Pete Hodgson
@thepete.net
170 followers 140 following 96 posts
Startup CTO and software delivery aficionado
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thepete.net
1000000%
chriscoyier.net
I feel like how we feel about smoking on airplanes is how the next generation will feel about us just mainlining social media.
thepete.net
See if you can spot the prompt injection: github.com/trailofbits/...

Or if you can spot the backdoor being added: github.com/trailofbits/...

More on the lethal trifecta: simonwillison.net/2025/Jun/16/...
thepete.net
Good example of why it's important to monitor your LLM-powered features in prod.

Apparently some bug in Amazon's AI assistant where the product description isn't in it's prompt.

Pre-production evals are super important, but wouldn't catch this. Monitoring some key metrics in prod would.
thepete.net
c) invest in making your codebases agent-friendly by wrapping all your conventions and tribal knowledge into a small set of scripts

point C is exactly the same guidance that I was giving 11 years ago(!!!): www.thoughtworks.com/insights/blo...

I was ahead of the curve I guess :D
In Praise of the ./go Script - Part I
My step-dad is a cabinet-maker by trade. We chat about his work from time to time. I've often been struck by the similarities between building furniture and building software. Take tooling for example...
www.thoughtworks.com
thepete.net
The point being:

a) In many situations LLMs are WAY WORSE that "classic" deterministic tools.

b) don't waste a ton of ultra-valuable LLM context on guidance that could be enforced a different way

🧵...
In Praise of the ./go Script - Part I
My step-dad is a cabinet-maker by trade. We chat about his work from time to time. I've often been struck by the similarities between building furniture and building software. Take tooling for example...
www.thoughtworks.com
thepete.net
Such a nice way to illustrate the point
jessitron.bsky.social
Putting all your controllers in one directory and your views in another
Is like putting the cortisone and hemorrhoid cream in the drawer with toothpaste because they're all tubes.
Reposted by Pete Hodgson
samuel.fm
Samuel @samuel.fm · Aug 7
they should be taken to The Hague for this graph crime
Bar chart where 52>69 and 69=30
about gpt5 comparison
thepete.net
I also highly recommend checking out other sessions from that AI That Works series if you're building AI-powered product features. There are some gems on how to do evals the right way, how to build agents, and lots more.

The presenters are practitioners in the thick of it - they know their stuff!
thepete.net
- invest time in really good "agent onboarding" - CLAUDE.md (or equivalent), and agent-friendly tooling in your repo. This is super valuable because *every time* you compact context or spawn a subagent it's like a brand new engineer just joined the team.
thepete.net
- when implementing you should be manually “compacting” context fairly regularly
- or even better, use tasks/subagents to achieve the same
- invest time in building really good re-usable prompts for research and planning phases

/🧵...
thepete.net
- break the task down into researching, then planning, then implementing, with human-in-the-loop at each step, and a new context window at each step (I wrote about this here: blog.thepete.net/blog/2025/04...)

/🧵...
Chain-of-Vibes
Chain-of-Vibes is a workflow that lets you overcome AI's current inadequacies in tackling meaty coding tasks, by setting up a tight feedback loop between yourself and the AI.
blog.thepete.net
thepete.net
I really like how @dexhorthy.bsky.social (the presenter) summarized some of the concepts visually - check out the github doc for a sneak peek.

My favorite take-ways:

/🧵...
thepete.net
There are some amazing pro-tips for AI coding in this session:
github.com/hellovai/ai-...

Specifically, really good advice on how to manage agent context (which can have a big impact on the LLMs performance).

If nothing else, just skim the summary and see if anything looks interesting.

/🧵...
ai-that-works/2025-08-05-advanced-context-engineering-for-coding-agents at main · hellovai/ai-that-works
🦄 ai that works - every tuesday 10 AM PST. Contribute to hellovai/ai-that-works development by creating an account on GitHub.
github.com
Reposted by Pete Hodgson
mikebroberts.com
Hi #AWS -using friends. I’ve been writing some articles about fundamental AWS ops for small-medium companies, all oriented around AWS Organizations. So far I’ve covered org structure, Accounts, managing human users, IaC. I have another 4 or so articles still to come, so am about half way.

(1/3)
thepete.net
I've tried "right-sized services" in the past, but it doesn't exactly skip off the tongue.

I quite like mezzoservices. It's cute, but that's ok :)
thepete.net
This continues to shock and confuse me: the proportion of devs who are still not getting any active encouragement from their employers to start experimenting w. AI-assisted coding.

Also goes to show how silly the "all devs will be replaced by AI in 2 years" claims are.

/via @angiejones.tech
thepete.net
Very cool!

FYI, I got an error in the sandbox when I clicked Generate Response. Do I need to add an API key somewhere, or something?
thepete.net
100% agree, but I'd say it applies to AI-assisted coding in general, not just code review.
thepete.net
I loved this quote:

The real power of AI in code reviews isn’t in replacing developers as the reviewers. It’s in handling the routine work that can bog down the review process, freeing developers to focus where their judgment is most valuable.

🧵..
thepete.net
3. Relatedly, LLM-based review does NOT catch everything a linter will. For one thing, the LLM doesn't have full access to typing info. For another, you can add custom linting rules which enforce team conventions and avoid coding footguns. Old-fashioned deterministic checks still have a place.

🧵..
thepete.net
2. Yes, of course you should be putting AI-generated code through the same CI/CD quality checks as human code. But consider adding to those checks. A theme I keep hearing is teams are adding extra linting and automated tests, as a way to reduce the burden for humans reviewing AI-generated code.

🧵..
thepete.net
Some points that perhaps aren't in GitHub's interest to include in the post as an AI vendor:

1. You need to review AI-generated code MORE throughly than human-generated. Imagine you're reading the first PR from an engineer who just joined the company today, and is really keen to impress you.

🧵..