Steven M. Ledbetter

(845) 379-0641

NYC Area, NY

Summary

Product leader who builds PM teams and ships developer tooling. 20 years as a PM, 10 in management, and three acquisitions. I've led product and design teams of 17+, creating and shipping models driving real revenue. I've built design-to-code handoff processes at 5 companies, and I publish LLM evaluation research on data analysis, code synthesis, and verifying agent tool calls.

Employment

Meta

2023 – 2026

Product Management Lead, AI & Data Infrastructure

  • Worked with Meta's enterprise advertisers to develop and ship a novel OLAP system with real-time freshness, <100ms latency, 10M QPS, 10x capacity savings, and $1Bil+ in new revenue in 6mo.
  • Scaled Meta's real-time metrics and analytics warehouse to absorb 100x agentic-workload traffic in a year while tightening latency and freshness SLAs.
  • Led the transition of org-wide planning with Design, Program, Engineering, and UXR from 6mo cycles to a continuous, code-context aware system that increased productivity by >30% in 90 days.
  • Co-led the PM org's transition to agentic workflows with new calibration and career development criteria.

Supernatural (acquired by Meta)

2022 – 2023

VP of Product

  • Led a team of 17 PMs & UXR to make what Business Insider called 'the one life-giving product from Meta'.
  • Grew the business 3x ARR with 2x user retention with a suite of behavioral science-based features.
  • Guided product through a successful acquisition by Meta and data compliance audits by the FTC.
  • Created the PM hiring and training systems that led to top 10% job satisfaction scores for PMs at Meta.

Elevate Security (acquired by Mimecast)

2020 – 2022

VP of Product

  • First product hire; built the Product and Design Team including PMs, POs, Designers, and Technical Writers.
  • Pivoted the company to new products for security engineers that 2x ARR with less than 5% churn before acquisition by Mimecast.
  • Co-inventor on patent US12149553B1, ML behavioral risk-scoring and intervention system to prevent social-engineering attacks.

Tonal

2018 – 2020

Director of Product Management, Engagement

  • Developed the workout experience, coordinating across design, hardware, firmware, software, and content teams.
  • Created the evaluation criteria for the motor control firmware responsible for weight feel.
  • Increased engagement 2x and grew NPS to 80+ by implementing Motivation Science education and metrics across the coaching, product, and design teams.

Habitry (acquired by Lift The Bar)

2013 – 2018

CEO, Head of Product, Co-Founder

  • Co-founded, raised funding, and built the first CRM iOS app for health coaches.
  • Grew the team to 12 and developed multiple applications for health care and insurance customers.
Writing — smledbetter.com/writing

Structure Beats Scale (2026) — Structured review outperforms brute-force generation in LLM code synthesis.

Receipt-Gated Pipelines (2026) — Cryptographic verification of tool-call claims in multi-agent LLM systems.

Open Source Projects — github.com/smledbetter

CandidBench

https://candidbench.dev

Open benchmark that measures whether an LLM data agent is trustworthy, not just capable.

  • Designed and coded 49 tests to evaluate LLM data agents on real-world tasks.
  • Defined the annotation pipeline and quality metrics for agent output that separate answers safe to delegate from confident errors.
  • Shipped as a developer kit: an adapter contract to plug in any agent, a submission checker, the grader source, and a checksum-verified dataset on Hugging Face.
  • Used by teams at accounting firms and AI startups to evaluate frontier models and coding harnesses.

Flowstate

https://github.com/smledbetter/flowstate

Observability platform for agentic code development. Tracks metrics, gate-failure signals, drift detection from design to shipped code.

  • Sustained 97% prompt-cache hit rate across 130 sprints in 16 projects. Only ~3% of per-sprint tokens are new work, enabling an 842M-token single-operator agent-dev pipeline.
  • Pre-registered factorial experiments; killed 2 of 3 proposed workflow changes after measuring a 10–13% noise floor.
Skills

Product Leadership — three acquisitions, patent co-invention, infrastructure org transitions

AI & LLM Agents — Anthropic SDK, Claude Code, MCP, eval design, prompt caching, tool-call verification

Product Design — Figma, prototyping, design systems, design-to-code handoff

Front-End Development — HTML, CSS, JavaScript, Astro

Machine Learning — LLM-as-judge, drift detection, factorial design, noise-floor calibration

Education

Master's, Sport Psychology — John F. Kennedy University (2014)

Bachelor's, Philosophy — University of Chicago (2004)