Interviews
How an Enterprise Deployed 10,000 AI Agents: A Practitioner Interview
A Fortune 500 platform lead explains how 10,000 AI agents run in production: orchestration, model routing, AgentOps, evals, and the failures that shaped it.
Articles by Elliot Park
Interviews
Inside a Machine Learning Platform Team: An Interview with the Engineers Running 500+ Production Models
Five senior engineers on the team running 500+ production ML models share lessons on serving, monitoring for drift, governance, and cutting inference cost at fleet scale.
Interviews
Inside a 10,000-Seat Agent Deployment: How One Enterprise Operationalized AI Agents Across Its Teams
Most AI agent projects die quietly. The numbers in 2026 are blunt: about 88% of agent pilots never graduate to full production, and only around 11% of enterprises run an agent at genuine scale. Yet on
Interviews
Inside an Enterprise AI Platform Team: How One Company Scaled Agentic Automation Across the Business
Step inside one company's enterprise AI platform team and learn how they scaled agentic automation from scattered pilots to 50 governed, production workflows.
Interviews
In the Trenches: How One Team Cut Agent Hallucinations by 78% in Production
A fintech engineering lead shares the four-pillar playbook that cut production agent hallucinations by 78% — grounding, retrieval evals, guardrails, and abstention — plus the exact metrics they tracke
Interviews
Inside the AgentOps Trenches: An Interview with an Enterprise AI Lead on Shipping Production Agents
An enterprise AI lead gets candid about what it really takes to ship and operate production AI agents in 2026 — failures, evaluation, observability, guardrails, team structure, and the true cost of AgentOps.
Interviews
From 5 Evals to 5,000: Inside the QA Team Making Enterprise LLMs Trustworthy at Scale
The author is the QA Platform Lead on the Platform Engineering team, with 15 years in software testing and 6 years building LLM evaluation systems. All figures in this article come from internal run l
Interviews
"We Hit 10x Query Volume With Zero Latency Spikes": An SRE's AI Infrastructure Story
An SRE's real-world story of scaling AI inference infrastructure from baseline to 10x query volume — with zero latency spikes. Covers observability, KEDA autoscaling, semantic caching, and warm pool strategies.
Interviews
Inside Google's DeepMind: A Research Lead on Scaling Laws and What Comes After
Researchers at DeepMind spent seven years chasing the idea that intelligence scales. GPT-4, Gemini, Claude — these are children of scaling laws. But the researchers who built them are now asking: what happens when the scaling laws stop scaling?
Interviews
We Replaced Our Entire Data Labeling Team: A Manufacturing QA Director's Real-World AI Story
When I told our operations VP we were going to replace our entire data labeling team with AI, the first question wasn't "how?" It was "are you sure that's going to work?" Fair question. We had 14 peop...
Interviews
From Rule-Based Bots to Autonomous Agents: A Practitioner's 5-Year Journey Scaling Enterprise AI
The year was 2021. We had just launched our first "AI-powered" customer service bot — a sprawling decision tree of if-this-then-that rules, scripted responses, and keyword matching. In demos, it performed beautifully. Every conversation followed the happy path we had meticulously designed. Senior le
Interviews
How AI Agents Cut Our Sales Cycle from 6 Weeks to 11 Days
A B2B sales team deployed an AI agent stack and closed deals three times faster. Here is the exact workflow that made it happen, with real numbers.
Interviews
Building AI Products at Scale: A Conversation with ML Engineering Leaders
ML engineering leaders share hard-won strategies for scaling AI products in enterprise environments. Covers MLOps maturity, ROI measurement, agentic AI challenges, and organizational alignment.