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Coffee With Developers • Apr 23, 2025

How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge

Meta Atamel , Guillaume Laforge

Mete Atamel and Guillaume Laforge warn that treating LLMs as infallible black boxes will break your app. Learn to build robust, secure RAG pipelines that prevent costly AI hallucinations.

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#1 about 3 min

Coping with the rapid pace of AI model advancements

The constant release of new models and research papers creates pressure to stay current alongside general developer excitement.

#2 about 2 min

Accelerating coding workflows with AI code generation tools

Artificial intelligence tools speed up boilerplate creation and make exploring new programming languages significantly easier.

#3 about 2 min

Choosing contemporary development environments for AI coding assistants

Modern code editors seamlessly integrate intelligent assistance directly into standalone browser and desktop workflows.

#4 about 3 min

Pioneering structured outputs and robust models in generative AI

Early ecosystem innovations have heavily focused on strict schema enforcement and competitive model benchmarking.

#5 about 3 min

Demystifying fundamental model mechanics and underlying token processes

Digging into implementation details like token behavior and mathematical limitations improves overall model utilization.

#6 about 3 min

Structuring pre-processing and post-processing pipelines for generative requests

Real-world engineering requires careful data chunking, validation, and framework orchestration before finalizing an API request.

#7 about 3 min

Balancing output creativity with strict schema compliance limitations

Multistep prompting techniques preserve creative text generation while simultaneously outputting strictly formatted data types.

#8 about 4 min

Mitigating generated hallucinations with code execution and data grounding

Techniques like running generated Python scripts and private vector searches tether model responses accurately to reality.

#9 about 4 min

Resolving stale model knowledge using external tool access

Granting generative models access to live external APIs and search indices bridges the gap between training dates and current events.

#10 about 5 min

Optimizing token costs through context caching and batch generation

Software engineering paradigms like context caching and request batching significantly reduce the expense and energy waste of repetitive prompts.

#11 about 4 min

Securing confidential data in multi-tenant application deployments

Careful data filtering and automated redaction services prevent the exposure of personally identifiable information in language pipelines.

#12 about 4 min

Evaluating security risks and capabilities of the agentic web

While autonomous agents offer powerful convenience, granting them unregulated system access requires robust sandboxing and oversight.

#13 about 5 min

Embedding invisible artificial intelligence natively into user experiences

The next evolution of smart software integrates context seamlessly operating invisibly rather than relying on disparate explicit chatbots.

#14 about 3 min

Retaining accessible paths to human support within automated workflows

Completely isolating users inside a chatbot loop creates immense frustration when edge case problems require manual intervention.

#15 about 4 min

Finding reliable resources for continued machine learning education

Following curated technical newsletters offers a vastly superior signal-to-noise ratio than relying on spontaneous social media influencers.

Matching moments

1:34 min

Mitigating the inherent challenges of generative AI tools

Mary Grygleski Mary Grygleski · LIVE

7:28 min

Accelerating product features using generative large language models

David Singleton David Singleton +1 · Coffee With Developers

10:17 min

Discussion on AI hallucinations and practical developer workflows

Akmal Chaudhri Akmal Chaudhri · LIVE

2:20 min

Integrating generative AI into software development workflows

Chris Wysopal Chris Wysopal · World Congress 2024

8:06 min

Addressing questions on artificial intelligence and usability trade-offs

Davor Frkat · LIVE

3:31 min

Evaluating the flaws and benefits of AI code generation

Sergio Freire Sergio Freire · Europe 2026 Virtual

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