Is AI the Future of Software—or Just the Enhancer?
An analysis on Building Smarter, Not Sooner
As the buzz around AI-native startups grows (shoutout to Greg Isenberg’s recent X thread on stealing market share with AI-first products), I’ve been reflecting on a more grounded approach.
While AI offers game-changing potential—think vertical agents or CLI-first tools—its non-determinism and token costs (e.g., $0.01-$0.10 per thousand, per 2024 Moesif data) pose risks for fully AI-native builds.
My strategy? Start with a solid foundation.
I’m developing a game requiring complex pattern-matching for player commands (e.g., "attack the orc with the sword"). Instead of diving straight into AI, I’m building a rule-based PoC with regex—achievable in 1-2 weeks—then enhancing it with NLP models to automate and refine. This hybrid model leverages AI’s strengths (e.g., handling edge cases) while mitigating its volatility, aligning with Gartner’s 2024 finding that 65% of successful AI deployments build on legacy systems.
For truly innovative software, AI-first makes sense—especially in niches where complexity demands it. But rushing in without a base risks instability. What’s your approach? Are you going AI-native or enhancing existing systems? Let’s discuss—drop your thoughts below!
#AI #SoftwareDevelopment #Innovation #TechStrategy #GameDev