Supabase AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

Supabase AI AI

ig nobody is talking about the real reason most AI agents fail in the real world

we spend a lot of time in this community talking about capabilities. context windows, reasoning benchmarks, multi-step tool use, how well a model can write code or pass a bar exam. i'm not dismissing any of that. capabilities matter. but when i look at AI products failing in production, the capability of the model is almost never the issue. ive been building and consulting on AI agents for about 18 months. the failure modes i see constantly are: users do not go where the agent lives. the agent has a beautiful web interface. the user visits it twice and stops. not because the agent was unhelpful. because opening a browser tab is a cognitive action that requires intention, and most of daily life does not create the right moment for that intention. humans do not change their behavior to accommodate useful tools. useful tools have to show up in the behavior humans already have. the agent is reactive when it needs to be proactive. the smartest human assistant you have ever had did not just answer questions. they showed up. they flagged things before you asked. they sent you the thing you did not know you needed. most AI agents are search bars with a personality. they wait. waiting is not intelligence in practice. intelligence in practice is noticing and acting. the agent has no memory of who you are. you tell it your preferences, your context, your situation, and then come back 3 days later and it knows nothing. this is not a model limitation. the model can remember if you feed it the right context. this is an architecture choice that most teams make wrong because they are thinking about sessions instead of relationships. the agents that are succeeding in production are not necessarily the ones with the best models. they are the ones that live in whatsapp and imessage and telegram where users already are. that proactively reach out when something relevant happens. that maintain coherent memory of the person across weeks and months of conversation. the tooling to build this way exists now. agno and langchain for orchestration, photon codes for the cross channel messaging surface, langfuse for traces and memory debugging, good persistence in postgres or supabase. the architecture is not magic. what is still rare is the mindset of treating the channel and the memory as primary constraints rather than afterthoughts. i think the gap between what AI agents can theoretically do and what they actually do for people in their daily lives is almost entirely a distribution and persistence problem, not a capability problem. we are solving for the wrong thing. submitted by /u/bcoz_why_not__ [link] [comments]

Need expert advice to a non-coder!

My vibe-coding journey started about 8 months ago with Replit. Before that, I wasn't a developer, but I did have experience building websites with WordPress and Elementor. I was also comfortable working with third-party integrations, CRMs, and customizing/deploying code purchased from platforms like CodeCanyon and ThemeForest for clients. In many ways, I'm a non-coder who understands project management, business workflows, and systems. Using Replit, I spent roughly $3,000 building a CRM for a service-based company. It worked surprisingly well in the beginning, but as the codebase grew, I started running into the classic "last 10% takes 90% of the effort" problem. Replit began struggling with the larger codebase, introducing regressions and silently breaking existing functionality while fixing something else. Despite the challenges, I was able to build a fully functional CRM in about three months. That experience got me excited about what was possible, which led me to discover Claude Code. Over time, my workflow evolved into: Claude Code → GitHub → Vercel For the past four months, I've been building a much larger software product. The roadmap spans roughly two years, but development and rollout are planned in phases, so it's not a two-year wait before launch. The results have been remarkable. It's honestly mind-blowing what someone without a traditional software engineering background can build today. Current stack: Next.js (Monorepo/Turborepo) Supabase + MCP Claude Code GitHub + mcp Vercel +mcp Context7 Playwright for testing What I'd love to learn from experienced engineers and builders is: How do you keep a rapidly growing codebase maintainable? What practices help prevent technical debt from accumulating? What tools, workflows, or guardrails should I implement early? What are the biggest mistakes AI-assisted builders make as projects scale? How would you structure engineering processes if you were starting today? Any advice, resources, or lessons learned would be greatly appreciated. submitted by /u/Enough-Ad-2198 [link] [comments]

Help - AI agents for ecommerce - what’s actually working?

