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I like this quote, what do you think?
"If the part of programming you enjoy most is the physical act of writing code, then agents will feel beside the point. You’re already where you want to be, even just with some Copilot or Cursor-style intelligent code auto completion, which makes you faster while still leaving you fully in the driver’s seat about the code that gets written.
But if the part you care about is the decision-making around the code, agents feel like they clear space. They take care of the mechanical expression and leave you with judgment, tradeoffs, and intent. Because truly, for someone at my experience level, that is my core value offering anyway. When I spend time actually typing code these days with my own fingers, it feels like a waste of my time." — Obie Fernandez, What happens when the coding becomes the least interesting part of the work
https://simonwillison.net/2025/Dec/13/obie-fernandez/
Missed a session or want to revisit your favorites? Now’s your chance!
Explore 42 sessions packed with insights, including:
✅4 inspiring keynotes
✅ 22 Customer success stories
✅5 Partner innovations
✅11 MathWorks-led technical talks
Each session comes with video recordings and downloadable slides, so you can learn at your own pace.
The Cody Contest 2025 has officially wrapped up! Over the past 4 weeks, more than 700 players submitted over 20,000 solutions. In addition, participants shared 20+ high-quality Tips & Tricksarticles—resources that will benefit Cody users for years to come.
Now it’s time to announce the winners.
🎉 Week 4 winners:
Weekly Prizes for Contest Problem Group Finishers:
@JKMSMKJ, @Yu Zhang, @Oliver Jaros, @Pauli Huusari, @Karl, @Marcos Silveira, @goc3, @Ildeberto de los Santos Ruiz, @Norberto, @Eric
Weekly Prizes for Contest Problem Group Solvers:
Weekly Prizes for Tips & Tricks Articles:
This week’s prize goes to @WANG Zi-Xiang. See the comments from our judge and problem group author @Matt Tearle:
‘We had a lot of great tips for solving Cody problems in general and the contest problems specifically. But we all know there are those among us who, having solved the problem, still want to tinker and make their code better. There are different definitions of "better", but code size remains the base metric in Cody. Enter Wang Zi-Xiang who compiled a list of many tips for reducing Cody size. This post also generated some great discussion (even prompting our insane autocrat, Lord Ned himself, to chime in). I particularly like the way that, while reducing Cody size often requires some arcane tricks that would normally be considered bad coding practice, the intellectual activity of trying to "game the system" makes you consider different programming approaches, and sometimes leads you to learn corners of MATLAB that you didn't know.’
🏆 Grand Prizes for the Main Round
Team Relentless Coders:
2nd Place: @Roberto
Team Creative Coders:
Team Cool Coders
Congratulations to all! Securing a top position on the leaderboard requires not only advanced MATLAB skills but also determination and consistency throughout the four-week contest. You will receive Amazon gift cards.
🥇 Winning Team
The competition was incredibly tight—we even had to use the tie-breaker rule.
Both Team Cool Coders and Team Relentless Coders achieved 16 contest group finishers. However, the last finisher on Cool Coders completed the problem group at 1:02 PM on Dec 7, while the last finisher on Relentless Coders finished at 9:47 PM the same day.
Such a close finish! Congratulations to Team Cool Coders, who have earned the Winning Team Finishers badge.
🎬 Bonus Round
Invitations have been sent to the 6 players who qualified for the Bonus Round. Stay tuned for updates—including the Big Watch Party afterward!
Congratulations again to all winners! We’ll be reaching out after the contest ends. It has been an exciting, rewarding, and knowledge-packed journey.
See you next year!
In a recent blog post, @Guy Rouleau writes about the new Simulink Copilot Beta. Sign ups are on the Copilot Beta page below. Let him know what you think.
Guy's Blog Post - https://blogs.mathworks.com/simulink/2025/12/01/a-copilot-for-simulink/
Simulink Copilot Beta - https://www.mathworks.com/products/simulink-copilot.html
I believe that it is very useful and important to know when we have new comments of our own problems. Although I had chosen to receive notifications about my own problems, I only receive them when I am mentioned by @.
