John Keller

[NXT1 @nxt1sports]

DON’T JUST COMPETE. 𝘿𝙊𝙈𝙄𝙉𝘼𝙏𝙀.

Not just a chatbot. A real work engine personalized around your program.

Stop grinding on busywork. Start executing.

The greatest sports intelligence platform in the world.

[Peter H. Diamandis, MD @PeterDiamandis]

We are the ARCHITECTS of TOMORROW!

[kuz @kylekuzma]

Quantum compute.

[John Keller @iamjohnkeller]

Shape your mind
Change your world

[John Keller @iamjohnkeller]

@ionleu https://t.co/bLTokaot1P

[John Keller @iamjohnkeller]

Thankful for the opportunity to be building the infrastructure to give coaches and athletes countless hours back.

Our goal is simple:
Give coaches more time to coach.
Give athletes more time to play.

Follow @nxt1sports to see what we're shipping next.

[NXT1 @nxt1sports]

TAKEOVER 2026.

[John Keller @iamjohnkeller]

Excited to announce @nxt1sports new platform is now live.

The first AI agent command center for sports organizations.

A 24/7 digital sports staff built to execute, drive outcomes, and get real work done.

[NXT1 @nxt1sports]

A new era begins.
The Sports 𝙄𝙣𝙩𝙚𝙡𝙡𝙞𝙜𝙞𝙚𝙣𝙘𝙚 Platform is now here.
Built on execution. focused on legacy.

For programs to move with speed, precision, and purpose.

NXT1 is live.

Start winning today.
https://t.co/xSsO60zuCC

@iamjohnkeller

[New Mentalities @NewMentalities]

Stay in the fight long enough and life has no choice but to hand you what’s yours.

[Elon Musk @elonmusk]

For quality of life, it is better to err on the side of being an optimist and wrong, rather than a pessimist and right

[NXT1 @nxt1sports]

Introducing 𝘼𝙜𝙚𝙣𝙩 𝙓

A full-stack AI operating system for athletes, hs/club teams, and colleges.

More time on the field or court. Less time everywhere else.
No learning curve required. Personalized around you. ⬇️

- The World’s First AI sports graphics designer and highlight video maker.
- Analyze athlete profiles.
- Generate AI scouting reports.
- Match your talent with colleges.
- Contact college coaches.
- Search college information.
- Build recruiting strategies.
- Analyze game film.
- And much more.

Agent X lives inside NXT 1 and works across the entire journey.

You ask. The Agent executes. It just works.

[Bleacher Report @BleacherReport]

SHEDEUR FIRST TD PASS AT HOME 🚨

(via @NFL)

[tetsuo @tetsuoai]

Our potential as a species is limitless.

[John Keller @iamjohnkeller]

Excited what we built this year @nxt1sports

- 27,230 Active Users
- 4,914 in-app graphics & videos created
- 2,000,000+ social media views
- 59,709 emails sent to college coaches
- 47% email open rate (2x industry avg!)
- 28,073 coaches engaged
- 408 posts generating 65K+ in-app views (new social feed)
- ~500+ offers delivered

Growth solely from organic and word of mouth. Started this from the ground up!

From networking, search, AI, graphics, highlights, profiles, scouting, analytics, team websites, and more.

NXT 1 can do it all !

[NXT1 @nxt1sports]

We’re building something revolutionary.

NXT 1 AI Copilot.

Your personal recruiting assistant built for athletes, parents, and teams.

It contacts coaches, finds college matches, creates highlights, graphics, and strategies and more all in one place.

Coming soon. Watch this ⬇️

[John Keller @iamjohnkeller]

@thejustinwelsh 💯. That’s what made people like Steve Jobs extraordinary.

[John Keller @iamjohnkeller]

@_mrosenfield I’m a subscriber. Use it for copyright free instrumentals in my app.
best price too

[John Keller @iamjohnkeller]

I built free AI sports scouting reports for https://t.co/jLqWex3oU8, and wanted to share how they work.

AI SCOUT generates comprehensive athlete evaluations in seconds.

Looks like this:

1. Report Foundation – Through a multi-agent architecture that combines fine-tuned foundation models with RAG. Meta llama 4 provides the base reasoning engine fine-tuned on 300+ professional scouting reports to capture domain specific representations and the structural patterns of expert evaluations.

2.Information Retrieval – The majority of info is drawn from our indexed database, which performs detailed profile analysis across structured inputs. This is extended through web search with Perplexity Sonar, which surfaces additional context that may not be present.

3. Comparative Modeling – Grok 4 is used to identify statistically similar athletes, evaluate their historical trajectories, and generate projection ranges.

4.Synthesis – All modeled data is passed back into llama 4, which puts the information against the established scouting framework and outputs a professional-style report.

It’s a great way to get a good base on an athlete quickly!

The current limitation is the absence of automated video analysis, which I plan to explore.

I think it’s a pretty good set up!

You can use it free here: https://t.co/sdSAhwonHZ