Final 7-Round Kansas City Chiefs 2026 NFL Mock Draft: Putting my skills to the test against an AI trained to think like Brett Veach
I trained my AI to think and draft like Kansas City Chiefs GM Brett Veach. Then I challenged it to a duel for my final 2026 NFL Mock Draft.
You’re going to see a lot of final mock drafts for the Kansas City Chiefs this week, but I decided to make mine a little bit differently this year.
I wanted to give Chiefs fans an idea of what I would do while also adding a predictive element. What I settled on was a dueling mock draft against an AI trained to think like Chiefs GM Brett Veach.
How did I train my AI? First, I uploaded Veach’s draft history since he took over as general manager following the 2017 NFL Draft. Then, I fed it pre-draft and post-draft press conference transcripts to give the AI context on how Veach views the NFL Draft. I weighted the more recent press conferences more heavily. From there, I uploaded historical data on key thresholds at specific position groups. It had access to confirmed combine formals and pre-draft meetings with 2026 NFL Draft prospects, along with historical context on their importance.
I also uploaded the Chiefs’ stats from last season so the AI could quantify areas that needed improvement relative to NFL averages. The final piece of the puzzle was to upload the Chiefs’ 90-man offseason roster and team needs.
To execute the mock draft, I used the A to Z Sports NFL Mock Draft Simulator. I provided the AI with the list of the 10 best available players at a given pick. I made my picks before the AI, but I didn’t tell it who I had chosen. The AI was prompted to use all available data to make a decision for each draft pick. With all that in mind, here’s a look at how the mock draft competition turned out.
Final Kansas City 2026 NFL Mock Draft
Pick No. 9
Top available: Mansoor Delane, Caleb Downs, Jordyn Tyson, Spencer Fano, Makai Lemon, Monroe Freeling, Jermod McCoy, Kenyon Sadiq, Ola Ioane, and Keldric Faulk.
My pick: Arizona State WR Jordyn Tyson
Solving for the Chiefs’ need for “the guy” on offense in the future just feels like the right move for this draft class. Travis Kelce can’t play forever. Add Tyson and get back to scoring 30+ per game.
What AI Brett Veach did: Auburn DE Keldric Faulk
Edge rusher was the No. 1 need that I provided to the AI. At 6-foot-6 and 275 pounds with 34-inch arms, Faulk meets virtually every Chiefs threshold from a physical standpoint. It’s not an exciting pick for fans, but even a robot can see the upside here.
Pick No. 29
Top available: Kadyn Proctor, Akheem Mesidor, Caleb Banks, Cash Howell, T.J. Parker, CJ Allen, Denzel Boston, Chris Johnson, R Mason Thomas, and Colton Hood.
My pick: Tennessee CB Colton Hood
I’m becoming increasingly comfortable with the idea of taking a cornerback early. The old NFL adage goes that you can never have too many cornerbacks, and the Chiefs need bodies there. Not just for 2026, but also for the long term. Hood gives you a physical man coverage corner who can play outside, but probably crosstrains inside, too.
What AI Brett Veach did: Alabama OT Kadyn Proctor
Offensive tackle wasn’t rated as highly on the AI’s needs list. However, the Chiefs did have a top-30 visit with Proctor. I think it probably took note of Brett Veach’s comments about offensive tackle drying up by pick No. 35. He also hits some athleticism thresholds, despite missing on one key measurable (arm length).
Pick No. 40
Top available: Caleb Banks, Chris Johnson, R Mason Thomas, Denzel Boston, Chris Bell, Zion Young, Christen Miller, Chris Brazzell, D’Angelo Ponds, and Gabe Jacas.
My pick: Florida DT Caleb Banks
There are obviously some questions regarding the nagging foot injury. Plus, there’s still some development and pad-level issues to work out. I just think the 6-foot-6, 310-pound defender would really thrive by learning from Chris Jones.
What AI Brett Veach did: Florida DT Caleb Banks
What a copycat. Based on the information I gave the AI, this doesn’t surprise me. Banks had the medical top-30 visit with Kansas City. Veach, of course, mentioned needing two more defensive linemen in this class during his pre-draft presser. This just makes me feel even more strongly that this is a no-brainer pick if he’s available at pick No. 40.
Pick No. 74
Top available: Ted Hurst, Davison Igbinosun, Dom Orange, Antonio Williams, Jonah Coleman, Genesis Smith, Caleb Tiernan, Dani Dennis-Sutton, Will Lee III, and Keionte Scott.
My pick: Penn State DE Dani Dennis-Sutton
A member of the 2026 All-Juice Team, Dennis-Sutton feels like he was built in a lab solely for Steve Spagnuolo. He hits all of the physical thresholds, but also is quietly one of the more productive players at the position.
What AI Brett Veach did: Georgia State WR Ted Hurst
I think this might have been a “best player available” pick for the AI. Hurst took a pre-draft visit with the Chiefs, and wide receiver is pretty high on the needs list. It makes sense why the AI Brett Veach would value him here.
Pick No. 109
Top available: Brian Parker, Nick Singleton, Isaiah World, Oscar Delp, Dontay Corleone, Bud Clark, Kaleb Proctor, Harold Perkins, Emmett Johnson, and Charles Demmings.
My pick: TCU S Bud Clark
A versatile safety prospect for the Chiefs. Clark has ball skills for days, with four consecutive college football seasons with 3 or more interceptions. At 6-foot-1 and 188 pounds, he’s also a physical presence in run support. He fits the Spags mold.
