Practical AI: Beyond the Hype Cycle

Cutting Through the Noise#

Every week brings a new "revolutionary" AI breakthrough. Most of them won't matter to your business. Some will transform it entirely. The challenge is knowing the difference.

Our Approach to AI#

We don't chase trends. We solve problems.

When a client comes to us with an AI request, we start with a simple question: What problem are you actually trying to solve?

More often than not, the answer reveals that AI is either:

• Exactly what they need
• Completely unnecessary
• A piece of a larger solution

The Three-Layer Framework#

We evaluate AI applications across three dimensions:

1. Feasibility: Can current AI actually do this reliably?
2. Value: Will this create meaningful business impact?
3. Risk: What are the failure modes and how do we handle them?

What Actually Works#

Based on our experience shipping AI features to production, here's what consistently delivers value:

1. Intelligent Automation#

Taking repetitive, rules-based tasks and adding just enough intelligence to handle edge cases. This isn't glamorous, but it compounds.

2. Enhanced Search#

Natural language understanding applied to search can be transformational. People can ask questions instead of guessing keywords.

3. Content Assistance#

AI that helps humans write better, faster - without replacing human judgment. The key word is assistance.

What Rarely Works#

Some applications sound great in demos but fail in production:

• Fully autonomous decision-making for high-stakes situations
• Perfect accuracy expectations where 95% isn't good enough
• Replacing domain expertise entirely with generic models

The Bottom Line#

AI is a tool, not a strategy. The companies winning with AI are the ones treating it as they would any other technology decision: evaluating trade-offs, starting small, and iterating based on real usage.

We're here to help you navigate that process - without the hype.

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Interested in exploring what AI could do for your product? Get in touch.