Students, early-career technologists, and career switchers looking for approachable, practical sessions.
12 sessions from the real MITechCon schedule
Apache Iceberg gets powerful when you understand the table lifecycle. The value comes from seeing how snapshots, rollback, compaction, and governance fit into the full table lifecycle. "Apache Iceberg Deep Dive Workshop" turns that scenario into a workshop.
Defenders make better decisions after seeing the attacker's workflow. Most defenders have never seen an attack from the other side of the keyboard. Ken Smith uses "Certified Red Team Fundamentals" to connect the warning signs to a walkthrough of a realistic.
Vague requirements turn into brittle architecture fast. How do you transition a sprawling, complex business problem into a clean, resilient software architecture? That is the entry point for "From Chaos to Context: A Hands-On Journey Through EventStorming.
Prompting is only one layer of useful AI. Once an LLM feature reaches real users, the engineering questions move from prompts to behavior, context, risk, and reliability. "LLMs Under the Hood - Applied Engineering Workshop" lets Barry Stahl connect tokens.
Data pipelines rarely fail on day one. The failure usually arrives later, when schema drift, volume growth, and ownership changes expose early shortcuts. Chris Birie uses "Designing Data Pipelines That Don’t Hate You Six Months Later" to follow that thread.
Slow lakehouse queries often come down to table design and maintenance. While we focus on Apache Iceberg, the techniques apply broadly to Delta Lake and Apache Hive as well. "Optimizing Your Apache Iceberg Lakehouse" keeps the conversation practical as.
Digital transformation fails when leaders start with tools instead of problems. Most organizations do not fall behind because the technology is missing; they fall behind when decisions, change, and readiness stay fuzzy. "Digital Transformation or Digital.
Public agencies need AI that improves services without adding complexity. Governments are starting to use AI agents to improve how services are delivered—from permits and public works to citizen support. Himanshu Goil brings that problem into "Civic Agents.
LLMs are powerful tools, but entity extraction still has classic CS problems. A tool can produce results while the underlying computer science problems are still very much alive. Milena F and Andy Schmidt use "LLMs are tools, not solutions: Entity extraction.
Manual testing slows delivery and weakens release confidence. The testing strategy has to scale across browsers and platforms without burying teams in maintenance work. "Test Smarter with AI: Playwright Automation at Scale on Azure" keeps the conversation.
Enterprise investigations slow down when evidence is scattered across systems. The challenge is bringing retrieval, agent workflow, and human oversight together without burying investigators in more noise. In "Case Study: Designing AI-Augmented Enterprise.
AI security changes when systems answer in probabilities instead of certainties. When I say "probabilistic" outcomes, your mind likely jumps to coins or dice. "Probably Secure: What We Misunderstand About AI And Determinism Is Making Us Less Secure" keeps.
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Speakers connected to the sessions in this guide
Lester MartinTrino Developer Advocate - Starburst2 sessions in this guide
Andy SchmidtSenior Software Architect1 session in this guide
Barry StahlSolution Architect and Developer1 session in this guide
Chris BirieSoftware and Data Martial Artist1 session in this guide
Dwayne McDanielDeveloper Advocate at GitGuardian and huge fan of open source1 session in this guide
Himanshu GoilChief Executive Officer, Ignatiuz Inc.1 session in this guide
John Selvaraj ArulappanLead AI Engineer @ADP1 session in this guide
Ken SmithDirector of Solutions and Strategic Partnerships1 session in this guide
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