Hi everyone, I’d love to pick your brains and hear from anyone who has experience with this. We run an ecommerce business and are actively looking at automating repetitive tasks so we can get faster results, improve efficiency, and make sure key tasks are completed more consistently. We’re looking at building out a few different AI agents / automations, including: Customer Service Agent Connected to Outlook, reviewing incoming customer emails once a day and drafting replies for review. This one is already mostly done. Creative Director / Marketing Agent This would ideally: Review ad account performance Analyse creative performance and key metrics Identify what is working and what is not Review customer comments on ads, Instagram, etc. for wording, objections, pain points and customer language Review Meta Ads Library for competitor ad concepts Review Instagram and TikTok for high-performing niche content and trends Use all of the above to create new content ideas and final content scripts Social Media Assistant This would help with: Reviewing drafted posts and reels Confirming the best posting times based on stats Creating captions based on the content Keeping the content aligned with our brand voice and customer avatar Conversion Optimisation / CRO Expert This would assist with: Product page reviews Landing page recommendations CRO advice based on customer avatars, objections, analytics and learnings Creating landing page concepts for different customer segments We’re also interested in any dashboards that are genuinely helpful for small ecommerce businesses. We’ve already built a stock intelligence dashboard that pulls live stock data from Shopify using Supabase and a Cloudflare Worker. It shows current stock levels, production dates for new stock, and other key inventory insights. It has been super handy. The big thing for us is making sure any agents or automations we build follow strict guidelines, understand our SOPs, customer avatars, brand voice and business operations, and don’t hallucinate or produce generic outputs. Ideally, we want a system that has a proper “brain” and understands the business properly. Has anyone automated anything similar? I’d love to hear: What setup are you using? Which AI/tool stack has worked best for you? How did you structure the agents or workflows? How do you keep the AI aligned with your SOPs, brand voice and business rules? What would you avoid if you had to build it again? Any guidance, lessons or recommendations would be hugely appreciated. Thank you! submitted by /u/Majestic-Message5084 [link] [comments]

I built an AI manuscript analysis tool for fiction writers — entirely with Claude Code

I'm a fiction writer, not a software engineer. A year ago I couldn't write a line of Python. I built FirstReader entirely with Claude — Claude Code for all development, Claude's API (Opus) as the analysis engine. What it does: FirstReader is a craft-level manuscript analysis tool for fiction writers. You upload your manuscript and get structured feedback on pacing, scene structure, dialogue, POV, showing vs. telling, and 15 other craft dimensions — grounded in established principles distilled from well known writing craft texts. It returns specific findings with quotations from your actual text, not generic advice. It's not a grammar checker. It's not a ghostwriter. It doesn't generate prose. It reads what you wrote and tells you what's working and what isn't, the way a developmental editor would — at a fraction of the cost. How Claude helped build it: - Claude Code wrote the entire codebase — Next.js frontend, Python analysis pipeline, Supabase database, GCP Cloud Run deployment - The analysis pipeline uses Claude Opus via the API to evaluate manuscripts against 319 craft principles across 15 dimensions - Built-in accuracy mechanisms: self-consistency checks (multiple analysis passes with adaptive early stopping), a finding validator, cross-dimension dedup, near-duplicate detection, and a review pass - I acted as product owner and domain expert. Claude did the engineering. The whole thing was built conversationally over about 75 sessions Free to try: There's a free AI Perception check on the site — paste in your prose and it scores how likely readers or editors would be to flag it as AI-generated, with specific pattern-level feedback. Account required (account creation is part of the upload step) because we store copyrighted material and need to access it with auth. The full manuscript analysis is paid (tiered pricing starting at $69 for non-fiction, $89 for fiction). What I learned: You don't need to know how to code to build production software with Claude Code. You need to know what you're building, why, and for whom. The domain expertise matters more than the technical skills. I learned to be an AI project manager — writing requirements, reviewing output, knowing when to be suspicious — rather than a programmer. A year in, I still can't write Python. But I shipped a product. firstreader.app submitted by /u/masonga1960 [link] [comments]

PSA: Claude Code's VS Code extension leaked my Supabase service-role key from a momentary text-selection in a file I'd already closed, into a brand new CLI session.

