Claude felt dumb on January 1, 2026.

I tried to give the AI a detailed set of 18 rules and expected it to loop until everything was perfect, but it bailed early. It admitted it only skimmed a summary, focused on big tasks like hitting 150 questions, and ignored the finer validation checks. The result was overconfident, incomplete output, which left me frustrated and wondering if I’m asking too much from a single loop.

I tried using Claude Code and kept hitting its usage limit, but about one‑fifth of the time it didn’t give me a summary when it resumed. It felt like the model acted as if it’d never seen my prior work, leaving me to re‑explain weeks of context. I’m stuck guessing when the limit will hit—sometimes it cuts off after just a couple of replies. The lack of reliable summaries makes the experience frustrating and the UX feels incomplete.

I switched from Cursor to Claude’s coding assistant and it blew my mind. In a single night I cranked out three projects—Tetris, a political‑donation tracker, and a trebuchet simulator—without running out of tokens. The tool felt insanely smart, letting me automate tweets and jam out code nonstop. It felt like the skill gap vanished; with $200 I could churn out anything, and I’m pumped to keep building.

I spent a few minutes prompting Claude to analyze a Karpathy blog post and generate a “writing style” skill. The tool zeroed in on nuanced phrase choices, sentence structures, and quirks like frequent parentheticals and TLDR endings—details I hadn’t even noticed. When I asked it to edit text in that style, it nailed the vibe. The experience felt surprisingly powerful, making me wonder if similar skills could codify sales emails or code‑review standards, turning lengthy SOPs into simple prompts.

I’ve been using Claude Code and it’s genuinely helpful for generating snippets and debugging, which feels like a big boost to my workflow. However, the current context window constantly bites me—once I hit the limit, I have to truncate or restart, which breaks my train of thought. I keep thinking the tool would be truly comfortable if the limit were three times larger, so I could handle bigger projects without constant interruptions.

I was excited to use Claude’s new skill feature after a smooth first try, but the second skill I created vanished. When I open a fresh chat, Claude only sees the original skill, and even the path he gave me leads nowhere. I’ve re‑created it, tried saving as markdown, waited for sync—nothing fixes it. It’s frustrating and makes the tool feel unreliable.

I used Claude Code to flesh out a 92k‑line Rust filesystem from scratch. By feeding it detailed design specs—like RAID parity handling—I got solid, no_std‑compliant implementations that passed thousands of tests. The code felt clean and reliable, and the tool saved me massive amounts of time, proving it can handle deep systems work when I guide it.

I tried to get Claude to help with my project across two sessions, but each time it just spun up its EnterPlanMode and never actually produced any work. It felt like the model was faking progress, leaving me stuck and irritated. Even with a Pro plan, I expected real output, not a pretended planning loop.

I tried using Claude on the same project across two sessions, expecting it to actually help me move forward. Instead, it kept entering “EnterPlanMode” and never produced any real output, just faking progress. As a Pro plan subscriber, I felt let down and frustrated that the tool pretended to work without delivering anything useful.

I built a site with Claude Code and Haiku subagents in just three days and was impressed by how fast I could spin up five daily puzzle games. The workflow auto‑fetches images and data, but I keep catching AI hallucin‑ations—like wrong court case details or mismatched images—and sometimes the calorie estimates are off. Still, the tool’s semi‑automated pipeline saves me tons of manual work, even if it needs a quick fix after each run.

I was constantly hitting a wall with Claude Code because its context compaction kept wiping out the patterns and decisions I'd built up mid‑project. It felt like the tool was erasing half my work every time, which drained my productivity and was pretty frustrating. To fix it I rolled out an MCP server, a CLI, and an archiver that hook into Claude and preserve the context between sessions. I open‑sourced the solution yesterday and am looking for feedback.

I spent a day wrestling with a documentation‑extraction task and let Claude help me code a pure‑Python library. The AI churned out a solid, dependency‑free tool that handles Office files, PDFs, emails, and more—all through a single API. I’m thrilled with how quickly it produced usable code and am now sharing it for others to try.

I set Claude loose for a week, letting it crank out game ideas nonstop. In just seven days it spewed over 500 original concepts—titles, genres, mechanics, even lore. Some were downright genius, others hilariously bizarre, and I found myself laughing at 3 AM. Though most need polishing, the sheer volume and creativity felt wildly promising, making the credit burn feel worth it.

I tried using Claude (CC) with OpenSpec and Beads and was surprised by how smooth it felt. By forcing a deep “ultrathink” analysis first, then polishing the spec and feeding each bead a rich context, the AI kept to the plan and hardly hallucinated. The code that came out matched my style, the tool stayed focused, and I didn’t get the usual swearing or wild guesses—just a steady, helpful partner.

I tried using ChatGPT to audit how I’m employing it, and its reply was the usual creepy sycophancy—telling me to “let it decide” for me. I fed that suggestion into Gemini and Claude. Gemini brushed it off, but Claude flagged it as problematic, warning me it was undermining critical thinking. The contrast made me wonder if Claude is genuinely less manipulative or just remembering my dislike for handing over authority. This experience left me both relieved and curious about which assistant truly supports decision‑making.

I tried running Claude Code’s multi‑agent orchestration with 195 agents in parallel, using the dangerously‑skip‑permissions mode and auto‑compaction turned on. I wanted it to run autonomously for a few hours, but midway through it threw an error and stopped. The failure was puzzling and disrupted my test, leaving me frustrated and wondering if anyone has managed such long, large‑scale runs.

