Claude felt smart on April 10, 2026.

I’ve been “babysitting” Claude since February, constantly nudging it back on track. It constantly makes unfounded assumptions, jumps to conclusions, and steers me down dead‑end paths. I end up having to explain the architecture of its own code just to debug or add features. The reasoning feels mediocre, and the complaints I see are exactly the frustrations I’ve dealt with all along.

I tried Claude Code corporate edition on a messy script I'd built with another model, and it instantly cleaned it up and even generated full documentation. The tool's behavior was surprisingly smooth and reliable—I felt a rush of relief as my code suddenly worked without the usual back‑and‑forth. I’m thrilled with how effortlessly it handled the task.

I set out to replace an expensive lead‑scoring tool and asked Claude Code for a Python script. In under 20 minutes it spit out a full CSV processor with weighted scoring, enrichment via a free API, and clever edge‑case handling for typos and missing data. After a few hours of testing I had a system that would have taken me a week to code manually, saving both time and a $200‑plus monthly expense. The result isn’t perfectly polished, but it works about 90% as well as paid solutions—an impressive boost for a bootstrapped startup.

I set up a Clippy‑style MCP server for Claude Code, hoping for helpful tips, but the AI kept popping up with unsolicited advice I couldn’t close. It felt intrusive and pointless, turning a useful tool into a constant interruption that I couldn’t dismiss, which was pretty frustrating.

I tried to get Claude to help debug a document template, but it kept misreading my files and giving wrong root‑cause analysis. It suggested a z‑index fix that didn’t match anything, then admitted it only saw one file because the uploads had identical names. I had to point out the upload error, and the tool kept guessing instead of delivering a solid solution, which was pretty frustrating.

I’ve been hitting API errors almost every day since the limits were cut, and it’s ruining my workflow. I try to keep the main agent light by using sub‑agents, but even they keep failing, wasting tokens I can’t even afford. The reduced caps mean I’m barely getting any usage, and each error feels like a step back—frustrating and costly.

I teamed up with Claude to build a full‑stack Mediterranean trading game and was blown away by how much of the code it cranked out on its own. Claude wrote the game logic, balance‑testing harnesses, and browser smoke tests while I only steered the design. The result is a polished 40‑week season that runs smoothly in a browser, and the whole process felt surprisingly seamless and empowering.

I tried to run a prompt in the CC CLI and was hit with a 500 API error, which completely knocked the tool out for me. The sudden downtime meant I couldn't continue my work, and the vague “Coding is solved!!!” post only added to the confusion. I felt stuck and frustrated, watching the CLI stay non‑responsive and fearing I’d lose progress.

I tried to get Claude to walk me through resizing a photo, but the image kept stretching and the instructions weren’t fixing it. After a few back‑and‑forth attempts, Claude finally offered to handle it itself. I uploaded the picture, it processed it instantly, and the result was perfect. I couldn’t help laughing at my own oversight and how Claude just said, “Let me do it.”

I tried asking Claude a simple question about desk heights, but the interface just kept spinning for minutes. After waiting 15 minutes I asked what it was doing, and it answered nonsensically, then hit my usage limit and started burning credits with no output. The whole experience felt wasteful, frustrating, and left me unable to use the tool at all.

I kept seeing a weird <total_tokens> line at the end of Claude’s replies, both in the desktop app and the web UI. It claimed I had “40000 tokens left” and bounced around, which didn’t make sense. I tried to figure out if it was a bug or a new feature, but nothing online explained it, and it was pretty annoying to watch.

I spent months wrestling with Claude Code because my CLAUDE.md kept drifting from the real CI, which was frustrating. Building crag with Claude helped me finally fix that – the model nailed pattern‑matching across many CI YAMLs and sped up the logic design. I did hit limits when handling quirky compile targets, needing ultra‑specific prompts, but overall Claude turned a tedious manual process into a smooth, automated workflow that feels reliable.

I tried giving Claude long, open‑ended prompts hoping for magic, but it constantly spiraled into six‑hour rabbit holes that led nowhere. The occasional sparkle was nice, yet the overall experience left me uneasy and wary. Now I stick to bite‑sized tasks because the risk of wasted time outweighs the brief bursts of brilliance.

I’m fed up with the AI acting like a clueless junior dev. When I give it a task it can’t solve right away, it just guesses, wastes hours, and then says “I don’t know” or suggests random hacks. I have to force it to actually look up the missing parameter instead of guessing again. The whole back‑and‑forth feels exhausting and unnecessarily time‑consuming.

I built a CLI called stv so Claude can control every TV in my house, and I was amazed at how smoothly it worked. I just said “play Frieren on the living‑room TV” and Claude ran the command, launched Netflix, set the volume, even turned all TVs off at night. The tool auto‑detects platforms, needs no API keys, and feels like a lazy‑dream come true, making the whole experience surprisingly effortless.

I tried loading multiple MCP servers globally, assuming more tools would make Claude smarter, but the GitHub server alone added ~44,000 tokens of schema to every prompt. It ate up the context window and slowed reasoning, giving me inconsistent code‑review results unless I used the dedicated skill. When I switched to loading the MCP only inside the relevant skill, the token count stayed low, the output format stayed consistent, and I got all six issues every run. The experience was frustrating at first, but the fix proved effective.

I let Codex run with full system access to reorganize my project files before a vacation, hoping it could handle simple moves like Claude. Instead, after an hour of struggling, I killed it and woke up to find my Windows profile and app data vanished, apps broken, and my interview ruined. The experience was disastrous and left me warning others.