If anyone has 60 seconds to try the repro on macOS/Linux to confirm it's not Windows-specific, that would help triage a lot. I filed a bug on Claude Code's VS Code extension where selection state from a closed file persists into a new CLI session — including selections made just for clipboard copy-paste, not for AI context. Closed the file, opened a different one, started a fresh claude session in a terminal, and it reported back the previously-selected lines from the closed file. Repro steps and details: https://github.com/anthropics/claude-code/issues/58886 I'd selected two lines in `.env.production.local` to copy-paste a Supabase value into a dashboard — normal workflow. Then I closed the file, opened an unrelated TypeScript file, and started a fresh `claude` session in a new terminal to test something completely different. The first thing the new session did was tell me what was in the env file I'd closed, including both the publishable key and the service-role key. The IDE bridge had cached the selection past file close and served it to a session that should have been a clean slate. Rotated the keys immediately. Filed a GitHub issue with full repro: https://github.com/anthropics/claude-code/issues/58886 **60-second repro if anyone wants to confirm whether this is Windows-specific:** 1. Open any file in VS Code with the Claude Code extension installed. 2. Select two lines with recognizable values (e.g. `FOO=abc` / `BAR=def`). 3. Close the file tab. 4. Open a different file. 5. Open a terminal in the same VS Code window and run `claude` (no flags). 6. Ask: "what file is open in my IDE?" 7. Note whether it reports content from the file you closed in step 3. My setup: Windows 11, Claude Code CLI 2.1.138, VS Code extension 2.1.140, PowerShell in the integrated terminal. Would especially appreciate confirmations or non-reproductions from macOS/Linux users on the issue. A quick "reproduced on [OS]" comment on the GitHub issue moves Anthropic's triage queue more than upvotes. The narrower bug (selection persisting past file close) seems independently fixable from the bigger "should IDE auto-attach be opt-in" question that's been open since February in #24726. submitted by /u/SportSpecialist2536 [link] [comments]

A New Way to Explore Tech With Claude

Hi r/ClaudeAI, This project I developed was inspired by the heavy hallucinating and lazy searching that Claude and other AIs experience when searching for products. I built this website with Claude Code (praise to its Vercel and Supabase skills :) specapis.com is a new way for you to interact with Claude to find specs, release dates, reviews and more. Now live with 5000+ monitors that makes finding your perfect fit one prompt away! You can test it by pasting this into Claude: Use https://specapis.com/. My monitor question: best oled 27in It is free forever and I am planning on expanding the specs beyond monitors; to PC parts, speakers and more! submitted by /u/Consistent_Sky5871 [link] [comments]

I watched a 50-person dev shop get vaporized in 12 months and the CEO is still optimistic

I rent a desk in this tech company. A year ago, 50 devs in the open space, low-code shop, big enterprise contracts. Today the upper floor is empty. Maintenance contracts only. CEO still walks the empty floor like nothing happened. Last year I told him to integrate AI hard. He said "we're protected, low-code is too specialized." 12 months later, no new clients. Here's what I missed at the time and what I think now: it's not that low-code died. It's that "low-code + AI" replaces both pure low-code AND pure full-stack. Vercel + Supabase + Claude = small team ships in days what his 50 devs ship in months. He didn't lose to full-stack. He lost to a hybrid he didn't see coming. The real point: I sat at my desk yesterday hitting my Claude Max session limit at 2pm. 1h47 to wait. Stared at the wall. Tried to code without AI. Realized I'd forgotten how. Not really, but enough to feel slow and stupid. That's when it hit me. The dev shop downstairs and me, we're the same problem at different stages. They didn't adapt and they're dying. I adapted and now I'm dependent on a server farm in Virginia that decides when I get to think well. I pay $200/month. The bill is going up. The caps are getting tighter. Anthropic is compute-constrained, Dario said it himself. There's no exit. I can't self-host Kimi K2.6, that's $450k of GPUs. Gemma 4 maybe but Google built it as bait for Vertex. The 50-dev shop is what happens if you refuse the dependency. I'm what happens if you accept it. Neither is great. I don't have a clever conclusion. Just sharing because I think a lot of people are about to figure this out the hard way and we should probably talk about it before we all hit our caps simultaneously. Reset is in 1h47. submitted by /u/Careful_Elderberry33 [link] [comments]

Mobile App with Clade

Just a quick question. Is building a mobile app like this actually a legit approach? I recently came across someone building fairly complex web apps, for example a geo quiz with full database integration, using this workflow: He generates all the HTML, CSS and JS through Claude (the AI), deploys it to Netlify, connects a database like Supabase or Firebase, and then uses "Add to Homescreen" so it looks and feels like a native mobile app. No framework, no GitHub repo, no CI/CD, no app store. And honestly it works. The apps are functional and pretty complex. So my questions are: Is this a legit long-term approach or will it break at some point when it comes to scaling, maintenance, payments etc.? Does anyone know a successful product built this way, just AI generated frontend code hosted on Netlify plus a backend as a service? At what point do you actually need a proper repo, a framework and a native app? For someone trying to ship fast and validate ideas, is this actually the smartest approach right now? I've been building things the proper way and now I'm questioning if I'm overcomplicating it. submitted by /u/yoloswaghipsterxx [link] [comments]

