In development 2026Find what to build before someone else does.
Building is easy now. Knowing what to build isn’t. Needler reads thousands of public developer conversations a day and turns real, repeated pain into software opportunities you can validate.
- Posts read
- ~12,000 a day
- Refresh
- Every 30 minutes
- Role
- Founder & engineer
Payout reconciliation for small SaaS
Founders doing their own books · today: spreadsheets
The problem
AI made building cheap, so the scarce part is knowing what is worth building. The best signal is people describing their own pain in public, but it is scattered across thousands of threads a day, buried between opinions, jokes and launch posts. Nobody has time to read all of it.
Use it to
- Pick your next side project from problems people already complain about.
- Check whether an idea you have is a pain many people share or just yours.
- See which workarounds people use today, so you know what you are competing with.
- Start validation with a one-page brief instead of a blank page.
What it does
Reads everything
New public posts and comments are fetched every 30 minutes, plus a 90-day backfill.
Separates pain from noise
A prefilter and an AI classifier keep real needs and drop opinions, hypotheticals and self-promotion.
Clusters the same need
Signals are embedded and grouped, so ten people describing one problem become one opportunity.
Scored on strength
Each opportunity shows how strong the signal is and why, so you can judge it yourself.
A brief, ready to validate
Problem, who has it, today’s workaround, desired outcome and a product idea, in one page.
Private by design
No usernames, no post text, no links on the public site. Only aggregates and the briefs derived from them.
Short jobs instead of a server
Trigger.dev starts a short task every 30 minutes. It reads the new public discussions since the last run, plus the previous hour again to catch comments that were indexed late. Inserts are idempotent and the cursor only moves after the posts are saved, so a crashed run simply repeats.
Most posts never reach a model
A deterministic prefilter runs first and discards the vast majority of posts with plain rules. Only the small rest goes to a language model, which keeps the pipeline fast and the data it stores small.
From comments to opportunities
Survivors are classified, then a larger model extracts the problem, who has it and the workaround. The normalized problem is embedded with bge-m3 and joins the nearest opportunity in pgvector, or starts a new candidate. A candidate only becomes an opportunity once several independent people describe it.
Privacy by construction
Usernames never reach the database, only a keyed hash, enough to count independent authors. Raw text is kept only for prefilter hits and expires. The public site shows aggregates and derived briefs, never post text, links or authors.