Is it possible to add a 'New comment' alert in front of each problem on the 'My Problems' page?
Over the past three weeks, players have been having great fun solving problems, sharing knowledge, and connecting with each other. Did you know over 15,000 solutions have already been submitted?
This is the final week to solve Cody problems and climb the leaderboard in the main round. Remember: solving just one problem in the contest problem group gives you a chance to win MathWorks T-shirts or socks.
🎉 Week 3 Winners:
Weekly Prizes for Contest Problem Group Finishers:
@Umar, @David Hill, @Takumi, @Nicolas, @WANG Zi-Xiang, @Rajvir Singh Gangar, @Roberto, @Boldizsar, @Abi, @Antonio
Weekly Prizes for Contest Problem Group Solvers:
Weekly Prizes for Tips & Tricks Articles:
This week’s prize goes to @Cephas. See the comments from our judge and problem group author @Matt Tearle:
'Some folks have posted deep dives into how to tackle specific problems in the contest set. But others have shared multiple smaller, generally useful tips. This week, I want to congratulate the cumulative contribution of Cool Coder Cephas, who has shared several of my favorite MATLAB techniques, including logical indexing, preallocation, modular arithmetic, and more. Cephas has also given some tips applying these MATLAB techniques to specific contest problems, such as using a convenient MATLAB function to vectorize the Leaderboard problem. Tip for Problem 61059 – Leaderboard for the Nedball World Cup:'
Congratulations to all Week 3 winners! Let’s carry this momentum into the final week!
If you haven't solved the problem yet, below hints guide how the algorithm should be implemented and clarify subtle rules that are easy to miss.
1. Shield is ONLY defended in HOME matches of the CURRENT holder - Even if a team beats the Shield holder in an away match, that does NOT count as a Shield defense.
2. A team defends the Shield ONLY when:
> They currently hold it.
> They are home team in that match
3. Shield transfer happens ONLY if the HOLDER plays a home match AND loses - A team may lose an away match — no effect.
4. The output ALWAYS includes the initial holder as the first row.
5. Defenses count resets for each new holder. - Every holder accumulates their own count until they lose it at home.
6. Match numbers are 1-indexed in the input, but “0” is used for initial state - The first real match is Match 1, but the output starts with Match 0.
7. Output row is created ONLY WHEN SHIELD CHANGES HANDS - This is an important hidden detail. A new row is appended, When the current holder loses a home match → Shield taken by visitor. If no loss at home occurs after that → no new row until next change.
8. The last holder’s defense count goes until the season ends - Even if they lose away later.
9. If a holder never gets a home match, defenses = 0.
10. In case the holder loses their very first home match → defenses = 0.
11. Shield changes only on HOME LOSS, not on a draw.
I hope above hints will help you in solving the problem.
Thanks and Regards,
Dev
In just two weeks, the competition has become both intense and friendly as participants race to climb the team leaderboard, especially in Team Creative, where @Mehdi Dehghan currently leads with 1400+ points, followed by @Vasilis Bellos with 900+ points.
There’s still plenty of time to participate before the contest's main round ends on December 7. Solving just one problem in the contest problem group gives you a chance to win MathWorks T-shirts or socks. Completing the entire problem group not only boosts your odds but also helps your team win.
🎉 Week 2 Winners:
Weekly Prizes for Contest Problem Group Finishers:
@Cephas, @Athi, @Bin Jiang, @Armando Longobardi, @Simone, @Maxi, @Pietro, @Hong Son, @Salvatore, @KARUPPASAMYPANDIYAN M
Weekly Prizes for Contest Problem Group Solvers:
Weekly Prizes for Tips & Tricks Articles:
This week’s prize goes to @Athi for the highly detailed post Solving Systematically The Clueless - Lord Ned in the Game Room.