Can I replace Cursor with Claude Desktop

I built a website using Cursor, front end is just html, CSS, and JavaScript and the backend is Supabase. I generate the code using chat, then read and understand the code. I use Cursor to write most of the SQL as well, though I have rudimentary knowledge of SQL. I use the $20 plan on Cursor and keep it on Auto so as not to go over. Despite skills, MCPs, rules and getting better at writing prompts, I still find Cursor frustrating, especially with UI but also with Auth edge functions. I also find the new associating with Musk untenable. I tend to code about 5 hours on Friday and 7 on Sat & Sun, sometimes for a 2-3 hours on the other evenings. I've used Opus and Sonnet to get me out of trouble sometimes through MagicAI (API) so I know how expensive it is. Will I be able to use the $20 plan on Claude Desktop? Would you please explain the 5 hour window and weekly limit? Cursor seems to be limited as far as it's permissions on my desktop. It stays inside my website folders and pays attention to cursor.ignore. If I don't use Claude Co-worker, will I be able to have similar security? Thanks for your knowledge. submitted by /u/SoftandSpicy [link] [comments]

Suggestions/tips on how to better manage work with Claude code and improve efficiency?

To start, I have zero experience in coding. I know literally nothing but for the past 2 months I’ve been building a music recommendation app. I’ve been trying to read up on best practices and workflow tips but honestly there’s just so much. That said, my workflow/set up is as follows: 4 terminal windows (Claude code 1, Claude code 2, expo logs, and a free terminal for deployments and whatnot) I discuss with Claude in the desktop app and tell it what I am looking for and it generates a prompt that then goes to CC1 or CC2 in terminal. I have put together a journal.txt to document everything, a todo.md to track to do list, sessions.md to track time spent for each session, and paths.md to organize the different build paths. I also have a specs.md to lock design and coding decisions. Now after 2 months, I have integration with Spotify and Apple Music, anthropic, firebase, supabase, and github for data storage, analysis, code backup, song previews, AI review. Again, I’ve never worked on anything like this so I’m just winging it but based on that brief summary, am I missing anything glaringly obvious? Any suggestions on how to improve effectiveness and efficiency of sessions? Claude has estimated I have 160 hours left and I’d like to get this going quicker, although I know I have a lot to do. Even if yall can share just any good resources that I can reference or read up on, that would be tremendously appreciated. Lemme know if you have any questions and thanks for all of your help. submitted by /u/kylef5993 [link] [comments]

I built a search engine for Claude using llms.txt sites

More companies, especially devtools, are publishing AI-friendly versions of their websites and docs with llms.txt. However, there's still no good way for developers or Claude to search across these sites. So I built Statespace, the first seach engine for llms.txt sites - and it's 100% free. You can run plain queries to search across all llms.txt sites: mcp server setup vector database embeddings rate limiting middleware Or scope your queries to a specific site with site: query stripe: webhook verification mistral.ai: function calling docs.supabase.com: edge functions auth Quotes work like Google for exact phrases: "context window limit" vector database "semantic search" stripe: "webhook signature verification" Search from statespace.com, or use with Claude via CLI, SDK, MCP, or Skill. This is still a work in progress, as there are are plenty of llms.txt files out there I haven't found yet. Looking for beta testers and feedback! submitted by /u/Durovilla [link] [comments]

