Log what worked and what failed
Enter what AI assistance sped up this cycle and what had to be redone, alongside review time and any incidents it caused.
AI-ASSISTED DEVELOPMENT
AI Coding Retrospective Generator
Turn one AI-assisted development cycle into a structured retrospective: what worked, what failed, and what to change next time.
- Uses your inputs in a transparent calculation
- Instant result with practical next steps
- No signup required
Planning guidance only. Validate important decisions with customer evidence and your delivery team.
YOUR INPUTS
Build your result
Complete every field. The result updates only when you choose Calculate.
How it works
We classify the cycle's outcome
Review time, unreviewed-trust level, and incident count combine into a strong, mixed, or high-risk read on the cycle.
Get a targeted next-cycle change
The result carries your stated process change forward and pairs it with next steps matched to this cycle's outcome.
Continue learning: Remote debugging for distributed MVP teams · When to stop validating and start building
Frequently asked questions
How is this different from a general sprint retrospective?
A sprint retro covers the whole team's work. This tool is scoped specifically to AI-assisted coding: how much AI output needed rework, how much the team trusted it unreviewed, and how many bugs traced back to AI-generated code.
Why does unreviewed trust level affect the score in the opposite direction I'd expect?
A team that always reviews AI output before merging (low self-reported unreviewed trust) is running a safer process than one that frequently merges without review, even if trust feels like a positive word. The score rewards review discipline, not blind confidence.
What if this was our first AI-assisted cycle and we have nothing to compare it to?
That's fine — score review time and incidents against how the same work would normally go, using your best estimate. The value is in creating a documented baseline for the next cycle's retrospective, not a comparison against last time.
Does a high score mean we should use AI more?
It means this cycle's process — review discipline, incident rate, and time saved — held up well. Whether to expand AI use is a separate decision that should also weigh the type of work and its risk if something goes wrong.
Is this a replacement for a full team retrospective meeting?
No. It's a fast structure to walk into a retrospective with data already organized, not a substitute for the team discussion itself.
How We Compare
| Feature | MVPHub | Notion | Linear |
|---|---|---|---|
| AI-coding-specific retrospective structure | Included | Not included | Not included |
| Outcome-based next-step generation | Included | Not included | Not included |
| Long-term documentation storage | Not included | Included | Limited |
| Team issue tracking integration | Not included | Limited | Included |
Notion stores retrospective notes long-term and Linear tracks the resulting issues, but neither is scoped to AI-assisted coding specifically. MVPHub generates the initial structured review and prioritized process change before either tool is used.
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