SaaS ideas your next customers are already looking for
100 SaaS startup ideas for the people who said they'd pay, from agency owners to dentists. Micro SaaS ideas, AI SaaS ideas and B2B SaaS ideas: find yours, build it, sign them up.
Popular:
| # | Idea |
|---|
No idea matches this filter.
Pain points in business: what people struggle with
Search the problems to solve, as people described them on Reddit and other platforms, in their own words.
Popular:
| # | Pain point |
|---|
No pain point matches this filter.
Manual Failure Triage
Engineers waste hours manually triaging noisy logs, CI failures, and vague bug reports to find root causes instead of getting automated diagnosis and routing.
In their words
Does a production failure automatically make it worth adding to your eval suite, or do you have a filter?
It is not common but sometimes there is corruption in database... the team has never been able to reproduce the problem.
answering it means manually stitching three tools by user id and timestamp
they run into one stumbling block and just stop trying ... half my job is determining what the right data is
Whenever a build fail, it search all the logs (multiple files over 200MB of raw text logs, cooking, compiling, shaders, symbols etc..)
the weird other error on your S2S that you can’t track down but prevents the application going in
frontend code written by ai will compile, render, look totally normal, and then some state thing three components deep just stops working
giving it access to system log and crashdump files to figure out why a system crashed. Saves me hours of looking at system logs.
it’s very very hard to catch all corner case issues, especially for such large volume devices
Every error monitoring tool we've used treats Spring like a black box. The moment your code enters a transaction boundary or an async thread, context disappears.
performance problems remain hidden until the scene becomes more complex
these extensions are undocumented and secretive and developers are at a loss to self-support
I spent about $200 on openai tokens today to solve a seriously hard distributed systems problem that would have taken me probably three weeks to understand, let alone fix.
when one of them hits a bug they don't know what a console log is — I get "it's broken" over email
Software and DevOps engineers
Where they talk
- r/AI_Agents
- r/devops
- r/SaaS
- r/ClaudeCode
- r/LLMDevs
- r/Observability
- r/LangChain
- r/sre
Tools they use today
- Claude
- PostHog
- Claude Code
- GitHub Actions
- Sentry
- Slack
- Crashlytics
- GitHub
Why those fall short
- AI fixes add -ErrorAction SilentlyContinue, masking errors
- treat Spring as a black box; context disappears at transaction boundaries and async threads
- Procmon shows calls but not why; vendors are clueless; recommended deployments refused
- instructions get lost in noise past 200K context
- weird other error on your S2S that you can’t track down
Map of ideas
Drawing the map…