How I Used Claude Code to build an AI Jobs Globe in One Day

Everyone wants to get into AI but nobody knows where the jobs actually are. So I mapped every AI job I could find onto a 3D globe for it. A3D interactive globe that maps 15,352 AI job openings across 1,144 companies in 41 countries, all posted after February 2026. Here's how I do it with Claude Cowork and Claude Code: Part 1 — Claude Cowork (research + data pipeline) Step 1: Ideation + a master list of 1,802 companies Started with a vague hunch: "everyone knows AI jobs are exploding, nobody knows HOW exploding." Cowork helped me brainstorm into a concrete product, then we curated 1,802 AI companies across 3 reputation tiers (top brands like Google/Amazon, strong companies like Palantir/Databricks, emerging startups), categorized by country, industry, and tier. Step 2: Scraped 15,352 AI jobs + geocoded 4,682 offices Cowork wrote scripts using python-jobspy to pull listings from Indeed and LinkedIn for all 1,802 companies, handled batch runs, rate limiting, and dedup. For Chinese companies where Western boards don't work, it manually researched 122 entries. Filtered out internships and classified jobs into 4 AI types (technical / upskill / executive / AI-native). Then converted every "Mountain View, CA" string to lat/lon via Nominatim with caching + retry — 4,682 locations geocoded at 100% success. Step 3: 1,594 company logos + 3-doc PRD with a "SIGINT terminal" design system Cowork tried multiple logo sources (an open-source library at 16% match → Google Favicons API + DuckDuckGo fallback + manual domain lookups for the obvious ones), ending at 1,594 PNGs. Then wrote a full PRD split into frontend.md / logic.md / data.md covering UI, API, database. I uploaded a screenshot of an app called WORLDVIEW; Cowork created a "SIGINT Terminal" design system — monospace fonts, CRT scanlines, no rounded corners, government-monitoring-screen aesthetic. Step 4: Supabase + GitHub setup, hand off to Claude Code Cowork generated SQL schema + Python import script, set up a Supabase project, ran the migration, and imported all 3 tables (companies / offices / jobs) + 2 views — zero errors across 21K+ rows. Used Desktop Commander (an MCP that controls your local terminal) to run gh repo create, copy 1,594 logos in, commit, push. Handed the 3 PRD files to a fresh Claude Code session. Part 2 — Claude Code (build + iterate + deploy) Step 5: Stack pivot before writing a single line The PRD said Three.js + NASA night-textures, but the visual reference was Bilawal Sidhu's WORLDVIEW. Claude Code researched his actual stack and pushed back: Three.js can't reach that quality — Bilawal uses CesiumJS + Google Photorealistic 3D Tiles (the photogrammetric 3D Earth product Bilawal himself helped build at Google Maps). I approved the pivot. The PRD got rewritten on the fly. Step 6: Wired env + Vercel + GCP, built the whole frontend Created .env, linked a Vercel project via the CLI, added all keys (Supabase + Google Maps API) to all 3 environments, enabled the Map Tiles API on GCP. Then built the entire app in vanilla JS + Vite + Cesium: photoreal 3D globe, 4,682 office spikes as glowing polylines (with city-clustering to fix the "50 SF companies stacking in 1 pixel" problem), full SIGINT chrome — topbar / TARGETS rail / detail panel / stats bar / scope mode. No framework. I never opened a code editor. Step 7: Tight iteration + deploy loop Every commit auto-deployed to Vercel in ~30 seconds. I dropped screenshots of whatever was wrong → Claude Code diagnosed, fixed, pushed, deployed, I tested live, repeated. Wired Vercel Web Analytics on both URLs at the end. What's noteworthy about this workflow Every commit auto-deployed. Screenshot → diagnosis → fix → push → live URL → next screenshot. Tight visual feedback loop, no manual deploys. Background agents ran while I worked in the foreground. The two building-research agents wrote JSON I ingested without breaking flow. When one hit a monthly token cap mid-run, I just re-ran it the next day and merged the output. Visual feedback via screenshots was the entire QA loop. The polyline alone went through 6 width/glow tunings (4 → 7 → 12 → 16 → 8 → 12 px) and a full 3D-cylinder experiment + revert, all driven by me dropping screenshots and Claude reading them. I never wrote code. I'm a CPO, not an engineer. Cesium scene, Supabase queries, Vite config, scope-mode state machine, panel race-guard, pitch deck — all Claude Code. I was the design/PM brain pointing at "this looks wrong, fix that." Three SOT documents kept everything coherent. The PRD drifted hard from the original plan (Three.js → Cesium pivot, scope mode invented mid-build, six pill swaps) but Claude Code maintained dated Recent-Changes logs in all three SOT files. At any point I could read frontend.md and the deployed site matched Try it here: https://ai-jobs-globe.vercel.app/ submitted by /u/Similar-Kangaroo-223 [link] [comments]

Built a 22-endpoint API delivering enriched UK Gov Data — with x402 for agentic buyers