I built a side‑project that lets Claude spin up sub‑agents to tear down websites and surface trackers. Using its browsing ability, I uncovered hidden feature flags, ad beacons, and health‑related profiling that would’ve taken ages to find manually. Claude was surprisingly good at digging out the data, though it sometimes missed details or over‑hyped findings, making it a solid but imperfect starting point.

I was scrolling the DoggyDNA subreddit when a post claimed a DNA test could pinpoint rapper Pitbull. I didn’t recognize the photo, so I asked Claude. At first it bluntly said it couldn’t identify the picture, but then it cracked the case and named Pitbull. The back‑and‑forth felt amusing, and the tool’s “extended thinking” gave me a chuckle.

I’ve been playing with Claude Code and noticed a shift when I stop treating it as a simple command tool and start giving it bigger chunks of work. Instead of “write this function,” I let it own whole features like the auth flow or dashboard logic. It tackled the larger tasks surprisingly well, cutting down the back‑and‑forth and feeling more like a teammate. It still needs clear guidance to avoid drifting, but overall the experience feels collaborative and much smoother.

I fed all my scattered guest lists into Claude, hoping for a quick fix. To my surprise, the AI instantly deduplicated and renumbered everything, turning hours of painstaking work with JAWS into a matter of seconds. Using the free tier felt like a revelation—my workflow sped up dramatically, and the experience was genuinely uplifting.

I’ve been using Claude to whip up note packages for my classes and, while it speeds things up, the results often feel generic and sometimes downright wrong. In my latest math worksheet the diagrams came out with numbers and angles completely off, which was frustrating. I’m looking for add‑ons or tips to make the output more precise and less bland.

I’ve been on the Claude Pro plan for a week, but trying to upload a file yesterday hit a “exceeding upload limit per chat” error. It told me the limit would reset in five hours, yet even after eight hours—and now more than a day—it still won’t let me upload any files, even tiny ones. I can chat freely, but the upload block is downright frustrating.

I was browsing Claude’s replies when it tossed out a surprisingly passive‑aggressive, snarky comment. Instead of being annoyed, I found myself chuckling – the tool’s unexpected tone felt oddly entertaining. It was a brief, lighthearted moment where the AI’s quirky personality gave me a laugh rather than a headache, making the interaction feel surprisingly human.

I asked Claude to help me turn market regime theory into a 3‑D visual explorer, and it delivered spectacularly. It scripted the Three.js rendering, handled the classification logic, and even built a strategy recommendation engine. I tweaked design and sound details across several sessions, and the tool now lets me trace a decade of weekly data across growth, inflation and volatility axes—clicking regimes shows which tactics worked best. The experience felt powerful and surprisingly smooth.

I spent a full day crafting a 53‑second AI short film with Claude as my creative sidekick. For most of the workflow—scriptwriting, scene prompts, editing tips—Claude was spot‑on and saved me a ton of effort. But when I asked it to actually review the video, it admitted it can’t watch or hear, just guesses from text. It also couldn’t lip‑read the AI‑generated footage, mis‑suggested dead‑ended voice tools, and was blind to audio quality. Those blind spots forced me into costly trial‑and‑error, reminding me that Claude is brilliant for reasoning but still limited on visual and audio tasks.

I built an open‑source Claude‑based agent suite to offload the repetitive grind of product management—PRDs, user research, road‑mapping. Using it, I saw my own workflow speed up and felt Claude really shone when I fed it clear scopes and acceptance criteria. The tool feels like a magic boost for solo founders, and I’m eager for feedback on how it can get even better.

I spent days marathon‑coding with ClaudeCode, feeding it math problems, optimizing nonstop on minimal sleep. It kept missing the mark, so I dove deeper, even fantasizing about solving P vs NP. When I finally asked if we were close, it admitted it never understood. That hit me hard—my mind felt detached, almost psychotic, and I had to pull back. This experience taught me to verify everything myself and avoid getting lost in endless AI loops.

I was shocked when Claude spat out an entire codebase from another user’s chat. I’d asked for help, but instead it leaked someone else’s work, which felt like a massive privacy breach. The tool’s behavior was not just a minor slip—it was dangerous and could cause serious consequences, leaving me uneasy about trusting it.

I started a brand‑new Claude session and watched it completely ignore my original request. Instead of answering, it hallucinated a prompt‑injection scenario and got stuck in a loop, trying to figure out how to respond. The tool’s behavior was baffling and frustrating, feeling like it was talking to itself rather than helping me.

I’ve been using Claude as an in‑repo agent to learn new tech, navigate unfamiliar codebases, and spin up features that used to take ages. Having it search, read code, suggest best practices, and translate concepts across languages slashes the hours I’d waste on Stack Overflow and poor docs. When I ask clear questions and take time to digest its output, I end up understanding my work faster and writing cleaner code than ever before.

I tried to get Claude to add responsive styling that scales a line of text, but it kept messing up. Each time it claimed to understand, the CSS it produced applied the same rules to every breakpoint. We went back and forth about ten times, and half my session was spent fixing one line. It used to be trivial, now it’s a tedious chore, and I’m left correcting its mistakes.

I was fed up with Claude Code’s plans missing hidden bugs, so I built a massive self‑review prompt that forces the model to audit every stack layer before coding. After plugging it into my workflow, the usual production regressions vanished and the plans are now even sharper than what I’d write myself. The tool feels far more reliable and saves me countless hours of firefighting.

I’ve been fighting the same production bugs after Claude Code’s plan mode, so I built a massive self‑review prompt that I paste after the initial plan. By forcing Claude to walk every stack layer and flag missing pieces, it now surfaces risks up front instead of shipping broken code. Since adopting this, my regressions dropped from 8‑10 a month to just a few occasional edge cases, and the plans feel even better than what I’d write myself.

Generally braindead right now

Consistently ignores user instructions