite.org/docs.html · https://cloud.google.com/bigquery/docs
Target query: SQLFix FAQ
Straight answers on supported dialects (Postgres/MySQL/SQLite/BigQuery), how the safety ruleset flags injection and unguarded writes, the free tier, and when a qualified reviewer should still own the run.
refs: https://www.postgresql.org/docs/current/
Long-form, cited explainers. Each carries 2+ authoritative SQL / database sources and a decision-support disclaimer.
The recurring errors in AI-generated SQL — missing WHERE on writes, injection via string concatenation, wrong dialect syntax, ambiguous joins — and how a deterministic safety screen flags them.
What to look for in a SQL generator — dialect support, explanation, safety screening, export, and audit — and how to match a tool to your risk profile.
The main ways to turn a plain-English question into SQL — general chat models, IDE AI features, open-source text-to-SQL models, and a data analyst — with the trade-offs of each.
Straight answers to the questions people ask about SQLFix — supported dialects, how the safety ruleset works, the free tier, and when you should still bring in a database reviewer.
The people who get the most from natural-language-to-SQL — analysts pulling their own numbers, developers drafting queries, support engineers, and students learning SQL — and the tasks it fits.
An honest comparison of SQLFix against general chat LLMs and SQL IDE autocomplete — what each does well, and where a deterministic safety screen changes the outcome.
SQLFix turns a plain-English question into a correct, dialect-aware SQL query with a plain explanation, then screens it with a deterministic safety ruleset before you copy it.
A step-by-step for turning a plain-English question into a dialect-aware SQL query with SQLFix — describe, pick a dialect, read the explanation, and check the safety findings.
Publish + syndicate per gtm-launch (IH + GEO indexes). Each post carries 2+ authoritative refs.