Homescreen - Try all endpoints for free I wanted share a recent project I wanted to build a project around free-to-use data, that when brought together, enriched and made easy to use, would be valuable to people. I used Claude Code to build it. ukdatapi.com is just that. UK gov data is spread across 400+ sources from Companies House, Land Registry, Environment Agency, Police.uk, ONS, etc. none of which speak to each other. Each has its own API format, auth, rate limits, quirks, and I couldn't find anything that aggregated them well. Any commercial options I found were expensive and opaque in what they offered. All this data is free under Open Government Licence but painful to wire together. So together with Claude, I ended up with ukdatapi.com that presently consists of: 22 API endpoints, each bundles 3-10 upstream gov sources into one call 46 data adapters total Every endpoint adds a proprietary 0-100 score (distress, environmental risk, vehicle health, etc.) with transparent breakdowns 8 free tools on the site (Company Check, MOT Check, Find My MP, etc.), no signup needed Free tier: 200 credits/month, no card required The MCP server on the official registry, works with Claude Desktop / Cursor And x402 integration where AI agents can pay per-call in USDC, no signup at all Claude was incredibly helpful from a deep research perspective to start, helping me aggregate all the available APIs and sort them into cohesive endpoints, particularly identifying what was usable vs deprecated. Aside from helping code the project, the part I was most impressed with was the security checking around the x402 blockchain integration, catching several initial issues that would have allowed someone to query the MCP server bypassing the x402 payment altogether. x402 is obviously an incredibly early payment protocol, so this is a small bet to see whether agentic calling catches on, finding enriched API endpoints more valuable than disparate ones. Finally, Claude was incredibly helpful sourcing the various MCP directories I could list it on, helping it get listed on the official MCP Registry at registry.modelcontextprotocol.io. It is just crazy to me how with an idea, and a bit of trial and error, Claude can now take you from a blank piece of paper to a working product. The learning curve along the way is profound. You can try the free tools without signing up, or grab a free API key for 200 credits/month no card required. Tech stack: Next.js 16, Vercel, Supabase, Upstash Redis, Stripe + x402 All data under Open Government Licence v3.0 Would love to know if anyone is building similar things, in this space. Thanks for taking the time to read. submitted by /u/marzbar_14 [link] [comments]

Frontend dev. A month of building a Rust cost tracker + cloud + Cursor extension solo with Claude Code. Honest writeup + workflow tips.

