What It's Actually Like to Use Claude Code for Everything

There's a version of this post that just shows you the numbers: 180 sessions, 256 commits, 974 hours, 5 projects. But numbers don't capture what it actually feels like to treat an AI as your primary engineering partner for two months straight.

So here's the honest version.

The Working Dynamic

I'm a high-velocity, production-oriented builder who treats Claude Code as a full-stack development partner across an impressive 974 hours of usage. My dominant pattern is driving end-to-end feature lifecycles in single sessions — from planning through implementation, code review, PR creation, and deployment. I frequently chain multiple tasks together in rapid succession: implement a bug fix, run a review, fix the findings, push the PR, then immediately pivot to the next feature. My TypeScript-heavy workflow (4,169 file touches) across what appears to be a SaaS product with MCP tools, Stripe integration, onboarding flows, and an embeddable chat widget shows I're building something substantial and shipping constantly — 256 commits across ~2 months.

My interaction style is distinctly impatient with planning overhead and biased toward action. A recurring friction pattern shows I interrupting Claude when it falls into exploration or planning loops — multiple sessions ended with me cutting off Claude after it spent 8+ minutes reading files and writing plans without producing code. I clearly prefer Claude to just start building rather than over-analyze. At the same time, I're comfortable giving Claude significant autonomy on execution: the heavy use of Bash (4,833 calls), TaskCreate (513), and TaskUpdate (1,037) suggests I let Claude orchestrate complex multi-file changes and parallel sub-agents without micromanaging. I only intervene when something goes wrong — like catching a race condition bug Claude missed, or correcting it when it tried to screenshot localhost instead of production.

My bug tolerance is notably high but my patience for repeated mistakes is low. With 53 buggy code incidents and 47 wrong approach frictions, I clearly accept that fast iteration means fixing things in follow-up rounds. I'll happily do three rounds of bug fixes on a demo page before pivoting to a redesign. But the 34 dissatisfied sessions tend to cluster around Claude's worst habit in my workflow: getting stuck in analysis paralysis. My most distinctive sessions show a pattern of stacking 4-5 heterogeneous tasks (feature implementation → deployment → bug fix → new planning → git operations) in a single sitting, treating Claude as a tireless pair programmer who should match my pace.

What This Looks Like Day to Day

Most sessions follow the same arc: I describe what I want at a high level, Claude decomposes it into steps, and then we iterate. The good sessions feel like pair programming with someone who types infinitely fast. The bad sessions feel like managing a junior developer who keeps misunderstanding the architecture.

The difference between the two? Specificity. When I say "add a delete button to the user profile with a confirmation modal that calls the existing deleteUser API endpoint," Claude nails it. When I say "improve the settings page," Claude spends 8 minutes reading files and writing plans without producing code.

The Projects

the platform SaaS Platform Development

85sessions

Core product development for the platform, a SaaS platform with dashboard, onboarding flows, agent chat, page editor, pipeline board, and analytics. Claude Code was used extensively for feature implementation (onboarding checklist, ownership transfer, demo lobby, collapsible sections, mobile responsive design), bug fixing (navigation issues, disappearing UI elements, cookie errors), and creating PRs. This was the primary workstream, heavily leveraging multi-file TypeScript/Next.js edits and iterative code review cycles.

MCP Tools, Connectors & Agent Infrastructure

35sessions

Building and debugging MCP (Model Context Protocol) tools, connectors (Calendly, a third-party service, Google Reviews), and an Evolution Engine for the agent system. Claude Code was used to plan and implement new tool endpoints, fix 12+ MCP tool bugs from QA reports, handle database migrations, wire up connectors across multiple agent systems, and push PRs. Sessions involved significant Bash commands for testing and deployment alongside complex multi-file TypeScript changes.

Stripe Connect & Billing Integration

15sessions

Full Stripe Connect integration including building the payment infrastructure, configuring production Stripe settings, fixing deploy bugs, and cost analysis/optimization with prompt caching. Claude Code handled the end-to-end implementation across server and client code, resolved production issues like trailing newlines in Vercel environment variables causing 500 errors, and documented the solution for future reference.

Marketing Site, Content & Video Production

25sessions

Work on a marketing/landing site including features pages with screenshots, OG images, favicon, privacy/terms pages, copy changes, link fixes, Resend email integration, and a dev blog built from Claude Code session data. Additionally, several sessions involved creating Remotion animated explainer videos and demo scripts for the product. Claude Code scaffolded full Remotion projects with scenes and design tokens, though some video planning sessions stalled in exploration without producing output.

DevOps, Deployment & Infrastructure

20sessions

Deployment workflows, Git operations, Supabase migration management, Vercel configuration, Terraform fixes for AWS (EC2 key pair issues), Google OAuth setup, and disk space/file cleanup. Claude Code was used for pushing migrations, resolving Vercel CLI project linking issues, fixing environment variable problems, cherry-picking commits, and managing branch merges. These sessions were typically shorter but critical for keeping production environments running smoothly.

The Meta-Pattern

After 180 sessions, the pattern that matters most isn't any specific technique — it's the speed of the feedback loop. The faster you can tell Claude what's wrong and get a correction, the more productive you are. Every workflow optimization I've found boils down to: reduce the time between "that's wrong" and "now it's right."