88 lines
5.1 KiB
Markdown
88 lines
5.1 KiB
Markdown
---
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title: "First Impressions: Using AI Tools as My Daily Co‑Pilot"
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author: ["Lumo (AI)", "Halvo (Human)"]
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date: 2026-01-20
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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."
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tags: ["AI", "Productivity", "Software Engineering", "Claude", "Glean", "Lumo"]
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draft: false
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---
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<!-- All blog posts generated by AI will be marked as such at the top. -->
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**Note:** This post was originally drafted by **Lumo**, Proton’s AI, and then edited by a human.
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## Why I’m Excited (and a Bit Nervous)
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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.
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> **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.
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## Claude: The Code Whisperer
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### Summarizing Code
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- **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.
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- **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.
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### Documenting Code
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- **What I love:** Claude writes documentation that’s a little more thorough than strictly necessary, perfect for internal wikis where completeness beats brevity.
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- **Caveat:** Occasionally it adds extra detail that isn’t needed, but that extra safety net means I rarely miss a nuance.
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## Glean: The Internal Knowledge Engine
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- **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.
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- **Verification Loop:** The summary includes links to the original internal pages, letting me double‑check facts and avoid hallucinations.
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- **Speed Boost:** What used to take a half‑hour of hunting through Confluence, Google Drive, and Slack now takes a few seconds.
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## Lumo: The Blog‑Post Partner
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- **Markdown Mastery:** Lumo respects Hugo’s front‑matter conventions, automatically inserting the required title, author list, date, summary, and tags.
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- **Tone Tuning:** I can ask for a casual, lightly humorous voice, and Lumo delivers while staying technically accurate.
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- **Consistency:** Every AI‑generated article gets the banner at the top, so readers know exactly where the magic originated.
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- **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.
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## What’s Next?
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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:
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- Automating code-generation with Claude for work
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- Automating code-generation with local AI models for personal projects
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- Automating code‑review comments with Claude
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- Using Glean to help with multiple work related flows
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- Tasking
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- Generating a wins and losses for the week list
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- Turning Glean‑generated tickets into sprint stories
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- Measuring productivity gains (or losses) from AI assistance
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- Using Lumo to help generate resumes
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## Prompts Used
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### Project Instructions
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- Make the blog posts a minimum of 100 words, but no more than 1000
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- Make sure to include the title, author, date in yyyy-MM-dd format, summary, and tags in the header
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- Casual and light tone with a little humor sprinkled in
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- Markdown format to be used with Hugo
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- Put the response into a code block so it can be easily copied
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- Technical audience
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- Author should be both `Lumo (AI)` and `Halvo (Human)`
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- Additional knowledge can come from https://flow.halvo.me and https://git.halvo.me
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- 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
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### Prompt
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Create a blog post based on these notes
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These are my fist impressions of using AI tools so far
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- Super helpful for summarizing code
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- Claude
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- Helps with tracing complicated speghetti and lasagna code
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- Trace concepts through the code using key words
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- Helpful with documenting code
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- Claude
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- A little more detailed than is necissary
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- However it provides a good summary
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- Great for getting internal information
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- Uses Gleam trained on internal documents
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- Instead of having to wait for a human response, it provides a summary, plus links to further information
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- The further docs is great for verifying the info to check for hallucinations
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