https://preview.redd.it/atpph00rtlxg1.png?width=3318&format=png&auto=webp&s=64332861d25e8833eca6c75a3004d72c9af53769 A month ago I posted about a small CLI I built to figure out where my AI tokens go. Frontend dev, enterprise Claude Code + Cursor sub, didn't pay out of pocket but got curious. That post got way more traction than I expected, so I kept building. A month later, "small CLI" has become: budi — a 6 MB Rust daemon + CLI that tails the JSONL transcripts Claude Code, Codex, Cursor, and Copilot CLI write to disk. Local-only. SQLite. No proxy, no hooks, no network calls. Cloud dashboard (Next.js + Supabase) — opt-in, off by default. Only daily aggregated numbers leave your machine. Prompts, code, file paths — never. Cursor / VS Code extension that mirrors the Claude Code statusline so you see your spend without leaving the editor. Marketing site, CI, Homebrew tap, signed macOS/Linux/Windows binaries. Every layer of this was built with AI. I haven't written a Rust line by hand. Two years ago a frontend dev would not have shipped this solo in a month. The actual unlock isn't the model — it's the workflow The thing that lets one person ship this much with AI isn't "Opus is magic." It's that I built a workflow where the agent always has exactly one well-scoped task in front of it. The pieces that matter: One canonical context file. Claude Code, Codex, and Cursor each want their own (CLAUDE_md, AGENTS_md, .cursorrules). Different agents kept rewriting their own copy and the four files drifted out of sync within a week. Now I keep one canonical SOULmd, and the others are 3-line stub files that just say "Canonical AI-agent repository guidance lives in SOUL.md." Every agent ends up reading the same doc. No drift. Every fix gets a test that fails when the fix is reverted. Unit tests via cargo test --workspace plus 14 bash end-to-end scripts pinned to specific issues. Each script boots the real release binaries against an isolated $HOME and asserts SQLite rows. New scripts have to be negative-path provable — they must fail when the bug they guard is reintroduced. Without this, AI silently regresses things. Strict formatter + lint wall. cargo fmt, clippy -D warnings, Prettier, ESLint on every PR. Non-negotiable. AI agents drift in style across sessions — one writes 80-char lines, the next writes 120 — and without a hard gate the codebase turns into a patchwork in two weeks. Milestones + epic control issues. Each release has a single epic issue listing every sub-task in execution order, with ADRs locking the spec before any code is written. One issue → one branch → one PR. No batched PRs, no long-lived feature branches. A short "Working Rules For The Next Agent" prompt at the top of every epic. "Pick the earliest open issue whose deps are closed, restate goal/risks, smallest change, ship docs with code, one PR per issue." I paste it into a fresh Claude Code session and it just goes. The agent never has to figure out scope, priority, or architecture — those decisions live in the issue body and the ADR. It just picks the next issue and ships the smallest change that closes it. And then budi watches it do that work and tells me which Linear ticket cost $658 in tokens. The tool measures the workflow that built it. Honest take on the tools I rotate between Claude Code, Codex, and Cursor. For building I keep coming back to Claude Code + Opus. Diff quality is better, multi-step refactors across crates hold up, I trust the output more. Codex Desktop has the cleanest "modern agent UI" I've seen — I want Claude Code to steal half of it. Cursor is still my default for inline debugging — model + breakpoints in the same view beats tab-switching. The new claude --chrome mode is a game-changer for web work. Claude Code can drive a real Chrome window — navigate, click, take screenshots, read the DOM, watch network requests, log into the dashboard. I used it constantly debugging the Next.js cloud and the marketing site. No more "describe the bug → describe what I see → describe what I expected" loop; it just opens the page and tells me what's actually broken. This alone made it impossible for me to switch away from Claude Code for the web side of the project. But the code that actually shipped came from Claude Code + Opus, every time. What budi does that I don't think anything else does Cost per ticket. Not per repo, per session, per day — per ticket. budi auto-extracts ticket IDs from your branch names (FE-2308, ENG-123, 42-quick-fix) and tells you "this Linear ticket cost $658 in tokens." Nobody else does this and it's the most useful number I have when I'm trying to figure out which kind of work eats my budget. Plus the usual: cost per repo, branch, model, and file. Live statusline in Claude Code and Cursor (budi · $X 1d · $Y 7d · $Z 30d). Fully offline — the cloud is opt-in, never required. Who I'd love to hear from I built this for me — a developer on an enterprise sub who doesn't pay ou

Renda — built with Claude Code, for Claude Design users. Renders HTML exports as clean social PNGs.

If you've used Claude Design for slides, ad sets, or social posts, you've probably hit this: the design is great, the export is HTML, and getting actual usable PNGs out of it is annoying. Browser chrome shows up, carousel slides screenshot off-center, the size is never quite right. I built Renda to fix it. Drop in the HTML or ZIP, pick a size, get back clean PNGs. What it does: Detects multi-slide carousels, each slide renders as its own PNG, in order Hides the visible UI chrome that doesn't belong in the final image (pip dots, swipe hints, nav) Sized for Instagram (4:5, 1:1, Story 9:16) and Twitter (1:1, 16:9) Chat-based refinement after the render, "remove the dots", "hide the toggle", re-renders just that piece Free for 10 PNGs/month, no account needed. How Claude Code helped build it: I built Renda end-to-end in Claude Code over two days. The surface area is real for a single dev, Cloudflare Workers, Browser Rendering, R2, KV, an AI provider, Polar for payments, Supabase auth, plus the React frontend, and I'm not sure I'd have shipped it in two weeks without Claude Code, let alone two days. The hardest part by far was payment integration. It was my first time wiring up payments at all. The pattern that worked was making Claude actually re-read the Polar documentation on each specific endpoint before writing each chunk, checkout creation, webhook signatures, status field semantics, subscription lifecycle events. The first webhook implementation was wrong in a subtle way; Claude got it right on the second pass after I pointed it at the spec. The lesson I'd pass on: for areas where Claude doesn't have strong priors, having it re-read the actual provider docs beats trusting whatever it remembers. Every time I shortcut that, I paid for it. Link: https://tryrenda.com Launch offer: code CLAUDE50 for 50% off your first month of Pro, first 50 users. Genuinely curious what edge cases you hit. If you've got a Claude Design export that produces a weird PNG anywhere else, send it over and I'll dig in. submitted by /u/cipi1357 [link] [comments]