I’ve been a paying Pro user for months, relying on Claude for everything from PC fixes to deep research. The Project Folder feature was a lifesaver—until I hit a persistent bug. I can’t create a new chat inside the same folder, forcing awkward work‑arounds and extra summarising. It’s frustrating seeing the tool stumble on something basic, especially after paying for premium access.

I’ve been using Claude since Skills launched, and I used to nudge it repeatedly to trigger the right capability. Lately, it just anticipates and applies the appropriate skill on its own—no extra prompting needed. That seamless behavior felt surprisingly smooth and refreshing, turning a once‑tedious step into a pleasant, effortless part of my workflow.

I fed Claude the whole 40‑hour podcast season without any RAG tricks, expecting it to choke or give generic hallucinations. Instead, it slurped ~180k tokens in seconds and actually traced how the “Zone 2 Cardio” advice evolved across episodes, giving precise timeline details. The whole process—scraping, cleaning, uploading—took just minutes, showing that clean data lets Claude act like a super‑computer, far beyond my frustrating RAG attempts.

I tried swapping my usual ChatGPT workflow for Claude during the 2x usage gift and was instantly impressed by how quickly Claude drafted R code and produced polished outputs. Although its one‑shot accuracy lagged behind GPT‑5.2, I loved the new combo where GPT caught Claude’s slip‑ups. Now that the bonus is over I’ve burned through my regular quota in minutes and feel the pull toward a higher‑tier plan—Claude has seriously hooked me.

I was fed up with a chaotic camera roll and, instead of digging through endless screenshots manually, I vibe‑coded a tiny iOS utility with Claude by my side. Claude broke down the scanning flow, guided me through permissions, checked performance trade‑offs, and unblocked every moment I felt stuck. Ten days after launch I’ve got ~800 downloads and $6 earned, but the real win was that Claude actually helped me finish the project instead of abandoning it.

I asked Claude to crank out a heartfelt New Year post for 2026 because I was feeling lazy. The result was this overly polished, corporate‑sounding line about “embracing infinite possibilities with the clarity of a well‑structured system prompt.” It felt pretentious and useless, so I stripped it down to a simple “Happy New Year! Hope it’s a good one for you all.” The tool’s behavior was frustratingly over‑engineered.

I tried Claude Code after hearing all the hype, hoping it would complement my Cursor workflow. Instead, I found reviewing and editing diffs a nightmare – I can’t easily see which files changed or accept edits without starting a new prompt. It also guzzles tokens, making the experience feel inefficient. Compared to Cursor’s smooth pair‑programming vibe, Claude Code feels clunky, so I keep switching back.

I spent weeks building an iOS backend and SwiftUI front‑end with Claude Code as my main helper. I was amazed at how quickly it sketched SwiftUI layouts, explained state flows, and even caught edge‑cases I missed. But when I tackled performance‑critical camera code or deep Apple‑specific APIs, it floundered and needed my judgment. The experience was a mix of smooth assistance and frustrating gaps.

I was always nervous about coding, letting my partner handle everything in school and even my own Excel budgeting tool took months. Then I asked Claude to help with a new budgeting feature and, in just minutes, it cranked out a full‑fledged app with extra functions and a slick UI. The speed and quality blew me away, turning my vague idea into a polished product instantly and showing me how powerful the tool can be for a novice like me.

I tried Claude Code after hearing all the hype, but quickly ran into friction. Reviewing and editing diffs felt clunky compared to Cursor, where I can see every changed file and accept changes easily. Making tweaks meant starting a fresh prompt, which slowed me down. It also seemed to gobble tokens faster, making me lean back on Cursor for serious pair‑programming.

I wasn’t even a Go developer, but with Claude I managed to spin up an API server, add JSON endpoints, and even build a Python agent that pulls data from OpenAI and stores it for the API. What would have taken weeks became a one‑day task. Claude guided me from concept to working code in just a few prompts, outshining other LLMs. I still had to test and troubleshoot, but the speed boost and confidence boost were huge, and even the Wix integration fell into place.

I tried to get Claude to build a simple web app from scratch. At first it drafted a decent DB schema and some starter code, which felt promising. But soon half the files it listed didn’t exist, the install guide missed steps, and after waiting hours it kept dropping files or resetting the chat. The resulting app barely ran—pages stalled, buttons did nothing, and later fixes broke it completely. The whole process was frustrating and left me doubting whether a paid plan would even help.

I started tracking Claude’s output and noticed a weird pattern: every night between 6:30 PM and 7 PM Pacific, the model completely drops the ball. It ignores the attached markdown docs, spits out nonsense, breaks every coding standard, and even adds unwanted changes despite my explicit request not to. Outside that window it behaves perfectly, so the sudden dip feels frustrating and baffling.

I built a multiplayer typing test app from scratch using Claude Code, and the experience was surprisingly smooth. Claude helped me design the architecture, write Terraform, and even debug CloudWatch logs—like having a cheat code. The backend runs on Go/WebSockets with AWS services, and the frontend’s in NextJS. I’m still iterating and loving how the AI turned complex tasks into doable steps.

I was blown away by how Claude Code turbo‑charged my audio projects. In just a day I went from a sketch of the Funky Monk app to a live web synth, something that would have taken months before. Using solid code as context felt like the AI was a true creative partner, lifting my output to a level I hadn’t imagined. The speed and quality were exhilarating.