Comment from the judge:
Shortly after the problem set dropped, several folks recognized that the final problem, "Clueless", was a step above the rest in difficulty. So, not surprisingly, there were a few posts in the discussion boards related to how to tackle this problem. Athi, of the Cool Coders, really dug deep into how the rules and strategies could be turned into an algorithm. There's always more than one way to tackle any difficult programming problem, so it was nice to see some discussion in the comments on different ways you can structure the array that represents your knowledge of who has which cards.
Congratulations to all Week 2 winners! Let’s keep the momentum going!
% Recreation of Saturn photo
figure('Color', 'k', 'Position', [100, 100, 800, 800]);
ax = axes('Color', 'k', 'XColor', 'none', 'YColor', 'none', 'ZColor', 'none');
hold on;
% Create the planet sphere
[x, y, z] = sphere(150);
% Saturn colors - pale yellow/cream gradient
saturn_radius = 1;
% Create color data based on latitude for gradient effect
lat = asin(z);
color_data = rescale(lat, 0.3, 0.9);
% Plot Saturn with smooth shading
planet = surf(x*saturn_radius, y*saturn_radius, z*saturn_radius, ...
color_data, ...
'EdgeColor', 'none', ...
'FaceColor', 'interp', ...
'FaceLighting', 'gouraud', ...
'AmbientStrength', 0.3, ...
'DiffuseStrength', 0.6, ...
'SpecularStrength', 0.1);
% Use a cream/pale yellow colormap for Saturn
cream_map = [linspace(0.4, 0.95, 256)', ...
linspace(0.35, 0.9, 256)', ...
linspace(0.2, 0.7, 256)'];
colormap(cream_map);
% Create the ring system
n_points = 300;
theta = linspace(0, 2*pi, n_points);
% Define ring structure (inner radius, outer radius, brightness)
rings = [
1.2, 1.4, 0.7; % Inner ring
1.45, 1.65, 0.8; % A ring
1.7, 1.85, 0.5; % Cassini division (darker)
1.9, 2.3, 0.9; % B ring (brightest)
2.35, 2.5, 0.6; % C ring
2.55, 2.8, 0.4; % Outer rings (fainter)
];
% Create rings as patches
for i = 1:size(rings, 1)
r_inner = rings(i, 1);
r_outer = rings(i, 2);
brightness = rings(i, 3);
% Create ring coordinates
x_inner = r_inner * cos(theta);
y_inner = r_inner * sin(theta);
x_outer = r_outer * cos(theta);
y_outer = r_outer * sin(theta);
% Front side of rings
ring_x = [x_inner, fliplr(x_outer)];
ring_y = [y_inner, fliplr(y_outer)];
ring_z = zeros(size(ring_x));
% Color based on brightness
ring_color = brightness * [0.9, 0.85, 0.7];
fill3(ring_x, ring_y, ring_z, ring_color, ...
'EdgeColor', 'none', ...
'FaceAlpha', 0.7, ...
'FaceLighting', 'gouraud', ...
'AmbientStrength', 0.5);
end
% Add some texture/gaps in the rings using scatter
n_particles = 3000;
r_particles = 1.2 + rand(1, n_particles) * 1.6;
theta_particles = rand(1, n_particles) * 2 * pi;
x_particles = r_particles .* cos(theta_particles);
y_particles = r_particles .* sin(theta_particles);
z_particles = (rand(1, n_particles) - 0.5) * 0.02;
% Vary particle brightness
particle_colors = repmat([0.8, 0.75, 0.6], n_particles, 1) .* ...
(0.5 + 0.5*rand(n_particles, 1));
scatter3(x_particles, y_particles, z_particles, 1, particle_colors, ...
'filled', 'MarkerFaceAlpha', 0.3);
% Add dramatic outer halo effect - multiple layers extending far out
n_glow = 20;
for i = 1:n_glow
glow_radius = 1 + i*0.35; % Extend much farther
alpha_val = 0.08 / sqrt(i); % More visible, slower falloff
% Color gradient from cream to blue/purple at outer edges
if i <= 8
glow_color = [0.9, 0.85, 0.7]; % Warm cream/yellow
else
% Gradually shift to cooler colors
mix = (i - 8) / (n_glow - 8);
glow_color = (1-mix)*[0.9, 0.85, 0.7] + mix*[0.6, 0.65, 0.85];
end
surf(x*glow_radius, y*glow_radius, z*glow_radius, ...
ones(size(x)), ...
