Growth @ Unstoppable, Ex Police, Wannabe Wizard, BBQ Aficionado, Pigeon fan.

London, England
Joined December 2021
A lower token price only helps if the task stays scoped. Add retries, tool time, review and escalation to a stronger model. I’d compare models on cost per accepted change, using the same issue set and stop conditions.
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Generating 318,484 protein designs sounds impressive. Testing 211 and getting 17 that met the binder criteria is the number I care about. AI can make the search cheaper. Validation is still where the time and money go.
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Interesting approach from @unstoppableweb Their IDE lets you run Claude and Codex together in code review loops, customize multi-agent workflows, and switch between agents in one place The cross-agent code review is what caught my attention
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Useful workflow, but I’d keep the final application step behind approval. A generated CV can be reviewed. An application sent to the wrong role or with the wrong claim is much harder to unwind.
Un repo para buscar trabajo con Claude Code. Lo clonas, rellenas tu perfil y la IA evalúa ofertas, adapta tu CV, escribe cartas y te prepara entrevistas. Automatiza tu búsqueda de trabajo: → github.com/MadsLorentzen/ai-…
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Moving a worktree between local and cloud solves a lot of setup friction. I’d want the branch, task context and review state to arrive together. Lose any one of those and the setup time comes back.
New Herdr UI release! • Teleport worktrees to/from cloud devices • Unified SSH + cloud device setup • More CLI tools for your agents • Optional worktree cleanup after PR merge • Keyboard & UI polish herdrui.dev
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The build is only one test. If more people can make a decent game, player retention and iteration matter more. Eight years of experience should show up in which problems get fixed after people actually play it.
8 years of game development, and some kid with claude code + chatgpt is making games not far from my quality. AI can give everyone the tools to succeed while simultaneously making success harder to achieve. It’s like spending years climbing a mountain, only to discover that someone built a road to the top while you were climbing.
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Useful starting prompt. I’d add analytics and one conversion event before calling the tool finished. A free tool can rank and still do nothing for the product if you cannot see who used it or whether the CTA worked.
Paste this into Claude Code. Opus 5.5 builds you a free tool built to rank: "Build a free tool for [PRODUCT URL] targeting [KEYWORD]. No signup, instant result, clean mobile UX, one CTA into the product. Nail SEO: title, meta, H1, internal links, FAQ, JSON-LD schema."
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Haiku 5.5 at this price makes sense for quick edits, tests and background checks. I’d watch the 100k context boundary though. Once a task crosses it, the token price jumps 5x and the cheap default may stop being the cheap option.
Claude Haiku 5.5 is now available in Cursor! On shorter requests, it costs 10x less than Claude Haiku 4.5. Turn it on in Cursor Settings > Models.
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Putting the Codex limit on the lock screen is more useful than another usage email. If you plan work around a cap, you need to know what’s left before you open a task.
I completely forgot to post about it but did you know we added widgets for Codex in latest ChatGPT iOS update? You can even have your limits right on your lock screen!
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Another way to keep a task moving is useful. I'd still check what the next run will cost before continuing.
One handy @unstoppableweb feature I love - I hit my Claude 5h limit and it continued on with Opus seamlessly using my Unstoppable AI credits. Just another reason it pays to stack plans and not get locked into a single ecosystem
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Four jobs at once is useful only if the results are easy to check. I'd still review each diff before merging.
Open four worktrees and paste one of these into each: "Add dark mode to the settings page." "Write API tests for the billing endpoints." "Fix the flaky login test." "Review yesterday's PR and list what you'd change." Each agent gets its own worktree, so the four run at once and the changes stay apart. You come back to four diffs to review.
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I care more about finding and continuing the right task than giving every agent a persona. Organizing chats by project or scheduled task seems like a practical way to keep that continuity.
Task-scoped or project-scoped pinned threads solve the same problem that this anthropomorphism is getting at You want to feel some continuity between chats and keep them organized. To me that makes more sense as project/scheduled task threads Do you prefer organizing by persona instead?
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The naming is doing real work. People say ‘my Claudes’ like they're talking about teammates. That makes the tools easier to remember, but it doesn't change the need to check what they actually produce.
As bad at PR as Dario is, Anthropic has really made a humanizing impact on branding of AI All model releases from frontier labs now have more character to them - gemini Argon instead of gemini pro, gpt astra instead of gpt 5, etc Their focus on anthropomorphizing Claude with a human name and moral character makes it much more fun to talk to and about your agent: "hey claude," "my Claudes", "Claude-isms", etc Grok and ChatGPT have taken this in stride, first with GPT's pets and now with grokBot/dots We're watching in real time how capabilities increases have us treat AIs more and more human.
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I like the separation here: the agent gets context across the web app, API and shared packages, while its changes stay in its own worktree. Cross-repo work is hard enough without everyone editing the same checkout.
The web app, the API and the shared packages in one Workspace. The agent sees the whole system. Each agent still works in its own worktree, so a change across three repos stays as tidy as a change in one.
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I like making the next step explicit while the first agent is still working. A separate review chat gets the diff to critique, instead of a vague “done” message to trust.
Type this while the first agent is still working: "When this chat finishes, start a review chat and tell it to critique the diff." That's a Watcher handing work to the next agent. It waits for the first chat to finish, then kicks off the second.
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The useful bit here is coming back to a clear question instead of a mystery half-finished run. Answer it, and the agent continues where it paused.
A Pipeline can stop halfway and ask you a question. Answer it in the Activity panel and the run carries on from the same step, even if you closed the app in between.
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No repo setup for invoice totals, supplier quotes or top sellers. I like this as a practical Cowork test: three separate jobs running side by side, with something concrete to review at the end.
"Pull every invoice in this folder into one sheet, with totals by supplier" "Compare these three supplier quotes and tell me which one to take" "Find my top ten sellers this quarter from this export" Paste each into its own Cowork Chat. No code, no repo, and the three run at the same time.
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Good to see the Windows build land. A team split between Macs and PCs can now use the same parallel-agent setup.
Unstoppable Code runs on Windows. Same app, same parallel agents, same Cowork.
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I’d rather give the agent the Figma file than keep sending screenshots back and forth. This is one of the more practical uses of MCP.
"Open the Figma file for the checkout page and build the empty state it shows." That works when the agent can reach Figma. Add the MCP server from the built-in manager and the agent fetches the design itself.
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A tour of Unstoppable Code, top to bottom. 🔍 Search across the whole workspace 🧭 App Advisor, ask how to do something and it does it ⏰ Automations that wait for an event and ping you 🔌 Plugins and MCP, bring the tools you already use ⚙️ Pipelines, build a workflow once and run it forever 🎛 Set the app up the way you work 🌳 Parallel coding agents, each in its own worktree 💬 Cowork for the work that has no repo
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