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AI Prompt Firewall for Codebases
Build a proxy and developer plugin that intercepts AI coding requests, detects sensitive code or secrets, and redacts or blocks risky content before it reaches external model providers. The product solves the immediate trust gap for teams that want AI productivity without handing over unrestricted repository context.
これが重要な理由
You want the speed of modern coding agents, but every prompt feels like a quiet data export. As soon as the tool scans your repo, you worry it will ingest proprietary logic, customer details, or credentials that were never meant to leave your environment. Existing secret scanners help after code is written, not at the moment an assistant is about to transmit context. So you end up choosing between productivity and control. A prompt firewall changes that by screening what the agent sees and what actually leaves your boundary, while preserving enough context to keep the assistant useful.
- · Software teams at startups and SMBs using external AI coding assistants but lacking enterprise-grade data controls.向けに構築。
- · 最も可能性の高い収益化モデル: SaaS subscription。
痛み · ナラティブ
You want the speed of modern coding agents, but every prompt feels like a quiet data export. As soon as the tool scans your repo, you worry it will ingest proprietary logic, customer details, or credentials that were never meant to leave your environment. Existing secret scanners help after code is written, not at the moment an assistant is about to transmit context. So you end up choosing between productivity and control. A prompt firewall changes that by screening what the agent sees and what actually leaves your boundary, while preserving enough context to keep the assistant useful.
スコア内訳
市場シグナル
市場投入
Engineering managers at 10-200 person software companies that already allow AI coding tools but need tighter controls for customer-facing codebases.
~50K-100K teams globally that are actively experimenting with AI coding in production environments
cold outbound
$99/month
10 teams install the proxy and 3 convert to paid within 30 days after a targeted outbound campaign
MVPの範囲 · 1～2週間
- Build a local proxy that accepts chat and code-completion requests and forwards them to one model API
- Add regex and entropy-based secret detection for common key formats
- Create a simple CLI wrapper that captures prompt text and attached file paths
- Store request metadata and redaction events in PostgreSQL
- Ship a minimal dashboard listing blocked and allowed requests by project
- Implement repository path allowlists and deny-lists per project
- Add PII detection for emails, phone-like strings, and customer identifiers
- Support masking sensitive spans instead of fully blocking requests
- Integrate one Git provider to map file sensitivity based on repo folders
- Launch a self-serve team settings page with policy templates
差別化
失敗する可能性がある理由
自己反論 — 最も重要な信頼のシグナル
- 1If masking or blocking removes too much context, developers will bypass the tool and return to unrestricted workflows.
- 2Security buyers may prefer broader existing platforms rather than a focused prompt-layer product.
- 3Native provider controls could improve fast enough to make third-party filtering feel redundant for smaller teams.
エビデンスの概要
AIがこのインサイトをどのように統合したか — 逐語的な引用はありません
A large share of the discussion centered on the idea that coding agents can sweep in an entire repository and retain that traffic longer than teams expect. Multiple commenters specifically worried about trade secrets, broad code exposure, and accidental reading of sensitive files. Others pointed to minimizing storage and reducing exposure as the only reliable defense, which supports demand for a software layer that filters prompts before transmission.
アクションプラン
コードを書く前に、この機会を検証しましょう
推奨する次のステップ
開発する
強い需要シグナルを検出。本物の課題と支払い意欲を確認 — MVPの開発を始めましょう。
ランディングページ文案キット
実際のRedditコメントから抽出したコピー、そのまま貼り付けられます
見出し
AI Prompt Firewall for Codebases
サブ見出し
Build a proxy and developer plugin that intercepts AI coding requests, detects sensitive code or secrets, and redacts or blocks risky content before it reaches external model providers. The product solves the immediate trust gap for teams that want AI productivity without handing over unrestricted repository context.
ターゲットユーザー
対象：Software teams at startups and SMBs using external AI coding assistants but lacking enterprise-grade data controls.
機能リスト
✓ Prompt and file-context interception via CLI or proxy ✓ Secret and PII detection with configurable block rules ✓ Repository-aware redaction and allowlists ✓ Audit logs showing what was sent, blocked, or masked ✓ Per-model policy routing to approved providers
どこで検証するか
r/HN · front_page にランディングページのリンクを投稿しましょう — そこがこの課題が発見された場所です。
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