// Topic
Developer Tools
Definition
Developer Tools coverage in this archive spans 6 posts from Jun 2021 to Apr 2024 and leans into practical engineering craft: interfaces, testing, and maintainable implementation details. The strongest adjacent threads are ai, productivity, and go. Recurring title motifs include ai, developer, months, and github.
What the archive argues
- The through-line is clarity first: simple designs that survive change beat clever abstractions.
- Early posts lean on github and copilot, while newer posts lean on ai and code as constraints shifted.
- This topic repeatedly intersects with ai, productivity, and go, so design choices here rarely stand alone.
Execution checklist
- Keep interfaces small, automate regressions early, and make operational assumptions explicit in code.
- Start with the newest post to calibrate current constraints, then backtrack to older entries for first principles.
- When boundary questions appear, cross-read ai and productivity before committing implementation details.
Common failure modes
- Abstracting before usage patterns are stable enough to justify indirection.
- Treating style consistency as optional until quality and velocity both degrade.
- Applying guidance from 2021 to 2024 without revisiting assumptions as context changed.
Suggested reading path
- Start here (current state): Most AI Developer Tools Are Not Worth Adopting Yet
- Then read (operating middle): Five Days With ChatGPT
- Finish with (foundational context): GitHub Copilot: First Impressions From a Go Developer
Related posts
- Most AI Developer Tools Are Not Worth Adopting Yet
- I Tracked My AI-Assisted Coding for Three Months. Here Are the Numbers.
- AI Code Review: What It Actually Catches (And What It Misses)
- Five Days With ChatGPT
- My Honest Take on GitHub Copilot After Six Months
- GitHub Copilot: First Impressions From a Go Developer
References
6 posts
- Most AI Developer Tools Are Not Worth Adopting Yet
The AI tooling landscape is exploding. Most of it adds complexity without removing real friction. Here is how I decide what earns a spot in the stack.
I Tracked My AI-Assisted Coding for Three Months. Here Are the Numbers.
After three months of tracking Copilot and GPT-4 usage across real projects, the productivity picture is messier than the marketing suggests.
AI Code Review: What It Actually Catches (And What It Misses)
After three months of using AI-assisted code review across multiple projects, here's what actually works and what's just noise.
Five Days With ChatGPT
First impressions of ChatGPT from a working engineer. It is not a search engine, it is not a colleague, and it is definitely not a replacement. But it is something.
My Honest Take on GitHub Copilot After Six Months
Six months with Copilot in real projects. What it actually helps with, where it quietly makes things worse, and why the productivity claims are overblown.
GitHub Copilot: First Impressions From a Go Developer
I got early access to GitHub Copilot's technical preview. Here's what it actually does well, what it gets wrong, and why I'm cautiously interested.