'EdgeColor', 'none', ...
'FaceColor', glow_color, ...
'FaceAlpha', alpha_val, ...
'FaceLighting', 'none');
end
% Add extensive glow to rings - make it much more dramatic
n_ring_glow = 12;
for i = 1:n_ring_glow
glow_scale = 1 + i*0.15; % Extend farther
alpha_ring = 0.12 / sqrt(i); % More visible
for j = 1:size(rings, 1)
r_inner = rings(j, 1) * glow_scale;
r_outer = rings(j, 2) * glow_scale;
brightness = rings(j, 3) * 0.5 / sqrt(i);
x_inner = r_inner * cos(theta);
y_inner = r_inner * sin(theta);
x_outer = r_outer * cos(theta);
y_outer = r_outer * sin(theta);
ring_x = [x_inner, fliplr(x_outer)];
ring_y = [y_inner, fliplr(y_outer)];
ring_z = zeros(size(ring_x));
% Color gradient for ring glow
if i <= 6
ring_color = brightness * [0.9, 0.85, 0.7];
else
mix = (i - 6) / (n_ring_glow - 6);
ring_color = brightness * ((1-mix)*[0.9, 0.85, 0.7] + mix*[0.65, 0.7, 0.9]);
end
fill3(ring_x, ring_y, ring_z, ring_color, ...
'EdgeColor', 'none', ...
'FaceAlpha', alpha_ring, ...
'FaceLighting', 'none');
end
end
% Add diffuse glow particles for atmospheric effect
n_glow_particles = 8000;
glow_radius_particles = 1.5 + rand(1, n_glow_particles) * 5;
theta_glow = rand(1, n_glow_particles) * 2 * pi;
phi_glow = acos(2*rand(1, n_glow_particles) - 1);
x_glow = glow_radius_particles .* sin(phi_glow) .* cos(theta_glow);
y_glow = glow_radius_particles .* sin(phi_glow) .* sin(theta_glow);
z_glow = glow_radius_particles .* cos(phi_glow);
% Color particles based on distance - cooler colors farther out
particle_glow_colors = zeros(n_glow_particles, 3);
for i = 1:n_glow_particles
dist = glow_radius_particles(i);
if dist < 3
particle_glow_colors(i,:) = [0.9, 0.85, 0.7];
else
mix = (dist - 3) / 4;
particle_glow_colors(i,:) = (1-mix)*[0.9, 0.85, 0.7] + mix*[0.5, 0.6, 0.9];
end
end
scatter3(x_glow, y_glow, z_glow, rand(1, n_glow_particles)*2+0.5, ...
particle_glow_colors, 'filled', 'MarkerFaceAlpha', 0.05);
% Lighting setup
light('Position', [-3, -2, 4], 'Style', 'infinite', ...
'Color', [1, 1, 0.95]);
light('Position', [2, 3, 2], 'Style', 'infinite', ...
'Color', [0.3, 0.3, 0.4]);
% Camera and view settings
axis equal off;
view([-35, 25]); % Angle to match saturn_photo.jpg - more dramatic tilt
camva(10); % Field of view - slightly wider to show full halo
xlim([-8, 8]); % Expanded to show outer halo
ylim([-8, 8]);
zlim([-8, 8]);
% Material properties
material dull;
title('Saturn - Left click: Rotate | Right click: Pan | Scroll: Zoom', 'Color', 'w', 'FontSize', 12);
% Enable interactive camera controls
cameratoolbar('Show');
cameratoolbar('SetMode', 'orbit'); % Start in rotation mode
% Custom mouse controls
set(gcf, 'WindowButtonDownFcn', @mouseDown);
function mouseDown(src, ~)
selType = get(src, 'SelectionType');
switch selType
case 'normal' % Left click - rotate
cameratoolbar('SetMode', 'orbit');
rotate3d on;
case 'alt' % Right click - pan
cameratoolbar('SetMode', 'pan');
pan on;
end
end
Thank you to everyone who attended the workshop A Hands-On Introduction to Reinforcement Learning! Now that you all have had some time to digest the content, I wanted to create a thread where you could ask any further questions, share insights, or discuss how you're applying the concepts to your work. Please feel free to share your thoughts in the thread below! And for your reference, I have attached a PDF version of the workshop presentation slides to this post.
