The notebook
Two kinds of writing. Bugs that produced no error message and cost me real time in a real codebase — and first-person accounts of learning to ship software without ever having been a developer. All of it first-hand.
Suman Debnath spent nine years in brand and performance marketing before building any software. Starting in late 2024 with a reminder app abandoned on a free tier, he has since shipped twenty-one products, trained a language model from scratch and run a fleet of autonomous agents — with no computer science degree and no developer job.
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Working notes, newest first.
Worth your time
An ancestor with overflow: hidden becomes the sticky element's scroll container. That container never scrolls, so the sticky child has nothing to stick to and scrolls away with the page instead. Nothing errors and no warning appears. Check every ancestor for overflow-hidden before touching the sticky element's own CSS.
Also worth it
React StrictMode mounts every component, runs cleanup, then remounts. A module-level `if (initialised) return` guard is set on the first mount, survives the cleanup because it lives outside the component, and blocks the second mount from ever re-attaching its listeners. The feature is then dead for the whole dev session while production works fine.
The notebook's shape, rather than its order.
The rest of the notebook, newest first.
Search optimisation competes to be ranked among ten results; answer optimisation competes to be the one passage quoted. The unit shifts from the page to the self-contained block, the currency shifts from keywords to resolved entities, and the outcome becomes largely unmeasurable — there is no rank to track and the same question returns different answers on different runs.
A weekend produces a working version, not a finished product — those are separated by weeks of unglamorous work. What makes the weekend possible is severe scope discipline and research before the first prompt. What makes it defensible is refusing to cut the handful of things that are cheap now and expensive later.
Taste is the ability to choose between options that are all technically correct, and it becomes the scarce skill once generation is cheap. A model optimises whichever metric it is given. Deciding which metric is the right one — and recognising when a measurable win is the wrong trade — is the part that cannot be delegated.
Probably not for search visibility. Google has publicly declined to support llms.txt, and reported monitoring of AI crawler traffic through 2026 found direct fetches to be negligible. Where it does get read is agent-side — coding assistants and desktop agents retrieving a domain because a user named it. Worth having if it is generated, not worth maintaining by hand.
Named tools are not skills, because everyone has access to the same tools and the claim cannot be checked. What survives scrutiny is anything with an artefact or a measured outcome attached: a process automated with the time saved stated, a system built and linked, or a described method for judging whether an output is correct.
In Next.js 16, middleware.ts is gone. The replacement is proxy.ts at the project root, exporting a function named proxy(request) and a config.matcher, and it runs on the Node runtime rather than Edge. The matcher is read statically at build time, so it cannot reference an imported constant.
Since three.js r152, ColorManagement.enabled defaults to true, so new THREE.Color(0xADC1DE) converts sRGB to linear before reaching the shader. Red loses proportionally more than blue, so colours picked against older releases drift violet. Nothing errors — the scene simply renders a different colour than the hex you wrote.
I documented that window scroll listeners never fire on this site because the body is the scroll container. Half of that was true: document.body.scrollTop does read 0. The conclusion was not. When I finally measured, a window scroll listener fired 19 times during a single programmatic scroll. The note had been steering design decisions away from working approaches.
Open to meaningful collaborations, AI-native systems, product strategy, and future-focused conversations.
“Human instinct. AI amplification.
Systemic execution.”
Suman Debnath
·Brand Marketing Leader & AI Product Builder
© 2026
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