What AI Brett Veach did: Stephen F. Austin CB Charles Demmings
Cornerback also ranked highly on the needs list, so I can see how the AI prioritized this position group at this pick. Veach also has a history of drafting FCS talent, including Fayetteville State CB Joshua Williams and Western Illinois DT Khalen Saunders. Demmings fits the mold for what K.C. likes at the cornerback spot in terms of physicality and athleticism.
Pick No. 148
Top available: Sam Roush, Kevin Coleman, Jalon Kilgore, Billy Schrauth, Kaleb Elarms-Orr, Ephesians Prysock, Justin Jefferson, Zane Durant, Logan Taylor, and Jeff Caldwell.
My pick: Stanford TE Sam Roush
I’m a big Roush fan. He’s already one of the better blocking tight ends in the class, but I also think there’s big upside as a pass-catcher. He has a 6-foot-6 and 267-pound frame. Plus, he’s a legacy player in Kansas City.
What AI Brett Veach did: South Carolina DB Jalon Kilgore
Nickel/safety versatility probably appealed to the AI here. There’s also really good ball production with eight career interceptions and 21 passes broken up. I think he’s rather role-limited in the NFL, but the AI could’ve done a whole lot worse at pick No. 148.
Pick No. 169
Top available: Landon Robinson, Josh Cameron, Caden Curry, Taureen York, Demon Claiborne, Domani Jackson, Eli Raridon, Cade Klubnik, J.C. Davis, and Keagen Trost.
My pick: Illinois OT J.C. Davis
I hadn’t taken an offensive tackle yet, so this felt right. This one is a bit of a homer pick as Davis played for my UNM Lobos before transferring to play for my Fighting Illini. If the Chiefs wait on offensive tackle, he’s the one I’d want them to target.
What AI Brett Veach did: Navy DT Landon Robinson
Doubling up on the pass-rushing interior defensive linemen. I see you, Brett Veach AI. Robinson is undersized, but his athleticism and production are absolutely worth taking a chance on. Being the top-ranked player on the list I gave to the AI probably played a part in this decision.
Pick No. 176
Top available: Jeremiah Wright, Ar’Maj Reed-Adams, Mikail Kamara, Marlin Klein, Adam Randall, Trey Moore, Jakobe Thomas, Nick Barrett, Kaelon Black, and Febechi Nwaiwu.
My pick: Michigan LB Jimmy Rolder
Call it a reach on my part, as Rolder is 201 on the A to Z Sports big board. Only a one-year starter. Instinctive with impressive closing speed at 6-foot-2 and 238 pounds. He’s someone who could slot in as a SAM linebacker in 2026, but potentially develop into the green-dot-wearer down the line.
What AI Brett Veach did: Indiana RB Kaelon Black
I noted three things the Chiefs still needed at running back in team needs for the AI: Pass protection, short-yardage, and return specialists. Black (5-foot-10, 210 pounds) can handle the first two, at the very least. The one thing I found interesting here is that running back was very low on my AI’s needs list.
Pick No. 210
Top available: Tyren Montgomery, John Michael Gyllenborg, Robert Spears-Jennings, Skyler Gill-Howard, Diego Pounds, Carver Willis, Caleb Douglas, Eli Heidenreich, Red Murdock, and George Gumbs Jr.
My pick: Florida EDGE George Gumbs Jr.
Gumbs felt like that developmental speed-rusher prototype that the Chiefs want, but haven’t really hit on. He’s long (6-foot-6 with 34-inch arms), springy, super-athletic, and the flash plays look really good. It’s just all about further development and consistency.
What AI Brett Veach did: Buffalo LB Khalil “Red” Murdock
The AI got a little sassy with me and spat out Red’s government name. I feel like Brett Veach’s recent comments about the linebacker position stuck with the AI here. I also feel like it valued Murdock’s production (364 tackles and 17 forced fumbles in his career).
Final verdict
Charles Goldman’s Final 2026 NFL Mock Draft:
- 9: Arizona State WR Jordyn Tyson
- 29: Tennessee CB Colton Hood
- 40: Florida DT Caleb Banks
- 74: Penn State EDGE Dani Dennis-Sutton
- 109: TCU S Bud Clark
- 148: Stanford TE Sam Roush
- 169: Illinois OT J.C. Davis
- 176: Michigan LB Jimmy Rolder
- 210: Florida EDGE George Gumbs Jr.
AI Brett Veach’s Final 2026 NFL Mock Draft:
- 9: Auburn DE Keldric Faulk
- 29: Alabama OT Kadyn Proctor
- 40: Florida DT Caleb Banks
- 74: Georgia State WR George Hurst
- 109: SFA CB Charles Demmings
- 148: South Carolina DB Jalon Kilgore
- 169: Navy DT Landon Robinson
- 176: Indiana RB Kaelon Black
- 210: Buffalo LB Red Murdock
Overall, I was surprised by how well the AI drafted. My draft feels a bit more top-heavy with the instant-impact contributors, but I think the AI might’ve actually done a better job on Day 3. That felt especially Brett Veach-like, given his history and penchant for finding late-round steals.
If I do this again next year, I think I’ll feed the AI some of our draft rankings at A to Z Sports to give it better context. It had access to prospect data, but not any specific set of rankings. That’s probably the one area this experiment failed. The only context it had for “best” was the order of the 10 players I gave it to choose from at each pick. If I had the ability to “reach” as I did at 176, the AI should be able to.