If you were interested in joining the RL workshop but weren't able to attend live (maybe because you were in one of our other fantastic workshops instead!), you can find the workshop hands-on material in this shared MATLAB Drive folder. To access the exercises, simply download the MATLAB Project Archive (.mlproj) file or copy it to your MATLAB Drive, extract the files, and open the project (.prj). Each exercise has its own live script (.mlx file) which contains all the instructions and individual steps for each exercise. Happy (reinforcement) learning!
Is it possible to get the slides from the Hands-On-Workshops?
I can't find them in the proceedings. I'm particularly interested in the Reinforcement Learning workshop, but unfortunately I couldn't participate.
Thanks in advance!
In https://www.mathworks.com/matlabcentral/answers/38165-how-to-remove-decimal#comment_3345149 @Luisa asks,
@Cody Team, how can I vote or give a like in great comments?
It seems that there are not such options.
In just one week, we have hit an amazing milestone: 500+ players registered and 5000+ solutions submitted! We’ve also seen fantastic Tips & Tricks articles rolling in, making this contest a true community learning experience.
And here’s the best part: you don’t need to be a top-ranked player to win. To encourage more casual and first-time players to jump in, we’re introducing new weekly prizes starting Week 2!
New Casual Player Prizes:
- 5 extra MathWorks T-shirts or socks will be awarded every week.
- All you need to qualify is to register and solve one problem in the Contest Problem Group.
Jump in, try a few problems, and don’t be shy to ask questions in your team’s channel. You might walk away with a prize!
Week 1 Winners:
Weekly Prizes for Contest Problem Group Finishers:
@Mazhar, @Julien, @Mohammad Aryayi, @Pawel, @Mehdi Dehghan, @Christian Schröder, @Yolanda, @Dev Gupta, @Tomoaki Takagi, @Stefan Abendroth
Weekly Prizes for Tips & Tricks Articles:
We had a lot of people share useful tips (including some personal favorite MATLAB tricks). But Vasilis Bellos went *deep* into the Bridges of Nedsburg problem. Fittingly for a Creative Coder, his post was innovative and entertaining, while also cleverly sneaking in some hints on a neat solution method that wasn't advertised in the problem description.
Congratulations to all Week 1 winners! Prizes will be awarded after the contest ends. Let’s keep the momentum going!
Great material, examples and skillfully guided. And, of course, very useful.
Thanks!
Many MATLAB Cody problems involve solving congruences, modular inverses, Diophantine equations, or simplifying ratios under constraints. A powerful tool for these tasks is the Extended Euclidean Algorithm (EEA), which not only computes the greatest common divisor, gcd(a,b), but also provides integers x and y such that: a*x + b*y = gcd(a,b) - which is Bezout's identity.
Use of the Extended Euclidean Algorithm is very using in solving many different types of MATLAB Cody problems such as:
- Computing modular inverses safely, even for very large numbers
- Solving linear Diophantine equations
- Simplifing fractions or finding nteger coefficients without using symbolic tools
- Avoiding loops (EEA can be implemented recursively)
Below is a recursive implementation of the EEA.
function [g,x,y] = egcd(a,b)
% a*x + b*y = g [gcd(a,b)]
if b == 0
g = a; x = 1; y = 0;
else
[g, x1, y1] = egcd(b, mod(a,b));
x = y1;
y = x1 - floor(a/b)*y1;
end
end
Problem:
Given integers a and m, return the modular inverse of a (mod m).
