AI-Powered Dev Hacks at ConFoo 2025

Recently, I had the pleasure of presenting on a topic that I'm pretty passionate about: how artificial intelligence can amplify developer productivity and creativity. In my talk "Code Smarter, Not Harder: AI-Powered Dev Hacks for All," I explored how AI isn't replacing developers but rather making us more effective and efficient.

As I shared in the presentation, AI won't replace developers, but developers who use AI will replace those who don't. This sentiment captures the essence of what I believe is happening in our industry right now — we're witnessing a fundamental shift in how software gets built, and those who adapt will thrive.

Why AI Matters for Developers

The statistics speak volumes: 72% of developers are confident in AI tools, with 92% of Fortune 500 companies already using AI technologies in some capacity. Among developers, 75% are either using or planning to use AI tools, with an average productivity increase of 26%.

How are developers using these tools? According to recent surveys:

• 85% use AI for code generation
• 77% for research and learning
• 54% for debugging and testing

These numbers reflect what we're all experiencing: AI is becoming an essential part of the modern developer's toolkit.

8 AI-Powered Dev Hacks to Transform Your Workflow

Throughout the presentation, I shared eight practical ways to leverage AI in your development workflow. Here's a recap of these game-changing approaches:

#1 - Learning How to Talk to Robots (Prompt Engineering)

The foundation of effective AI use is learning how to communicate with these systems. Clear, structured prompts determine the quality of AI output. I demonstrated how to craft prompts that include context, examples, and specific instructions to get the best results.

Instead of vague requests like "Write a blog post about AI," try detailed prompts such as "Write a technical blog post explaining neural networks to junior developers, focusing on practical examples. Include code samples in Python and keep it under 1,000 words."

#2 - Prompting with Your Voice

Voice-based AI interaction is becoming increasingly powerful. By dictating your requirements rather than typing them, you can often articulate more complex ideas and save time. This approach is particularly useful when brainstorming or working through programming challenges.

#3 - Learning Software Development

AI excels as a personalized learning companion. For junior developers, AI can break down complex concepts into simpler terms with customized explanations that match your learning style. Senior developers can use AI to quickly understand new technologies and frameworks or dive deep into advanced concepts.

#4 - Reading Code

When faced with unfamiliar or legacy code, AI can provide remarkable assistance. By asking AI to explain code's purpose, identify design patterns, or break down complex functions, you gain insights that would otherwise require significant time to discover. This is particularly valuable when onboarding to new projects or maintaining legacy systems.

#5 - Documentation

Documentation is crucial but often neglected due to time constraints. AI can generate class/method documentation, explain complex algorithms, create usage examples, and document API endpoints. It can also improve existing documentation by enhancing clarity and consistency or converting between formats.

#6 - Building Tools

We're naturally tool-builders, and AI amplifies this capacity. I showed how developers can create AI-powered CLI tools, IDE plugins, browser extensions, and reporting tools that automate repetitive tasks in your workflow. Building these personalized tools allows you to address specific pain points in your development process.

#7 - Working with Data

AI excels at data-related tasks: transforming between formats (JSON, CSV, XML), generating realistic test data, optimizing database queries, designing schemas, and converting between SQL dialects. These capabilities save countless hours that would otherwise be spent on tedious data manipulation.

#8 - Running Models Locally

For tasks requiring privacy, enhanced performance, or offline capability, running AI models locally is becoming increasingly accessible. Tools like Ollama and Open WebUI enable developers to run powerful models on their own hardware, ensuring sensitive data stays within your infrastructure while maintaining full control.

Best Practices for AI Integration

Throughout the presentation, I emphasized several key principles for effective AI use:

1. Always review and understand AI-generated code - Never blindly trust what AI produces
2. Maintain strict security practices - Be cautious about sharing sensitive information
3. Use AI as a learning tool, not just a code generator - Understand the "why" behind solutions
4. Start small and scale gradually - Begin with well-defined tasks before tackling more complex ones

Getting Started Today

If you're looking to incorporate AI into your workflow, I recommend these practical steps:

1. Begin with documentation and code review tasks
2. Use AI to learn new technologies and concepts
3. Integrate AI tools into your existing workflow gradually
4. Develop a collection of reliable prompts for common tasks

Slides

You can find the slides from my talk below or download them here.

Final Thoughts

As software developers, we're entering an era where AI can handle many of the tedious aspects of coding, allowing us to focus on what truly matters — creativity, problem-solving, and delivering value. The key isn't to replace human judgment but to enhance it.

In the words of Satya Nadella, "I think what AI does quite frankly is reduce the floor and raise the ceiling for all of us." This perfectly captures the potential of AI in development: lowering barriers to entry while expanding what's possible.

AI doesn't diminish the importance of strong engineering principles or deep technical knowledge — it amplifies them. By embracing these tools, we can focus on higher-level thinking and more meaningful work while letting AI handle the repetitive tasks.

What AI hacks have you incorporated into your workflow? I'd love to hear about your experiences in the comments below!

For more content on AI and software development, visit danvega.dev or check out my AI-focused site at bytesizedai.dev.