Shipped It, Then Took It Back Down
Shipped a live Claude tool on the site, pulled it back to local-only the same day, and fixed the Learn page's stale quiz pitch while I was in there.
// Pillar I — Learn
Learning in public. Sessions where I sit down at zero and try to leave with one thing locked. The misses are part of the data.
Learn
Learning Claude by building — six real projects, one lane →
Six varied, real builds, one at a time, each earning its own concepts as it needs them. No typecasting — the lane gets picked at the end, from evidence. Start with P1.
Free resource
Project Instructions Generator — a copy-paste prompt →
Hand Claude this prompt and it interviews you, then writes a strong set of Project instructions built on the four ingredients pros use. Free — grab it or get it emailed.
Learning the tool I build with every day, by building with it — six real, varied projects, one at a time, each pulling in exactly the Claude Platform concepts it needs. P1 (a single API call wired into a real workflow) shipped E38. P2 is a small lookup-and-answer agent — the loop, and tool use.
Shipped a live Claude tool on the site, pulled it back to local-only the same day, and fixed the Learn page's stale quiz pitch while I was in there.
My first live Claude API call. I explained it flawlessly six times while the file sat empty, then found my best decisions trapped in dead comments.
Finished Claude 101, certificate and all — now onto the next two. This session was the unglamorous part: a rebrand, study guides, and a Hire Me page.
Sat down to study Claude 101. Instead I built the entire course into my site, repainted the whole place, and studied exactly one quiz. A confession.
Module 2 taught me what a Claude Project is — and I realised I'd been hand-building one in my terminal the whole time.
I scrapped a data cert to learn the tool I already run three pipelines on, and finished the first module by refusing to polish it.
My code worked on my phone, so I thought I was done. Then an army of AI reviewers handed me a B minus. The gap between working and safe.
I watched six videos, understood all of it, and recalled none of it thirty seconds later. A short field report on the fluency illusion.
The graded quiz was one paste away — and it even tried to hijack the AI to answer for me. Here's why I closed it and studied instead.
Three sessions stalled trying to recall one definition cold. The fix wasn't more recall — it was building it up a rung at a time, then sealing it last.
Session 25 of the Google Data Analytics cert: why watching the whole module and knowing the material are not the same thing.
I started the Google Data Analytics course, then opened my own life logs to analyze. Months of records, and not one row I could query.
I'm pausing Python for the Google Data Analytics cert — the skill behind the tool I build. I'll learn it on my own life, not a textbook.
Two CS50 Python submissions in one sitting. The real lesson: typing a line someone hands you teaches you nothing.
I encoded four Python keywords into a house I used to live in. One of them hums 'no no no no no.' This is what studying looks like now.
What I thought was a session about conditionals turned into a rewrite of how I encode vocabulary at all.
Sat down to watch a 15-min video. Codified three method improvements instead. Some days the improvements ARE the work.
Expected 3, got 12. The fix was one word — but the lock was watching the bug fire on my own machine.
Showed up post-night-shift, locked one concept by REPL prediction, caught a new gap I'd never have seen on a 'make sense?' cadence.
Made it through Sections 14 and 15 of CS50P, then ran a test. Half the answers were wrong on operators I'd just covered.
Claude cited a summary file as if it were a transcript and built false vocabulary on top of it. The hard rule that came out of catching it.
Drilled an f-string definition six times. Didn't stick. Typed two lines in a Python REPL — locked in one contrast.
Three hours of architecture, one championship memory image, and one missed step that proved why the IDE matters.
A 5 out of 10. Three new loci encoded, two swapped on the test, the lecture got skipped. Sometimes the messy reps are the ones that compound.
Tested the same 13 palace items with two instruments and got 7.7% with one, 100% with the other. The instrument shapes the result.
Cold walk: 1 of 13 clean. Rapid drill same day: 8 of 13. The structural cue decays slower than the content riding on it.
Three days ago I declared four palace anchors locked. Today's cold walk found half of them collapsed. Memorization without retrieval is a lie.
I guessed Python threw the error. PowerShell did. The correction stuck because I'd already committed to the wrong answer.
Session 5. Typed hello.py twice without the python prefix, got yelled at by the shell twice, and finally understood what an interpreter does.
Session four was CS50P Lecture 0. Fifty-five minutes in, I hadn't typed a line of Python — the pipeline I built to protect the session was eating it.
Sat down to build a learning tracker in twenty minutes. Twenty minutes of research later, the schema I would have shipped was wrong.
Encode v1.0 was finished at midnight after a ninety-minute argument. The first real session tried to skip the rules. The rules held.
Day 2 of CS50P was supposed to be Lecture 0. Instead it was 45 minutes fighting the Windows Python shim. Zero curriculum. Streak preserved. 4/10.
A nine-day gap proved that memory decay is a maintenance problem, not a technique problem.
Engram is the memory training thread — spaced repetition, encoding techniques, and what I can actually recall a year from now.
Encode is where AI learning gets locked into memory palaces — not just studied, but placed somewhere I can walk back to and retrieve.