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Preswald – AI Data Engineer in VSCode for Local Testing, Metrics

Hacker News

Preswald – AI Data Engineer in VSCode for Local Testing, Metrics

Hey HN, We're rolling out Preswald: an AI data engineer that lives inside VSCode. The goal is to make setting up and managing your startup metrics stupid simple—all from your editor, without adding SaaS tools, dashboards, or extra steps. Why? Most early-stage teams cobble together metrics using SQL, Python scripts, manual exports, and spreadsheets. We built Preswald to simplify that whole mess and keep it close to where engineers are comfortable: in their codebase. What Preswald Does: Local Testing: Write your SQL or transformation scripts directly in VSCode and test them locally before deploying. Preswald provides real-time validation and sample output previews to cut down the cycle of query-run-fix-repeat. Code Completion and Suggestions: Preswald autocompletes data transformations in SQL, helps with joins, checks your references, and prompts for missing details. It understands common patterns like churn and activation rates—no need to reinvent the wheel or dig through notebooks. Lightweight Analytics in VSCode: Get metrics like retention or churn set up in minutes, without exporting to another environment. Preswald can show sample metrics outputs as you work—helping you spot mistakes before they compound into bad analysis. Automation, Versioned in Code: Define your pipeline in pipeline.yml and deploy directly with preswald deploy pipeline.yml. No complex cron jobs, no broken scripts—Preswald automates ingestion, transformation, and delivery in a clean workflow. If something breaks, Preswald tells you what happened and suggests fixes. How it Works: Built on SQL Parsing and AST Analysis: Preswald analyzes your queries using abstract syntax trees to identify patterns and inefficiencies. It helps prevent redundant calculations or inconsistent joins and gives you suggestions to fix them. Real-Time Feedback: As you type in VSCode, Preswald generates inline comments, suggesting better SQL snippets, missing joins, or potential optimizations. We want to reduce the manual back-and-forth between writing queries and discovering runtime errors. Who It’s For: - If you’re a founder or part of a small team, Preswald can be your missing data engineer—saving you time that would otherwise be spent manually maintaining metrics. - If you’re a data engineer, this keeps your analytics in one place, gives you better version control, and helps automate testing and verification locally, all while reducing the tool overhead. Why VSCode? Everyone’s already in VSCode, so we figured, why create yet another dashboard? Preswald tries to bring the data engineering workflow into the same place you write the rest of your code, treating metrics setup like part of the codebase rather than a separate, duct-taped mess. We’re launching in private beta right now. If this sounds like something you could use, you can sign up for early access here: preswald.com We’d love your thoughts or feedback.

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Product HuntOn track for Day 1 leaderboard · Strong signals: using, code · Missing: mac, agents, macos
95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: mistakes, para · Missing: supports, reddit linkedin, podcasting
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, pipe, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: reviews · Missing: plus, platform, intuitive
28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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