Asher Atlas

Problem

We were launching the first-ever music livestreaming commerce platform with no users, no infrastructure, and no playbook. Midway through, internal load testing triggered by my own concerns revealed the platform would fail under festival traffic — and leadership resisted changing priorities.

The Hard Call

I had to choose between staying quiet and hoping the load wouldn't materialize, or persistently escalating until I changed the roadmap. I built a case with data, found internal allies, and kept raising the issue in every forum until I won the reprioritization.

What I Did

• Shipped the 0→1 livestream commerce platform: concept → live events → 100+ events, zero downtime
• Initiated load testing based on stakeholder estimates, found 2K cap with 8K expected
• Built internal alignment to push roadmap reprioritization against executive resistance
• Launched the Zoom Wall experiment: taped fan photos to a wall behind the artist to simulate virtual crowd energy; it validated the emotional gap before building Artist View
• Shipped Artist View: curated real-time fan message overlay for artists mid-performance

Problem

Board game discovery is messy — data is inconsistent, player constraints vary widely, and LLMs hallucinate when metadata is incomplete. I needed a system that could take vague inputs ("something fun for 5 players that's not too long") and return grounded, reliable suggestions.

The Hard Call

After shipping V1, I ran user tests and discovered the core assumption was wrong. I'd built a social recommendation system ("what other people liked") when users actually needed personal constraint matching ("what works for my group tonight"). Rather than patch V1, I rebuilt the architecture from scratch.

What I Did

Architecture

• V1: Built a full retrieval and reasoning pipeline (Flowise + GPT-4o-mini). Shipped, tested, discovered the core assumptions were wrong.
• Ran a 6-model head-to-head evaluation (latency, cost, consistency, reasoning quality) before committing to V2 stack
• V2: Redesigned as a 7-node hybrid pipeline: 5 deterministic constraint nodes (player count, complexity, game type, edition rules, catalog validation) + 2 LLM reasoning nodes
• Applied RICE prioritization under real cost constraints — cut scope to what moved the needle
• Built metadata enrichment flow to clean inconsistent fields and reduce hallucinations before LLM reasoning

Validation & Prioritization

• Discovered Discord/BGG beta testing was generating 100% S4/S5 signal; rebuilt user segmentation from 3 coarse buckets to a 6-segment framework with documented mental models, prompt patterns, and trust signals per segment
• Classified the full prompt log and bug backlog by actual target segment; built Bucket A/B triage: S3-affecting failures fix immediately, S4/S5-specific failures deprioritized from Day 1, redirecting ~40% of planned work
• Switched validation to Reddit r/boardgames; first round returned immediate positive S3 response and surfaced real gaps that Discord feedback had masked

Problem

A significant portion of our music catalog disappeared overnight due to licensing changes. Users couldn't find what they searched for, couldn't spend their credits, and were canceling. Support tickets spiked. We needed to stop the bleeding without the catalog back.

The Hard Call

The obvious path was to wait for licensing resolution and run damage control. Instead, I pushed for a structural fix: redesign search to surface discovery when exact matches fail, turning the missing catalog into a recommendation opportunity.

What I Did

• Proposed and led a Netflix-style fallback model: when a search fails, surface similar and trending albums instead of a dead end
• Added two region-specific features: "Most Purchased This Week" chart and a real-time "Last Purchased" ticker
• Managed alignment across design, engineering, and marketing to ship under pressure