If the inverse does not exist, return -1.
function inv = modInverse(a,m)
[g,x,~] = egcd(a,m);
if g ~= 1 % inverse doesn't exist
inv = -1;
else
inv = mod(x,m); % Bézout coefficient gives the inverse
end
end
%find the modular inverse of 19 (mod 5)
inv=modInverse(19,5)
Congratulations to all the Relentless Coders who have completed the problem set. I hope you weren't too busy relentlessly solving problems to enjoy the silliness I put into them.
If you've solved the whole problem set, don't forget to help out your teammates with suggestions, tips, tricks, etc. But also, just for fun, I'm curious to see which of my many in-jokes and nerdy references you noticed. Many of the problems were inspired by things in the real world, then ported over into the chaotic fantasy world of Nedland.
I guess I'll start with the obvious real-world reference: @Ned Gulley (I make no comment about his role as insane despot in any universe, real or otherwise.)
Hi, what’s the best way to learn MATLAB, Simulink, and Simscape? Do you recommend a learning path? I work in the Electrical & Electronics area for automotive systems.
Hi Everyone!
As this is the most difficult question in problem group "Cody Contest 2025". To solve this problem, It is very important to understand all the hidden clues in the problem statement. Because everything is not directly visible.
For those who tried the problem, but were not able to solve. You might have missed any of the below hints -
- “The other players do not get to see which card has been shown, but they do know which three cards were asked for and that the player asked had one of them.” - Even when the card identity isn’t revealed (result = 0), you still gain partial knowledge — the asked player must have at least one of those three cards, meaning you can mark other players as not having all three simultaneously.
- "If it is your turn, you know the exact identity of that card" - You only know the exact shown card when result = 1, 2, or 3 — and it must be your turn. If someone else asked (even if you know result = 0), you don’t know which one was shown. So the meaning of result depends on whose turn it was, which is implicit — MATLAB code must assume that turns alternate 1→m→1, so your turn index is determined by (t-1) mod m + 1 == pnum.
- "Any leftover cards are placed face-up so that all players can see them" - These cards (commoncards) are not in anyone’s hand and cannot be in the envelope. So they’re not just visible — they’re logical constraints to eliminate from deduction.
- “It may be possible to determine the solution from less information than is given, but the information given will always be sufficient.”
- "Turn order is implied, not given explicitly" - Players take turns in order (1 to m, and back to 1).
On considering all the clues and constraints in the question, you will definitely be able to card for each category present in envelope.
I hope above clues will be useful for you.
Thank you, wishing you the success!
Regards,
Dev
Experimenting with Agentic AI
44%
I am an AI skeptic
0%
AI is banned at work
11%
I am happy with Conversational AI
44%
9 votes
When solving Cody problems, sometimes your solution takes too long — especially if you’re recomputing large arrays or iterative sequences every time your function is called.
The Cody work area resets between separate runs of your code, but within one Cody test suite, your function may be called multiple times in a single session.
This is where persistent variables come in handy.
A persistent variable keeps its value between function calls, but only while MATLAB is still running your function suite.
This means:
- You can cache results to avoid recomputation.
- You can accumulate data across multiple calls.
- But it resets when Cody or MATLAB restarts.
Suppose you’re asked to find the n-th Fibonacci number efficiently — Cody may time out if you use recursion naively. Here’s how to use persistent to store computed values:
function f = fibPersistent(n)
import java.math.BigInteger
persistent F
if isempty(F)
F=[BigInteger('0'),BigInteger('1')];
for k=3:10000
F(k)=F(k-1).add(F(k-2));
end
end
% Extend the stored sequence only if needed
while length(F) <= n
F(end+1)=F(end).add(F(end-1));
end
f = char(F(n+1).toString); % since F(1) is really F(0)
end
%calling function 100 times
K=arrayfun(@(x)fibPersistent(x),randi(10000,1,100),'UniformOutput',false);
K(100)
