Report

You are strongest when you turn messy live founder-event feedback into concrete product direction, and your main next step is tightening the validation loop so more of those decisions land cleanly on the first or second pass.

What You Built

You evolved 2035App/Cafe2035 into a production event platform for founder events.

The work included event-scoped onboarding and workspaces, founder/admin auth, organizer access, scoring and rescoring controls, LinkedIn/PDF/screenshot proof flows, Slam Week invites, circle matching, admin diagnostics, AI cost reporting, public event reports, and production operations on Vercel/Supabase/OpenAI/Anthropic.

You worked through Claude Code and Codex CLI. Your role was not just “prompting.” You supplied product direction, security corrections, scoring policy, UX acceptance criteria, and deployment decisions while the agents supplied implementation speed.

Decision Patterns

Your decision-making style is product-led and architecture-heavy: 46 of 59 tracked decisions were in architecture, while the most common decision type was product_insight. The strongest pattern is Workflow from User Backwards, which appeared 22 times and means you start from the user’s desired experience, then force the implementation to fit it. Trace the Input appeared 5 times, showing you diagnose issues by following data through systems, including OpenAI cost investigations, LinkedIn scan failures, event-specific matching, and Supabase warnings.

What’s interesting here is the gap between decision volume and verified outcomes. Product_insight decisions led to positive outcomes in 8 of 39 tracked cases, strategic_redirect decisions in 1 of 8, technical_catch decisions in 0 of 11, and option_selection in 0 of 1. That does not mean the decisions were bad. It means your first correction often identifies the right direction, then needs a tighter prove-it loop to finish the job.

Strengths

You have unusually strong product taste under live feedback. You consistently turn vague pain into concrete UI requirements: one-screen-per-ask onboarding, inline Slam Week RSVP login, founder-readable admin cards, no-scroll mobile layouts, and reports that feel public-facing rather than internal.

You supervise AI agents instead of trusting them blindly. You rejected unsafe database access, corrected auth architecture, stopped accidental coding, challenged bad billing outputs, asked for production verification, and added a scoring owner to the Claude agent roster before approving it.

You are comfortable operating production systems. You investigated OpenAI billing discrepancies and token spikes, revoked suspected keys, audited Supabase warnings read-only, handled Vercel preview/production mismatches, and required production-tested demo generation instead of accepting localhost-only validation.

Growth Areas

Tighten the validation loop after product and architecture decisions. Only 9 of 59 tracked decisions led to positive outcomes, including 8 of 39 product_insight decisions and 0 of 11 technical_catch decisions. For decisions like billing output fixes, AI lab login and Ask AI behavior, matching visibility, and LinkedIn scan repair, add a small explicit “done means” check before moving on: production URL, affected record, expected UI state, and one failure case.

Convert your testing expectations into broader automated coverage. You did request strong tests in specific sessions, especially LinkedIn-less onboarding and fallback-score elimination, but the repository snapshot shows a test-to-code ratio of 0.06 by lines and 18 test files. Keep the same instinct, then make it systematic: every scoring, auth, proof, billing, and event-state change should leave behind at least one regression test.

Improve commit and change-history discipline. The period shows high shipping velocity, but only 13% conventional commits, and the repo had 9.6 commits/day across 46 active days. With production auth, scoring, billing, and event-state work moving this fast, clearer commit prefixes and smaller logical commits will make rollback, audit, and bisection much easier.