CHAPTERS
Sherwood’s second time in YC: why he’s returning now
Sherwood Callaway joins to discuss coming back to Y Combinator after exiting his first YC company. He frames this as a very different experience from his first, remote (COVID-era) batch and sets up the motivation to introduce his new company, Sazabi.
- •Second-time YC founder returning for a new company
- •Contrast with first YC experience being remote
- •Desire to re-enter YC with a clearer, more aligned mission
- •Positioning Sazabi’s launch to the broader YC community
What Sazabi is: AI-native observability that answers production questions
Sherwood explains Sazabi as an AI-native observability platform built for fast-moving engineering teams—like a modern Datadog/Sentry reimagined for an AI-first world. The product goal is to replace hours of manual debugging with an interface where teams can ask direct questions about production and quickly reach root cause.
- •AI-native observability designed “as if built in 2026”
- •Targets the painful, manual workflow of debugging outages/bugs
- •Natural-language queries like “Why is prod down?” and “Which customers/commit are affected?”
- •Focus on speeding root-cause analysis and resolution using AI agents
“Logs are all you need”: the manifesto and the bet against the three pillars
Sherwood presents Sazabi’s controversial principle: you can do observability well using logs alone. He argues logs are the simplest to instrument and interpret, and that modern AI makes unstructured logs far more machine-readable and useful than in the past.
- •Challenges the traditional “logs, metrics, traces” three-pillar approach
- •Instrumentation overhead of three pillars is a major burden for teams
- •Logs are the simplest developer primitive (print/read) and align with Occam’s razor
- •AI agents can extract structure and insight from unstructured log lines
Brex observability origin story: scaling microservices and getting “observability-pilled”
Sherwood recounts moving from frontend into infrastructure/DevOps and joining Brex early as one of the first infrastructure engineers. As Brex scaled to many Kubernetes microservices owned by different teams, production understanding became difficult—leading to formal observability work and a strong belief that production is fundamentally unpredictable.
- •Early career shift from frontend to CI/CD and infrastructure reliability
- •Joined Brex around employee ~70; helped build hypergrowth foundations
- •Microservices sprawl created a “what’s happening in prod?” problem
- •Observability as the core tool for answering production questions under uncertainty
What he built at Brex: auto-instrumentation, Datadog configuration, and SLO adoption
He details the practical scope of observability engineering at Brex: standardizing telemetry, building pipelines to capture/forward it, and operationalizing dashboards and monitors. He also highlights driving SLO/SLI practices so teams can consistently measure reliability and performance.
- •Auto-instrumentation across services for logs/metrics/traces
- •Telemetry capture and forwarding infrastructure
- •Deep configuration and operational use of Datadog modules
- •Dashboards, monitors, and SLO/SLI adoption across teams
Leaving Brex to found a startup: long-held YC ambition and pandemic catalysis
Sherwood describes wanting to build a YC-backed company since his bootcamp days in San Francisco, influenced by startup culture and Hacker News. During the pandemic in New York, he and his roommate/co-founder began exploring ideas seriously, leading to their first YC application.
- •Bootcamp exposure seeded the ambition to do a YC startup
- •Relocation to New York and pandemic downtime created space to ideate
- •Co-founder chemistry and desire to build together
- •Applied to YC and began the founder journey
Opkit’s original idea: voice AI for healthcare revenue cycle workflows
Sherwood explains Opkit (YC Summer ’21) as a healthcare voice AI effort focused on automating calls to insurers. The product targeted high-friction operational tasks like eligibility checks, prior authorizations, and claim-status calls—domains with heavy phone-based processes.
- •YC S21 company: Opkit
- •Voice/LLM agents to automate insurer phone calls
- •Use cases: eligibility, prior auth, and claim status checks
- •Entered a large but highly specialized healthcare operations market
Why healthcare—and the misalignment: choosing a market by “case study,” not founder-fit
He traces the rationale for healthcare: personal proximity via his father (a doctor) and the belief that verticalized fintech could be a big wave. In hindsight, he calls it a more MBA-style market selection—driven by perceived opportunity rather than deep personal insight or passion—leading to slower progress and strategic doubt.
- •Healthcare familiarity came mostly through his dad and accessible interviews
- •Hypothesis: healthcare as a huge vertical for “vertical fintech”
- •Retrospective: idea choice wasn’t grounded in founder strengths or passion
- •Key advice: build from prior expertise; you likely have more edge than you think
How Opkit evolved—and unraveled: SaaS RCM, a human call center, then early LLM voice agents
Opkit shifted from RCM SaaS to leveraging LLMs for call QA/data extraction and eventually a voice agent, supported by a Philippines-based call center. Despite building early and technically challenging voice automation, fundraising traction waned, prompting a re-evaluation of whether to continue.
- •Built RCM SaaS for insurance verification and claims submission
- •Discovered critical ops still required phone calls with insurers
- •Ran a Philippines call center; used LLMs for QA and data extraction
- •Pivoted to LLM voice agents; later faced lukewarm investor interest and runway pressure
Exit path and next stop: joining 11x to get closer to AI product velocity
After deciding Opkit wasn’t the right long-term bet, the team explored acquirers; many felt like “more of the same” in healthcare/fintech. They chose to join 11x (an AI sales tech company) where they could work on fast-growing AI voice products with familiar connections.
- •Decision to stop fundraising and pursue acquisition/soft-landing options
- •Healthcare/fintech acquirers felt like continuing the same work
- •Joined 11x due to momentum, AI focus, and a known CTO connection
- •Goal: move closer to the frontier of AI products
The insight behind Sazabi: AI is transforming coding—but debugging is still manual
At 11x, Sherwood rebuilt a major product, then returned to on-call and maintenance realities: setting up Datadog again and debugging via the same painful workflows he’d always used. That contrast—futuristic AI development with outdated incident response—crystallized the opportunity for AI-native observability and made Sazabi feel like the “perfect” founder-market fit.
- •Rebuilt 11x platform, then shifted into maintenance/on-call mode
- •Observed the persistent pain of manual production debugging
- •Recognized observability as the next domain to be transformed by AI agents
- •Founder-market fit: infra + dev tools + AI + prior founder experience
Why do YC again: acceleration, culture of shipping, and distribution to every software company
Sherwood explains returning to YC despite already being in the network: the market window feels time-sensitive and YC’s cadence can force speed and commercialization. He also wants YC’s cultural pressure toward shipping and sees YC companies as natural early customers because every software company needs observability.
- •Time-sensitive opportunity; wants maximum acceleration
- •YC creates deadlines and a ship-fast operating cadence
- •Avoids the trap of “engineering forever” without go-to-market
- •Distribution: selling observability into YC peers and batchmates; in-person experience this time
Founder lessons and hiring: long-horizon integrity, and the team to build the “Linear of observability”
Sherwood emphasizes startups as a long-term compounding game where relationships matter and integrity pays off later. He closes with what Sazabi needs in hires: high-agency tool-lovers (often ex-founders), strong infra/data/storage expertise, and product/design-minded engineers to deliver a modern, elegant observability experience.
- •Startups are long-horizon; relationships compound across years
- •Be good to people—future fundraising/recruiting depends on trust
- •Hiring profile: high agency, fast learners, flexible self-starters; ex-founders valued
- •Roles: infra/data/storage + full-stack; emphasis on great UX (“Linear of observability”)
