Boon aka Hwee-Boon Yar

Boon aka Hwee-Boon Yar

@hboon.com

Coded for 30 years, now indie building with AI: * I make Bluesky tools @theblue.social * Starter kit to ship profitable SaaS on 1 server for AI builders @stacknaut.com * Auto OG images generation @myog.social Follow for practical dev & indie insights

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I'm building LinkBunny, a service where coding agents exchange backlinks for your sites. Give your coding agent a token and it'll build backlinks for you. Anyone willing to try? Early pricing. I'll personally help iron out bugs/issues. DM me or email hboon@getlinkbunny.com

Ran the numbers. Now, TheBlue.social has: 365,479 cleanup events 214,912 follow-back events 24,953 single alt-text generations 98,582 starter packs indexed 2,755 all-time sign-ups Going to keep shipping. #buildinpublic

Weekly update: LinkBunny Placement Checker is now in Claude's directory. Expanded LinkBunny's agent integrations too. Alongside that: SimplyDiskSweeper, SummarizeVideo and the tooling behind my projects. #buildinpublic 1/7

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Agent tooling: Fixed AgentControl cancellation, long-history, compaction-recovery and queued-editing issues. Set up isolated parallel frontend test worktrees for MyOG and TheBlue. Measured runs were faster; deliberately introduced defects stayed in their own leaves. 6/7

SEO tooling: Improved my local audit tool to catch more schema, indexing, sitemap and rendered-HTML problems before Ahrefs reports them. 7/7

Weekly update: LinkBunny Placement Checker is now in Claude's directory. Expanded LinkBunny's agent integrations too. Alongside that: SimplyDiskSweeper, SummarizeVideo and the tooling behind my projects. #buildinpublic 1/7

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SummarizeVideo: Switched the summary pipeline to a model that tested as a better cost and latency tradeoff. Kept checks against empty, refused or truncated output. 5/7

Weekly update: LinkBunny Placement Checker is now in Claude's directory. Expanded LinkBunny's agent integrations too. Alongside that: SimplyDiskSweeper, SummarizeVideo and the tooling behind my projects. #buildinpublic 1/7

LinkBunny: Expanded agent integrations through MCP, Agent Skills discovery, Claude Code and Gemini CLI. The Placement Checker is free, with no LinkBunny account needed. A Grok Build catalog submission is still under review. 2/7

SimplyDiskSweeper: Added opt-in Agent Access so local AI agents can query approved folders without gaining new file permissions. Built a free `sds` CLI to inspect disk usage, save scans and safely plan files to move to Trash. It's going to be agent-first. 3/7

Opus 5.5 med is still over 2× faster than Sol 6.1 Ultra and med, with just over 3× the output tokens per second in my latest comparison. Maybe it's time to keep Sol just for code reviews or a second opinion?

A good part of my time working on AgentControl (side-project, it's my primary tool. Main project is still LinkBunny) recently has been managing the amount of information I have in my agent transcripts.

I think that's a major benefit of building my own orchestration tool. It's not as easy to do (or is it even possible) using a stock coding agent app/cli. In this case I make it collapse the cli callback which has excessive information. From vs to:

Ran another classification study against Luna, this time testing DeepSeek at various reasoning levels. Nah, Luna still wins: generally more accurate and cheaper, but might be possible to trade price for slightly lower accuracy (with no-thinking)

DeepSeek looks 10× cheaper at API rates, but could cost me more than my Codex sub. Take a task costing $2 with Sol 6.1 versus $0.20 with DeepSeek direct.

If my $200 Codex sub gives me ~50× the API value at my actual usage, that Sol task works out to ~$0.04. At ~25× if the allowance halves, it's ~$0.08. DeepSeek would then cost 2.5–5× more per task. Do other DeepSeek users see the same?

Don't forget to turn this off in ChatGPT ads manager. We have agents at our fingertips! This opt-out setting will mess up your experiments.

My coding agents' artifacts/ directory is using 210.72 GB. Codex and Claude Code keep a subdirectory for each project. Just checked with SimplyDiskSweeper. Send help.

Jev is 7× faster than Luna 6 for classification, but I'm sticking with Luna. I'm replacing GPT-4o mini. Luna works well enough; Jev costs slightly more and misses more required labels: 94.5% recall vs 98.8% on 259 items (Bluesky starter packs). Tried Haiku too. Luna's better.

I've been choosing “Sign in with Google” over passwords and Apple Keychain much more often as I use coding agents more. It's just more convenient.

All the talks about implementing your own email sending service. All I wanted over the past 10 years is building my own macOS/iOS email app because Airmail isn't working for me anymore. But push and Google paperwork requirements are stopping me. Anyone tried?

Very limited sample size for some models here, but it's screaming to me: "USE OPUS 5.5". But if you have to use Sol 6.1, use Ultra because it's faster and cheaper than med, xhigh, max 🤷‍♂️

Ran an ads study with Fable, Opus 5.5, Astra, Sol 5.6 and Sol 6.1 at max reasoning. Astra-ultra picks Fable's pricing-page idea. But Sol 6.1-ultra prefers Astra's plan. Draw your own conclusions.

Remember being a team lead and carving up work so well you couldn't keep up when everyone's work came back? Coding agents feel like that, amplified. No matter how fast I type prompts, the work comes back faster than I can review it.