Turn your prompt spreadsheet into a release packet.
PromptProof helps founder-led AI-agent teams convert prompt, retrieval, and tool-use regression cases into a human-reviewable pass/fail/delta packet before demos, pilots, and production updates.
Landing-page validation only. Human-reviewed release evidence, not a promise of automatic LLM grading.
release packet
213 cases · 17 deltas · 4 risky
Booking agent · refund path
Tool call changed arguments after model swap
Support copilot · billing answer
Expected disclaimer missing in 3 of 12 variants
Research agent · citation check
All source links preserved after retrieval update
Founder-ready summary
Every changed case links back to the prompt, transcript, screenshot, manual verdict, and release note so the team can ship or hold with evidence.
Narrow customer
Founder-led AI-agent startups and small LLM-feature teams with 50–1000 prompt, retrieval, or tool-use scenarios tracked outside a real QA system.
Paid problem
Model, prompt, or tool updates trigger days of manual regression work, subtle pilot failures, and founder/support time spent proving what changed.
Landing test
The waitlist tests whether teams will share redacted spreadsheet cases for a concierge regression packet before buying deeper automation.
Day-in-the-life pain
The prompt looked fine. The tool trace changed. The spreadsheet cannot explain why.
A founder tweaks a system prompt, swaps a model, adjusts retrieval, or changes a tool schema. The team has a spreadsheet of expected behaviors, a folder of screenshots, a few saved transcripts, and Slack messages from the last release. Before tomorrow's customer demo, someone must prove which cases still pass, which changed, and which failures matter.
Input
Upload the Google Sheet, CSV, YAML, or copied table that already holds prompts, tool calls, expected behavior, edge cases, owners, and current manual verdicts.
Review checks
PromptProof groups cases by workflow, captures actual outputs and screenshots, highlights changed behavior, asks for human verdicts where LLM judgment is unsafe, and keeps every risky delta visible.
Output
A release packet: pass/fail/delta summary, screenshots or transcripts, unresolved-risk queue, customer-demo notes, and a clean export founders can share before a pilot or production update.
Evidence-tied features
A regression evidence layer for the messy phase before mature eval infrastructure.
Sheet-to-run import
Start with the spreadsheet teams already use instead of requiring a code-first eval rewrite before the first release packet.
Human-verdict lane
Separate obvious passes from subtle output changes that need founder, PM, or domain-expert judgment.
Delta evidence capture
Attach transcripts, screenshots, tool traces, and issue links to each changed case so failures are not lost in Slack.
Pilot-ready summary
Export a concise packet for customer-success, enterprise pilots, or investor demos showing what was tested and what still needs review.
Concierge first run
Early waitlist users get one redacted regression-pack cleanup before any deep integration or automated judge is promised.
Proof and caveats
Public evidence points to spreadsheet regression. The waitlist tests willingness to share real cases.
The research is not proof of demand. It shows a repeated workflow: test cases in spreadsheets, manual verdicts, screenshot evidence, reporting overhead, and release fear. PromptProof starts as a service-like packet so the product is shaped by actual redacted artifacts, not generic QA assumptions.
Reddit · r/aiagents · spreadsheet regression scenarios
An AI-agent team described 1000+ scenarios tracked in spreadsheets, with every product update creating days of manual regression work. The post is promotional, but the workflow pain is concrete.
Open source →
Hacker News · LLM prompt testing
A practitioner described prompt testing as a spreadsheet of input, expected output, actual output, and manual evaluation. The subtle mistakes still need human review.
Open source →
Hacker News · manual QA evidence gathering
A common manual-QA pattern is a spreadsheet test matrix plus screenshots referenced from Google Drive — evidence and verdicts split across tools.
Open source →
Reddit · r/TestersForum · test cases, bugs, reports
QA engineers complained about scattered test cases, weak traceability, manual execution tracking, difficult coverage analysis, and reports that take longer than testing.
Open source →
Why not existing tools?
This is not trying to replace observability. It targets the spreadsheet gap before teams are ready.
Why not use an LLM eval platform?
Many eval platforms assume code-first instrumentation. PromptProof tests the spreadsheet-first buyer who needs a release packet this week, before observability plumbing is mature.
Why not automate all judging?
The evidence points to subtle mistakes and manual verdicts. PromptProof keeps humans in the loop instead of pretending every qualitative failure can be auto-graded.
Why not keep the spreadsheet?
Sheets hold rows, but they do not reliably preserve transcripts, screenshots, changed behavior, owner decisions, release notes, and customer-ready evidence in one place.
Who pays?
The buyer is a founder, product lead, or early QA owner at an AI-agent startup where one bad regression can damage a pilot or burn senior engineering time.
Early waitlist offer
Get one redacted regression packet before PromptProof becomes software.
Early teams will be asked for a sanitized case sheet. The validation signal is simple: do AI-agent teams care enough about this pain to share cases, review a packet, and ask for the next release run?