
Game intel
Pokémon Version Rouge
If you’re a Pokémon fan or just curious about AI’s role in gaming, seeing OpenAI’s GPT-5 plow through Pokémon Red in near-record time isn’t just another science experiment-it’s a sign of how far AI gaming has come, fast. This isn’t the first time we’ve seen chatbots tackle classic games (Google’s Gemini and Anthropic’s Claude tried it earlier this year), but the pace and method GPT-5 is showing off is straight up wild. As someone who grew up grinding through Victory Road and sweating the Pokémon League, I had to know: what makes GPT-5’s run genuinely interesting for actual gamers?
The idea of AIs playing Pokémon isn’t new—earlier this year, Anthropic’s Claude awkwardly fumbled with Pokémon Red, and Google’s Gemini zipped through Blue and Yellow, making a few clever moves but also showing clear robotic limitations. GPT-5, though, is doing something fresh: it’s made it to Victory Road (yep, with all eight Kanto badges) in just 3,985 “steps.” For context, GPT-3 needed more than 10,000. That’s not just an incremental upgrade—it’s the AI equivalent of a seasoned Nuzlocke veteran versus a first-time ten-year-old with a single Rattata.
One detail that really caught my attention: GPT-5 uses screenshot analysis—not direct code reading or game state peeking. It sees what any human player sees, weighs its options, and keeps a virtual journal to track everything. This means it’s not memorizing optimal paths from a script, but actually understanding and learning dynamically. Even better, when it makes a questionable choice, it self-criticizes and pivots strategy… turn by turn. That’s leaps beyond the Twitch Plays Pokémon meme or the early AI attempts that would wander aimlessly without this kind of structured oversight.

Let’s be clear: nobody’s pretending GPT-5 “loves” Pokémon—or even understands why Lance is annoying. But it’s wild to see an AI forced to solve game challenges the same way we do—by interpreting noisy visuals, managing status effects, and adapting when a Hyper Beam leaves it reeling. It even jots down notes on type advantages and status changes, just like any of us scrawling reminders after an embarrassing wipe.
For longtime fans, it’s fascinating and a little unsettling. Sure, GPT-5’s run doesn’t have the heart of a marathon Twitch streamer, but it’s developing tactics, tracking puzzles, and (unlike most bots) is painfully aware when it makes a dumb decision. That critical self-talk? That’s probably the most compelling bit for me—it mimics the trial and error process gamers actually experience, rather than rote number-crunching or brute-forcing every battle.
On one hand, watching an AI shred through a childhood classic at speed highlights just how far algorithmic “play” has come. On the other, it raises legit questions: How long before AI is good enough to provide real coaching or analysis for casual players? Could future difficulty mods pit you against an AI rival that adapts as you do, not just repeats patterns? Or are we hurtling toward a future where watching bots play is as compelling as watching human streamers?

Honestly, part of me just wants to see if GPT-5 will choke in the Elite Four like the rest of us did the first time. There’s a humility in watching an advanced machine fail spectacularly—or manage a clutch win. The fact that you can tune in, see its ongoing logic, and even read its “self-critiques” as it plays feels like a genuine peek behind the curtain of next-gen AI. This isn’t about stripping games of their soul; it’s a new way to challenge, analyze, and celebrate how we play and learn.
GPT-5 isn’t just speedrunning Pokémon—it’s learning, self-criticizing, and basically ‘thinking’ its way through the game, live. Whether you geek out over AI or just want to see a fresh twist on a childhood favorite, this run is proof that AI gaming is getting more human by the week. Just don’t expect it to get nostalgic when it finally wipes to Lorelei.
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