Conferences / QCon
QCon San Francisco 2026
Nov 16–18, 2026 · Hyatt Regency San Francisco (Embarcadero), San Francisco, CA, United States Announced
- Conference
- QCon Software engineering
- Dates
- Nov 16, 2026 – Nov 18, 2026
- Venue
- Hyatt Regency San Francisco (Embarcadero)
- Place
- San Francisco, CA, United States
- Format
- In person
- Status
- Announced
- Attendance
- —
- Website
- qconsf.com
- Recorded
- 31 sponsors · 94 speaker appearances
- Notes
- Conference Nov 16-18, trainings Nov 19-20, 2026 (Hyatt Regency San Francisco, Embarcadero). Program as published on qconsf.com/schedule/nov2026 on 2026-11-08; 12 sponsored-session placeholders and a few talks with no speaker named yet are omitted. Sponsors from the live sponsors page. Sponsorship packages not published (contact sales; InfoQ media kit linked).
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Conference (3 days), early | $2,995 | Nov 10, 2026 | qconsf.com | |
| Conference (3 days) + Trainings (2 days), early | $4,430 | Nov 10, 2026 | qconsf.com | |
| Video-Only Pass | $590 | — | qconsf.com | |
| Trainings only - 2 days | $1,490 | — | qconsf.com | |
| Conference (3 days), after Nov 10 | $3,250 | — | qconsf.com |
Sponsors 31
Speakers and talks 94
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Charlotte Mestwerdt | Bravely Amsterdam | Keynote | The Execution Muscle: Why Great Teams Are Built, Not Hired | — |
| Laura Savino | Adobe | Keynote | Learning Out Loud (Under Near-Existential Pressure) | — |
| Manju Rajashekhar | Mad Labs | Keynote | The Harness Is the New Operating System | — |
| Plum Ertz | Ro | Keynote | Game Time: How to (Unsuccessfully) 10x in a Week & (Successfully) 10x in a Year | — |
| Aarti Gupta | Netflix | Speaker | Stop Fighting the Remodel: API Design for Models That Outgrew Their Boundaries | — |
| Abhinav Sinha | Lucidic | Speaker | Skills, Memory, or Fine-Tuning? The Engineering Loop Behind Production Agents | — |
| Adam Bender | Speaker | No More Small Systems, How AI May Bring Large System Problems to Everyone | — | |
| Adam Berry | Netflix | Speaker | Growing Engineers in the Era of Agentic Coding | — |
| Adam Hicks | groundcover | Speaker | Notes From 300 Installs Inside Someone Else's Cloud | — |
| Aditya Patil | Endor Labs | Speaker | Architecting Security into the Agentic SDLC | — |
| Adrian Hatch | Antithesis | Speaker | Trust, but Verify: Delivering Quality with Agentic Workflows | — |
| Alex Mann | Apollo Graph | Speaker | Platform Engineering’s Second Act: From Vending Machine to Passport Control | — |
| Almog Gavra | Responsive | Speaker | How to Build Online Systems with Object Storage | — |
| Amanda Walker | Speaker | Agentic Trust: Securing AI Agents in Production | — | |
| Ammar Khaku | Netflix | Speaker | Building a Migration Platform: Moving 100+ Netflix RDBMS Workloads to Aurora PostgreSQL | — |
| Andrew Finch | Sonar | Speaker | Building a Safe Software Factory | — |
| Andrew Hatch | Cisco | Speaker | Adapt or Drift: Resilience Engineering When AI Moves the Operating Point | — |
| Andy Liang | Lucidic | Speaker | Simulating the Universe, 100 Times Over: Engineering Highly- Concurrent Agent Testing | — |
| Anirban Chatterjee | Sonar | Speaker | Code is abundant, Confidence is Scarce: What 1K Devs Say about Coding with Agents | — |
| Anvit Sinha | Lucidic | Speaker | Simulating the Universe, 100 Times Over: Engineering Highly- Concurrent Agent Testing | — |
| Ayushi Singh | Netflix | Speaker | Orderly Keys, Wild Values: Adaptive Compression for Distributed Key-Value Storage | — |
| Ben Segal | Parasail | Speaker | Efficient GPU Agents: Infra for Autonomous LLM Perf Optimization | — |
| Brandon Waselnuk | Unblocked | Speaker | Your Agents Lack Context: Here's How to Fix 'You're absolutely right!"' | — |
| Brian Douglas | Paper Compute Co | Speaker | Dreams on Paper: How Agents Learn from Experience | — |
