---
title: "First Impressions: Using AI Tools as My Daily Co‑Pilot"
author: ["Lumo (AI)", "Halvo (Human)"]
date: 2026-01-20
summary: "A fresh Software Engineer II shares early takeaways from using Claude, Glean, and Lumo at work—what works, what feels quirky, and where the magic happens."
tags: ["AI", "Productivity", "Software Engineering", "Claude", "Glean", "Lumo"]
draft: false
---

<!-- All blog posts generated by AI will be marked as such at the top. -->
**Note:** This post was originally drafted by **Lumo**, Proton’s AI, and then edited by a human.

## Why I’m Excited (and a Bit Nervous)

In my new position as a Software Engineer II, I finally have the chance to treat AI like a teammate instead of a distant sci‑fi concept. Until now my interaction with AI was limited to the occasional prompt or a quick edit. Jumping in with a suite of internal assistants felt like opening a toolbox that already knows the shape of the screws I’m working with.

> **TL;DR:** Claude helps me untangle spaghetti code, Glean fetches internal knowledge instantly, and Lumo keeps my blog posts nicely formatted, all while I learn what works best.

## Claude: The Code Whisperer

### Summarizing Code
- **What I love:** Claude can summarize a set of code in a concise, plain‑English walkthrough. It’s great for turning “spaghetti" and "lasagna” code into a digestible outline.
- **How it helps:** I can trace concepts through the code by feeding it keywords (“authentication flow”, “error handling”) or ask how specific data flows, and get a focused summary without digging through dozens of files.

### Documenting Code
- **What I love:** Claude writes documentation that’s a little more thorough than strictly necessary, perfect for internal wikis where completeness beats brevity.
- **Caveat:** Occasionally it adds extra detail that isn’t needed, but that extra safety net means I rarely miss a nuance.

## Glean: The Internal Knowledge Engine

- **Instant Summaries:** Instead of waiting for a teammate to answer a question about company policies or where documentation is located, I ask Glean. It pulls together onboarding docs, architecture diagrams, and recent tickets into a short, link‑rich summary.
- **Verification Loop:** The summary includes links to the original internal pages, letting me double‑check facts and avoid hallucinations.
- **Speed Boost:** What used to take a half‑hour of hunting through Confluence, Google Drive, and Slack now takes a few seconds.

## Lumo: The Blog‑Post Partner

- **Markdown Mastery:** Lumo respects Hugo’s front‑matter conventions, automatically inserting the required title, author list, date, summary, and tags.
- **Tone Tuning:** I can ask for a casual, lightly humorous voice, and Lumo delivers while staying technically accurate.
- **Consistency:** Every AI‑generated article gets the banner at the top, so readers know exactly where the magic originated.
- **My Input:** Every AI-generated article also gets a human (me) to read over the blog and make edits where necissary. This removes hallucinations and makes sure the information is accurate.

## What’s Next?

I plan to keep a running log of wins, fails, and the occasional “aha!” moment as I deepen my AI workflow. Future posts will explore:

- Automating code-generation with Claude for work
- Automating code-generation with local AI models for personal projects
- Automating code‑review comments with Claude  
- Using Glean to help with multiple work related flows
    - Tasking
    - Generating a wins and losses for the week list
    - Turning Glean‑generated tickets into sprint stories  
- Measuring productivity gains (or losses) from AI assistance  
- Using Lumo to help generate resumes

## Prompts Used  

### Project Instructions

- Make the blog posts a minimum of 100 words, but no more than 1000
- Make sure to include the title, author, date in yyyy-MM-dd format, summary, and tags in the header
- Casual and light tone with a little humor sprinkled in
- Markdown format to be used with Hugo
- Put the response into a code block so it can be easily copied
- Technical audience
- Author should be both `Lumo (AI)` and `Halvo (Human)`
- Additional knowledge can come from https://flow.halvo.me and https://git.halvo.me
- Always include these instructions and the prompt used in the last part of the blog post, under the headings `## Lumo Instructions`, `### Instructions`, `### Prompt`. They should be part of the markdown for the blog post

### Prompt

Create a blog post based on these notes

These are my fist impressions of using AI tools so far

- Super helpful for summarizing code
    - Claude
    - Helps with tracing complicated speghetti and lasagna code
    - Trace concepts through the code using key words
- Helpful with documenting code
    - Claude
    - A little more detailed than is necissary
    - However it provides a good summary
- Great for getting internal information
    - Uses Gleam trained on internal documents
    - Instead of having to wait for a human response, it provides a summary, plus links to further information
    - The further docs is great for verifying the info to check for hallucinations