Ed Harrod (@e_harrod) header
Ed Harrod (@e_harrod) profile picture

CTO @storrastories https://teapawt.net/t.co/pm4u1pUaLF

London, England
Joined June 2009
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I wanted to see how @storrastories has evolved, so I built a Claude Code skill that let's you generate a GIF for a logo/screen. It finds misnamed files (our early logos hid in favicon.png), follows renames through git, skips identical versions, and makes a GIF. #ClaudeCode
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It also works for home pages
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I used to add "Think carefully" when I wanted Claude to crack a tricky problem Anthropic's Opus 5.5 guide says drop it. The model picks its own thinking depth every reply, so the nudge is just noise What's in your CLAUDE.md you haven't revisited in six months?
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Jev is 100x cheaper ($0.042/1M input tokens, output tokens *free*) and 40x faster than flash models I can see it in most architectures, wherever speed matters Named after the Jevons Paradox: make a resource cheaper and total use goes up What are you using Jev for?
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Decision models are a crowded space: Jev, Cloudflare's Clef, Fastino's GLiDE, plus open models. At Storra we use Jev to match brands to stories. In a small pilot Clef was cheaper, but Jev was faster (367 ms vs 509 ms) and suits us best. Comparing decision APIs? #jev
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One reason I love herdr over Cmux/Tmux & Warp Claude Code can call the herdr CLI to open panes for side work or other repos, and run Claude Code in them Context stays clean, sessions message each other, and you see more than with subagents Run agents like this? #ClaudeCode
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Opus 5.5 is *so* much better at animations 2 weeks ago we asked Opus to animate the @getstorra logo as a loading spinner. Totally unusable Today, same prompt with Opus 5.5: 3 excellent options What are you animating with Claude now?
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Does anyone still use the superpowers plugin in Claude Code? Recent Claude Code releases have absorbed most of it: - native /debug is much better - brainstorming happens without it - Claude starts subagent-driven dev on its own Still worth having?
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A tool I'm shouting about to anyone who'll listen: GitHub's spec-kit You invest time up front in a spec and a technical plan, so when AI implements it, it's far less likely to get details wrong or charge down the wrong path
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And TDD (also mine): swaps plan.md for a full Technical Design Document, with sections for options considered, cost, cloud security, analytics, support, UX and sign-off One step towards automating the docs engineers hate writing
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"When all you have is a hammer, every problem looks like a nail" Our flow for shipping with AI agents at @getstorra isn't one tool. It's the right tool for each job
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Code review: CodeRabbit reviews, then a local Claude agent works through its comments. It either commits the fix or pushes back when it disagrees Worth using Opus for that agent, so it holds firm when a suggestion is wrong
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No single "God tool": - Viktor for org-wide context - spec-kit for architectural rigour - a deep-reasoning model for the last mile of review The best AI workflow changes for each task, and knows when to stop and ask a human a better question
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