<p><em>Zack Reneau-Wedeen</em> is the Head of Product at Sierra, leading the development of enterprise-ready AI agents — from Agent Studio 2.0 to the Agent Data Platform — with a focus on richer workflows, persistent memory, and high-quality voice interactions.</p><p><br></p><p>How Sierra Does Context Engineering, Zack Reneau-Wedeen // MLOps Podcast #350</p><p><br></p><p>Join the Community: </p><p><a href="https://go.mlops.community/YTJoinIn" target="_blank" rel="ugc noopener noreferrer">https://go.mlops.community/YTJoinIn</a></p><p>Get the newsletter: <a href="https://go.mlops.community/YTNewsletter" target="_blank" rel="ugc noopener noreferrer">https://go.mlops.community/YTNewsletter</a></p><p><br></p><p>// Abstract</p><p>Sierra’s Zack Reneau-Wedeen claims we’re building AI all wrong and that “context engineering,” not bigger models, is where the real breakthroughs will come from. In this episode, he and Demetrios Brinkmann unpack why AI behaves more like a moody coworker than traditional software, why testing it with real-world chaos (noise, accents, abuse, even bad mics) matters, and how Sierra’s simulations and model “constellations” aim to fix the industry’s reliability problems. They even argue that decision trees are dead, replaced by goals, guardrails, and speculative execution tricks that make voice AI actually usable. Plus: how Sierra trains grads to become product-engineering hybrids, and why obsessing over customers might be the only way AI agents stop disappointing everyone.</p><p><br></p><p>// Related Links</p><p>Website: <a href="https://www.zackrw.com/" target="_blank" rel="ugc noopener noreferrer">https://www.zackrw.com/</a></p><p><br></p><p>~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~</p><p>Catch all episodes, blogs, newsletters, and more: <a href="https://go.mlops.community/TYExplore" target="_blank" rel="ugc noopener noreferrer">https://go.mlops.community/TYExplore</a></p><p>Join our Slack community [<a href="https://go.mlops.community/slack" target="_blank" rel="ugc noopener noreferrer">https://go.mlops.community/slack</a>]</p><p>Follow us on X/Twitter [@mlopscommunity](<a href="https://x.com/mlopscommunity" target="_blank" rel="ugc noopener noreferrer">https://x.com/mlopscommunity</a>) or [LinkedIn](<a href="https://go.mlops.community/linkedin" target="_blank" rel="ugc noopener noreferrer">https://go.mlops.community/linkedin</a>)] </p><p>Sign up for the next meetup: [<a href="https://go.mlops.community/register" target="_blank" rel="ugc noopener noreferrer">https://go.mlops.community/register</a>]</p><p>MLOps Swag/Merch: [<a href="https://shop.mlops.community/" target="_blank" rel="ugc noopener noreferrer">https://shop.mlops.community/</a>]</p><p><br></p><p>Connect with Demetrios on LinkedIn: <a href="https://www.linkedin.com/in/dpbrinkm/" target="_blank" rel="ugc noopener noreferrer">/dpbrinkm</a></p><p>Connect with Zack on LinkedIn: <a href="https://www.linkedin.com/in/zackrw/" target="_blank" rel="ugc noopener noreferrer">/zackrw/</a></p><p><br></p><p>Timestamps:</p><p>[00:00] Electron cloud vs energy levels</p><p>[03:47] Simulation vs red teaming</p><p>[06:51] Access control in models</p><p>[10:12] Voice vs text simulations</p><p>[13:12] Speaker-adaptive turn-taking</p><p>[18:26] Accents and model behavior</p><p>[23:52] Outcome-based pricing risks</p><p>[31:40] AI cross-pollination strategies</p><p>[41:26] Ensemble of models explanation</p><p>[46:47] Real-time agents vs decision trees</p><p>[50:15] Code and no-code mix</p><p>[54:04] Goals and guardrails explained</p><p>[56:23] Wrap up</p><p>[57:31] APX program!</p>