FrictionLens

FrictionLens is an AI review intelligence tool live at frictionlens.net. Designed and shipped end-to-end (marketing site, dashboard, shareable Vibe Report pages) by directing AI development tools on Next.js, TypeScript, Supabase (Postgres + RLS + Edge Functions), Google Gemini, and Upstash Redis. The strategic bet: indie developers can't read every review, but the patterns that actually predict churn are buried in 2-3 star reviews. The hard part of shipping an AI tool isn't the AI. It's the unit economics.

Two problems made the obvious "summarize reviews with an LLM" pitch hard. First, naively sending every review through Gemini blows past free-tier limits in a single analysis, killing the freemium model the indie audience actually needs. Second, a black-box sentiment score is magical but useless: engineering needs to know what to fix, not how angry users feel.

1. 01

   LLM cost curves: routing every review through Gemini collapses the $0 freemium tier

2. 02

   Generic sentiment scores don't tell engineering what to ship

3. 03

   Indie tools die without a distribution channel; no marketing budget

4. 04

   Trust: black-box AI feels suspicious to the audience that's most cost-sensitive

5. 05

   Free Gemini API has 10-RPM limits; naive batching fails immediately

1. 01

   Cost-Aware Classifier Design

   Made cost-efficiency the primary product constraint before any model selection. Benchmarked classifier tiers against Gemini API cost curves to stay within free-tier volume across typical review workloads. The whole architecture exists to answer "how do we ship this for free?"

2. 02

   3-Tier Routing (Not Embeddings)

   Short reviews → keyword + star rules, no AI. Medium → keyword sentiment, no AI. Long batches → Gemini with Zod-validated structured outputs and 6.5s inter-batch throttling for the 10-RPM free-tier limit. Roughly 80% of reviews never touch the AI.

3. 03

   BYOK Architecture

   Built bring-your-own-key with AES-256-GCM encrypted per-user key storage so power users run unlimited analyses on their own Gemini key while the freemium tier serves curious visitors on 2 free runs. Lets the tool stay $0 forever without a paywall.

4. 04

   Vibe Reports as Distribution

   Designed shareable public Vibe Report pages with OG-image generation so every user sharing their report becomes acquisition. No ad budget, no growth team: the product itself is the distribution channel.

5. 05

   Marketing Site as Proof of Taste

   Designed and shipped frictionlens.net (positioning, type pairing, motion, the search-driven hero) alongside the product so the landing page IS the demo. One cohesive thing, not "marketing site eventually."

1. 01

   Cost-efficiency as the primary product constraint, not a backlog item

   Context

   Every "AI review analyzer" pitch deck assumes you can afford the API calls. The freemium model collapses in a week if every analysis costs $0.40. Treating cost as the first design constraint changed every downstream architectural choice.

   Outcome

   Stayed within Gemini free-tier limits for typical workloads, making the $0 forever tier real. The architecture is the moat, not the model choice.

2. 02

   3-tier rule-based classifier over embeddings or always-AI

   Context

   Embedding-based clustering is the "smart" move but adds latency, infrastructure, and cost. Always-AI is simpler but kills the freemium economics. Rule-based routing is none of the above but lets ~80% of reviews skip AI entirely.

   Outcome

   Short reviews resolve instantly with no API call. Long reviews still get the Gemini treatment with Zod-validated structured outputs. Free tier survives a real workload.

3. 03

   BYOK with AES-256-GCM, not a SaaS subscription

   Context

   The audience is indie devs, exactly the people who will run from a $29/mo subscription. A BYOK path lets them bring a free Google AI Studio key and run unlimited analyses.

   Outcome

   Pricing page reads "Free for indie devs. $0 forever." That positioning is only honest because the BYOK path exists.

4. 04

   Shareable public Vibe Report pages with OG-image generation

   Context

   Indie tools without a marketing budget need built-in distribution. Every share of a Vibe Report needs to look good as a link preview, not as a generic URL.

   Outcome

   Each Vibe Report is a public URL with a custom OG image showing the app icon, vibe score, and top friction. Sharing becomes acquisition.

Live at frictionlens.net. Full-stack ship across marketing site, dashboard, and shareable report pages. 3 classifier tiers running. 4 review sources unified (App Store, Play Store, Reddit, CSV). 256-bit AES-GCM per-user key encryption. Freemium tier holds because the architecture earns the right to be free.