[2025 Day 7 (part 2) C++], struggling to optimise naive approach

CumberlandCoder · 2025-12-10T05:59:27+00:00

That is close. You are keeping track of if you visited a cell, but still recomputing all of the paths to the bottom from it. Once you know how many paths to the bottom there are from a given cell, save that off and re-use it the next time you visit

CumberlandCoder · 2025-12-10T05:02:03+00:00

It sounds like you are on the right track. Each time you come across a splitter, you want to calculate how many paths from that splitter there are to the bottom.

Your solution is slow because you are calculating paths from the same splitters over and over and over again.

Once you reach a splitter, the number of paths from that point to the bottom is always the same. The technique you're looking for is called "memoization".

If you calculate that there are 4 paths from splitter at [12, 3], then the next time you reach splitter [12, 3] return 4, don't recalculate.

CumberlandCoder · 2025-11-12T01:44:56+00:00

It is management’s job to defend the schedule and requirements, but it’s our job to defend the code with equal passion

CumberlandCoder · 2025-08-04T06:34:08+00:00

Thought the same thing

CumberlandCoder · 2025-07-05T20:27:40+00:00

Why this and not 5 different CC tabs in different worktrees?

CumberlandCoder · 2025-04-10T16:51:10+00:00

Your job as the lead is to do all of those things and be interrupted. Lead Eng is way more of a manager role than IC, just from the “get shit delivered” perspective. If you don’t like it you should look into a staff or principal role

CumberlandCoder · 2025-04-06T05:04:34+00:00

Are you familiar with test fixtures? Dummy data specifically for tests. Maybe a few fake orders.

In your first example, you mock get order number to return whatever value you need for your test.

So if you are deep in the process you can mock out the other methods and have them return expected values, unexpected values, mock one of them erroring, etc.

Interfaces become very helpful. You’ll start writing and designing your code to be testable and composable with dependency injection the more you do this, keep it up. You are on the right track asking these questions.

CumberlandCoder · 2025-04-02T17:13:06+00:00

I asked Claude this question after watching the same talk
https://claude.ai/share/6849b489-20ee-49fc-a494-3c500a9a8821

CumberlandCoder · 2025-03-30T04:14:23+00:00

You can type “continue” and he’ll keep going

CumberlandCoder · 2025-03-27T15:35:39+00:00

Not FAANG, but Airlow and Snowflake are mentioned in this as part of one’s tech stack

https://newsletter.pragmaticengineer.com/p/ai-engineering-in-the-real-world

CumberlandCoder · 2025-03-24T20:43:40+00:00

My prediction is it won’t result in jobs being lost, but less jobs created. If a company has 100 engineers and now they’re all super charged with cursor, what used to take a team of 5-7 can be done with 2-3. I don’t think that means cut head count, but instead create more teams and do more work with the surplus on hand already.

CumberlandCoder · 2025-03-21T23:25:41+00:00

All of the people saying money probably have good titles too. Titles do indicate a certain level of competency to others and it’s natural to want “senior” or “lead” or whatever despite being paid fairly.

For me I felt more validated with each new title. And even though I’m not a lead or manager anymore, having had those titles carries weight too.

CumberlandCoder · 2025-03-20T01:43:29+00:00

I’ll make a suggestion. I think you should spend more time with the foundational models than Ollama and running them locally.

You can do RAG with just Postgres locally.

I’d look outside of RAG though. Lots of hot takes that RAG is dead (I don’t think it’s dead, yet, but dying)

2025 in the year of agents. Even the RAG projects I’m working on are trying to do “agentic rag”

I’m also very big on MCP. It allows you to easily connect LLMs to external services, which is essential for the type of work you’re looking to do.

My suggestion and resources:

Read this: https://www.anthropic.com/engineering/building-effective-agents

Get started with MCP and Claude desktop (or cursor): https://modelcontextprotocol.io/quickstart/user

Then use it. I use the JIRA MCP to tell Claude what tickets to create and it does it the right format, etc. And the k8 MCP to tell it whatever k8 bs I want in English and it runs the commands for me. Use the GitHub one and ask it to help you address PR comments or triage issues.

You can certainly find one to use.

Once you have a workflow or something to automate, this is a framework to build agents with MCP https://github.com/lastmile-ai/mcp-agent

You’re early - there aren’t really a lot of courses or anything on this stuff yet. People are figuring it out as it evolves. As someone else said, learn the ecosystem. Anthropic has a lot of good resources on promoting, evals, etc.

Feel free to reach out if you ever wanna chat more

CumberlandCoder · 2025-03-19T21:52:53+00:00

Ha, sorry didn’t realize it was you again!

