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World Congress 2026 Europe • Jul 9, 2026 • Session details

It's Not Vibe Coding If You Know What You're Doing

Jeff Blankenburg

Ditch the aimless prompting. You can build complex applications without writing a single line of code. Learn how strict guardrails and CLI agents completely transform your AI-assisted engineering.

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#1 about 2 min

Overcoming initial skepticism of AI code generation

Exploring the state of AI coding adoption and the initial doubts around hype versus reality.

#2 about 2 min

Defining vibe coding and navigating early tool limitations

Operating as a senior reviewer for an AI junior developer requires clear context over simple snippet generation.

#3 about 2 min

Discovering command line workflows and AI-generated planning

Using an AI assistant in the CLI to generate markdown rules provides the necessary planning context for complex execution.

#4 about 3 min

Evolving a card collecting application through various architectures

A personal project transitions from spreadsheets and Airtable into a full relational database and Retool architecture.

#5 about 2 min

Experiencing the dopamine rush of rapid AI development

Experiencing the joy of continuous iteration and high-speed creation without writing software manually.

#6 about 3 min

Automating a daily sports newsletter entirely with AI

Building a system that gathers and distributes baseball box scores to subscribers without typing a single line of code.

#7 about 3 min

Establishing firm project constraints using robot reference files

Sharing best practices through documented onboarding rules instructs agents on necessary coding patterns, structures, and tools.

#8 about 1 min

Handling local environment credentials alongside rigid AI behavior

Adapting to rigid agent logic requires matching local Docker database passwords to its default hardcoded guesses.

#9 about 3 min

Building an AI-friendly HTML design system and reference

Pre-defining component layouts in code prevents styling hallucinations and maintains visual consistency across generated pages.

#10 about 3 min

Managing continuous iteration using semantic commits and issues

Creating frequent atomic commits and CLI-generated issues tracks progress and safely rolls back undesirable agent changes.

#11 about 2 min

Validating generated software pipelines with application observability tools

Relying on application performance monitoring and tracing replaces manual code reviews and catches problems before users experience failures.

#12 about 3 min

Preventing data loss by keeping AI out of production

Granting AI direct access to production databases risks unpredictable destruction of data and ORM schema misalignments.

#13 about 2 min

Avoiding AI hallucinations and database connection performance traps

Reviewing agent outputs for logic correctness and sensible connection pooling prevents underlying system issues.

#14 about 3 min

Understanding security boundaries when combining generated software components

Combining distinct secure modules can inadvertently create broader vulnerabilities that require human architectural oversight and integration testing.

Matching moments

13:07 min

Analyzing the practical limits of AI vibe coding

Chris Heilmann +2 · LIVE

8:24 min

Cleaning up AI generated code and vibe coding challenges

Chris Heilmann +2 · LIVE

1:46 min

Introduction to AI code generation and developer habits

Prashanth Chandrasekar Prashanth Chandrasekar · WWC 2023

1:25 min

Introduction to vibe coding and AI system generation

Dishu Bagga Dishu Bagga · Europe 2026 Virtual

5:16 min

Motivations for adopting AI to enhance developer productivity

6:29 min

Balancing AI enthusiasm with cynical engineering tool practices

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