| Brian Yang | OpenAI | Speaker | Lessons from Building a $100M Product in Six Weeks at OpenAI | — |
| Caio Sousa | Nu | Speaker | AI Amplifies Everything, Including Your Mess: Lessons from Delivering with AI at Global Scale | — |
| Chris DeMars | TuxCare | Speaker | The Men in Black Know What's in Your JavaScript and How to Fix it! | — |
| Chris Kelly | Harness | Speaker | Drawing the Rest of the Owl: A Blueprint for Your Software Factory | — |
| Dan Wolf | BlackRock | Speaker | Inside Asimov: BlackRock’s Platform Architecture for Applied AI at Scale | — |
| Daniel Weeks | Databricks | Speaker | Iceberg V4: The Next Chapter in Table Formats | — |
| Denny Lee | Databricks | Speaker | Multi-Agent Coding with Omnigent | — |
| Diane Lin | Datadog | Speaker | LLM Flip-Flops: From Reliability Risk to a Hill-Climbing Signal | — |
| Drew Breunig | Cmpnd | Speaker | Avoiding Prompt Debt & Other Context Failures | — |
| Em Ruppe | Twilio Segment | Speaker | What Is Incident Severity, but a Lie Agreed Upon? | — |
| Emmanuel Paraskakis | Level 250 | Speaker | Everything I Knew About Developer Experience Is Wrong for Agents | — |
| Evelyn Hur | Databricks | Speaker | Multi-Agent Coding with Omnigent | — |
| Fawziyah Alebiosu | Imprint | Speaker | APIs That Can't Afford to Be Wrong: Lessons from Moving Money | — |
| Gwen Shapira | Nile | Speaker | When Your Users Are Agents: Lessons from a Distributed Postgres Platform | — |
| Hamel Husain | — | Speaker | The Revenge of the Data Scientist: Why Reliable AI Needs Evals, Traces, and Metrics | — |
| Hari Sunder | Yugabyte | Speaker | Your Agents Have Amnesia: Lessons from Building a Memory Layer for Multi-Agent Systems | — |
| Holden Karau | Snowflake | Speaker | Breaking Down the Walls to Python & Big Data + AI Performance with Transpilation and LLMs | — |
| Jacob Murphy | Speaker | Live Resharding Without Regret: Lessons from Building Valkey's Atomic Slot Migration | — | |
| Jay Moorthi | Roblox | Speaker | Generation Got Cheap, Trust Didn’t: Scaling Agentic Changes from Prompt to Prod at Roblox | — |
| Jeremy Castile | GitKraken | Speaker | Feeling Faster Isn’t a Metric: Measuring AI’s Real Engineering Impact | — |
| Jeremy Tian | Lucidic | Speaker | Model-Harness Co-Training: Data-Driven Optimization Toward Pareto-Optimal Agents | — |
| Jerry Peng | Databricks | Speaker | Apache Spark: Structured Streaming Real-Time Mode | — |
| Jordan Cutler | Speaker | Use AI to Multiply Your Team as a Staff Engineer | — | |
| Joseph Lynch | Netflix | Speaker | Orderly Keys, Wild Values: Adaptive Compression for Distributed Key-Value Storage | — |
| Joy Ebertz | Imprint | Speaker | Transitioning From a Startup to a Mature Platform | — |
| Jyothi Nookula | DataRobot | Speaker | Builder-Driven Development: Rebuilding the Organization Around the Builder | — |
| Kaye Mason | Meta | Speaker | Nobody Knows Everything (and That's OK): Building Alignment in Complex, Rapidly Changing Environments | — |
| Kent Beck | KentBeck.com | Speaker | Features With Futures | — |
| Kishor Yadav Kommanaboina | Snap Analytics | Speaker | Autoscaling 800 Valkey Clusters: Distributed Systems Lessons from Scaling Stateful Fleets | — |
| Kshitij Gupta | Netflix | Speaker | Building a Migration Platform: Moving 100+ Netflix RDBMS Workloads to Aurora PostgreSQL | — |
| Kushan Mehta | Roblox | Speaker | Generation Got Cheap, Trust Didn’t: Scaling Agentic Changes from Prompt to Prod at Roblox | — |
| Laura de Vesine | Speaker | Learning What’s Already There: A Breadth-Based Approach To Onboarding | — | |
| Laurie Voss | Arize AI | Speaker | Product Engineering: When code costs nothing, what's next? | — |
| Lee Faus | ATOMIC | Speaker | Wait, You're Still Doing PRs? | — |
| Liz Fong-Jones | Honeycomb | Speaker | Making Production Legible to Agents: Lessons From Building an Observability MCP | — |
| Lorin Hochstein | Airbnb | Speaker | Saturation: How Your Software Will Fail at Scale | — |
