Dmitry Alexeenko

Runway made 5 engineering hires through Paraform - including former Principal Engineers from Twilio and Snowflake.   Runway is a collaborative financial planning platform founded by Siqi Chen (former Head of Product at Zynga, VP Growth at Postmates) and Arya Asemanfar (ex-Twitter, Mixpanel, Lightstep).   In the last 18 months, they've gone from $150K to $4M in ARR and 200+ customers. By the end of 2026, they're eyeing $6M ARR. They move fast, run lean, and don't compromise on talent.   Every Runway engineer works on product that customers use to simulate and make multi-million-dollar decisions. The bar is high by design.   "We aren't looking for volume, we're looking for precision. We need people with real technical depth, strong product instincts, and the kind of ownership mindset that only thrives in a startup environment." - Annie Wu, Head of People & Operations   But Runway didn't want to scale internal recruiting just to keep pace. And traditional agencies historically couldn't hit their bar. Candidates were either missing on technical skills or not ready for a startup environment.   Instead of expanding internal recruiting or relying on traditional agencies, Runway used Paraform to access specialized engineering recruiters.   “Our POC, Emma, is a strategic partner who pushed us on calibration when market trends shifted, helping us tighten our process in real time. That kind of proactive partnership is what lets us keep raising the bar for talent and stay competitive in the market.”   Since kicking off, Runway has made 5 engineering hires - including 2 Staff Engineers, formerly at Twilio and Snowflake. Those hires now contribute directly to core product initiatives, from strengthening modeling infrastructure to supporting new AI-enabled functionality.   They've since expanded their search with Paraform to Forward Deployed Finance Partners and already made one successful hire with us.   "Rather than building internal sourcing capacity from scratch every time hiring spiked, we can dial recruiting support up when needed - and dial it back down when our priorities or needs shift." - Kirill Klimuk, Head of Engineering Read more about Runway's success with Paraform in the comments.

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Early on at NodeShift we made a decision that slowed us down for months. We built the anonymization layer before we built the flashy features. My instinct from product teams was to ship something demo-able fast. The regional reality forced a different order. No bank in the UAE was going to let us near their data because we had a slick assistant. They needed proof that a prompt with sensitive information could be masked, sent, and the response re-mapped, with a full audit trail behind it. The lesson stuck with me. In regulated markets, trust is the feature. Everything else is decoration on top of it. If we had built the assistants first and the governance second, we would have a beautiful product nobody in this region could legally use. Building the boring foundation first was the only thing that made the rest possible.

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A few years ago we taught LLMs to answer. Now agents must act inside our systems. Are they a strategic necessity or a temporary bridge? My view: necessity, but only when treated as an integrated service rather than a demo. What consistently works in production: • governed access to sensitive data and clear purpose limits • event-driven orchestration with retries and SLAs • least-privilege actions with full audit trails Healthcare example: an ambient scribe connected to the EHR reduces administrative load and eases burnout because notes flow from microphone to policy layer to EHR with human verification. Fintech example: an agent on the event bus monitors orders and positions and triggers compliance before clearing, not in end-of-day reports. Analyst consensus shows momentum, yet many agent initiatives are canceled when integration and measurable value are weak. Integration beats novelty. Which patterns have worked best for you: event bus, BPMN-style orchestration, or a tool-former stack tied to domain APIs? What broke, and why? #AI #AIAgents #AgenticAI #LLM #MLOps #SystemsIntegration #HealthcareIT #Fintech #CTO #EngineeringLeadership

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