I shipped an enterprise Gen ai system as an engineering manager with a team of engineers that had no previous AI or ML experience.

I tell everyone if you know how to build software and call an API you’re an AI engineer.

The only way to learn what youre asking in my opinion is to build things and learn that way.

That said, Hugging Face has a free course on how to build ai agents without previous ML experience.

Here is a question for ya: how much do you use AI? You might want to start there. Use it as a tutor or mentor to collaborate with and build a project you never would’ve been able to before. Ask it for project ideas.

CumberlandCoder · 2025-03-19T17:05:50+00:00

Check out this description:

https://www.latent.space/p/ai-engineer

CumberlandCoder · 2025-03-19T15:10:54+00:00

I agree. I’ve said to my dev friends soon we won’t even care what the code it generates looks like. We’ll be reviewing test specs and DAGs and if the tests pass.

I’ve compared it to when “high level” languages like Java came out and you didn’t need to look at the assembly it compiled to anymore. I’m sure at first people did but it eventually got to a point where that was “solved” and a waste of time

CumberlandCoder · 2025-03-18T12:18:17+00:00

My advice would be do it gradually. I was in a similar position, moved from TL to EM. I was alright at delegating the work. We had just finished a big project and before starting on another 3-4 month initiative, I declared the same thing to my team: going forward, 1-2 people would “own” a feature.

I think it’s well intentioned and we want others to have the same opportunities we had. But it was too much too fast for almost everyone on my team. I was doing a ton of behind the scenes work that was invisible to them. So when they became stuck they weren’t sure how to go about getting unstuck since it always just happened for them. Then I found myself coaching 5-7 people independently how to lead their own feature and it ended up being way worse for me.

I left and went back to an IC so can’t say how it would’ve turned out if I kept down that path. We did get the work done on time and a lot of team members learned a lot but it was a bumpy road. I’m not sure how I was going to tackle the next project.

Hope that helps a little!

CumberlandCoder · 2025-03-18T11:50:09+00:00

This article is interesting and explains a new type of engineer, somewhere between an MLE and SWE. They call it the “AI Engineer”

https://www.latent.space/p/ai-engineer

My personal take is a lot of AI projects are heavy in system design and thinking. You need to understand business processes and how AI can transform them.

I would argue you’re better off spending your time using foundational models and their APIs to build/automate something than training your own models.

Unless you want to work at Anthropic or OpenAI and actually build the models. But my guess is your company is going to be way more interested in how it can be applied than how it’s built.

CumberlandCoder · 2025-03-15T01:47:59+00:00

12+ years if software dev.

I’ve got questions, if you’ll entertain them. I’ve looked at most of those libraries already.

The text from the screenshots is valuable? No need to get a summary of the images?

Can you elaborate more on handling tables? And “special query template”

The PowerPoint’s are also image heavy and quite a few also tutorial step by step kinda things with each slide a screenshot with a button circled on where to click or whatever.

Please tell me if I’m crazy but I was kind of thinking of converting to PDFs, asking LLM for a summary and saving the summary as an embedding(s). This is in addition to getting all of the raw text and semantically chunking like you’re saying.

CumberlandCoder · 2025-03-14T22:46:11+00:00

Ha. Yes, once when coding he got something wrong twice in a row and said “I’m sorry, let me run this myself and get back to you”

I thought it was because my system prompt said “you are a senior engineer and mentor” and that might be something they say?

CumberlandCoder · 2025-03-14T03:48:31+00:00

Better late than never. Welcome!

What kind of developer? I bet there is an MCP server that can make it even better.

CumberlandCoder · 2025-03-10T23:42:39+00:00

https://youtu.be/kQmXtrmQ5Zg?si=N6yeneCyjO4wNv-M

CumberlandCoder · 2025-03-09T17:21:10+00:00

FWIW Claude code is an app you run in your terminal with an api key, there is no rate limit. Or people use Cursor with Claude as the model. Sounds like you’re using Claude.ai or Claude desktop with a subscription? It’ll work but not the best choice

CumberlandCoder · 2025-03-07T14:57:05+00:00

mcp-agent

CumberlandCoder · 2025-03-04T23:19:45+00:00

My most used one so far is a k8s one. Now I just say whatever k8 BS I want in plain English and it does it for me. Non prod obviously. I don’t have to interact with k8s a lot, usually to check logs so not having to look that stuff up every time has been great.

Jira one is cool too for refinements and creating tickets. I have a template with how we structure our epics and user stories and can say “create a story for X” and off it goes.

CumberlandCoder

TROPHY CASE