| Mallika Rao | Zocdoc | Speaker | Adaptive Systems in Production: What Recommendation Systems Can Teach Us About Agents | — |
| Margaret-Anne Storey | University of Victoria | Speaker | Shipping Faster, Understanding Less | — |
| Mark Khuzam | Netflix | Speaker | How Netflix Retrofitted Its SDLC for AI Coding Agents | — |
| Mouli Mukherjee | OpenAI | Speaker | Building a Data Platform with AI | — |
| Nancy Zheng | Cerebras | Speaker | Inside the Disaggregated Architecture Serving LLM Inference | — |
| Omer van Kloeten | Forter | Speaker | You Can't Read the Code Anymore - Verifying Software in the Age of AI | — |
| Paige Elinson | Datadog | Speaker | One Does Not Simply Add Synchronous Writes - Bridging Batch and Real Time with Apache Iceberg | — |
| Pavitter Josan | Nutrient | Speaker | Why Your Document AI Fails in Production — And How to Fix the Infrastructure Underneath It | — |
| Payal Patel | Freshworks | Speaker | Legacy vs. AI-Native Is the Wrong Question: Architecting the Modern Platform | — |
| Prachi Jain | Netflix | Speaker | The Freeze Paradox: Why Stopping Deployments Doesn't Stop Failures | — |
| Rachael Wonnacott | Capital Group | Speaker | Observability: The Missing Control Plane for Agentic Engineering | — |
| Rajat Shah | Netflix | Speaker | Failing in Layers: Lessons from Rebuilding Netflix's ML Serving Platform | — |
| Rishabh Bhargava | Together AI | Speaker | How to Build a Real-Time Voice Agent | — |
| Ronak Nathani | Speaker | Beyond the Kubernetes API: Building LinkedIn’s Compute Platform | — | |
| Ryan Brown | Crunchyroll | Speaker | The Schema Was Never Enough: The World in Protocols | — |
| Saiprasad Murali | Freshworks | Speaker | Legacy vs. AI-Native Is the Wrong Question: Architecting the Modern Platform | — |
| Sandhya Narayan | — | Speaker | The Freeze Paradox: Why Stopping Deployments Doesn't Stop Failures | — |
| Sanjay Singh | Speaker | When Everyone Can Code, Who Owns Production? | — | |
| Sarah Deitke | Duolingo | Speaker | No New Backend: The API Layer Behind 800+ Agent-Built Apps at Duolingo | — |
| Scott Behrens | Netflix | Speaker | Scaling Tech by Aligning Humans | — |
| Shannon McKenzie | Blackbaud | Speaker | From Datasets to Data Products: Powering Trusted AI for Social Impact | — |
| Shine Garg | Uncharted Path Breakthroughs | Speaker | Legacy as Leverage: How Brownfield Work Builds Technical Judgment | — |
| Shweta Vohra | Booking.com | Speaker | Why Most Platform Teams Fail: The Adoption Problem Nobody Wants to Own | — |
| Smruti Patel | Apollo Graph | Speaker | Platform Engineering’s Second Act: From Vending Machine to Passport Control | — |
| Sri Annapurna Bhupatiraju | BlackRock | Speaker | Inside Asimov: BlackRock’s Platform Architecture for Applied AI at Scale | — |
| Sudarshan Srinivasa Ramanujam | Speaker | Bridging Retrieval and Ranking: From LLM Embeddings and Graph Features to a GPU-Served DLRM | — | |
| Sunil Murthy | IBM | Speaker | You Steer, Agents Execute: Developer-Led Modernization with Agentic AI | — |
| Swayam Barik | IBM | Speaker | Beyond the Model: Engineering the Agent Harness for Autonomous Software Delivery | — |
| Tara Hernandez | MongoDB | Speaker | The Diary of an AI Adopter: How I Went From Skeptical to Enthusiastic in Our Organization’s AI Migration Efforts | — |
| Uday Kiran Medisetty | Uber | Speaker | Running Software Factory Efficiently at Uber Scale: Holding Agent Spend Steady While Requests Grew 9X | — |
| Vanessa Huerta Granda | Enova | Speaker | It's Never the Thing That Broke: Learning From Incidents at (AI) Speed | — |
| Weiping Peng | Airbnb | Speaker | How Airbnb Guardrailed Its AI Customer Support Agent | — |
| Wenbing Bai | Netflix | Speaker | Failing in Layers: Lessons from Rebuilding Netflix's ML Serving Platform | — |
| Xiaowei Jiang | Tacnode | Speaker | The Context Gap: Why Correct Agents Fail | — |