Innovation & Technology Watch
Continuous tracking of AI tooling, JS frameworks, cloud platforms, and OSS. Distinct from Strategic Vision (product business idea generation): this one is the technical scouting that keeps my engineering choices on the right side of the curve.
Each segment is a period (journey or achievement) where the competency was applied. The colour and size of the end dot reflect the level reached during that period.
My definition
Innovation and technology watch is, in my practice, the structured habit of scanning the landscape (LLMs, JS frameworks, cloud, OSS, regulation) and turning weak signals into testable bets. I deliberately distinguish it from Strategic Vision (business idea generation at the board level) and from Problem Solving (in-the-moment learning): it is the long-loop scouting that keeps engineering choices on the right side of the curve and prevents a CTO from ageing out in 18 months.
I rely on 2 structuring rituals. Daily intake: RSS, specialised newsletters (Pragmatic Engineer, Latent Space, Lethain), OSS releases (Anthropic, OpenAI, Mistral, Hugging Face), changelogs of top-tier frameworks (Next.js, React, Bun, Drizzle). Quarterly synthesis: a personal tech-radar published with explicit verdict (adopt / trial / assess / hold) on 5-7 topics. On the validation side, I never let an innovation hit a customer production without a personal mini-project first - that is what let me bring AI-augmented workflows into production as early as 2024 and ship the first Tailwind v4 obfuscator in six weeks.
In 2026, the watch has a particularly active ground on JavaScript runtimes: Bun has reached mainstream adoption on new TypeScript projects, and its support shipped in public beta on Vercel Functions, as detailed in the official Bun runtime on Vercel Functions post. In parallel, edge runtimes are converging through WinterCG on identical APIs across Node, Deno, Bun, Cloudflare Workers, and Vercel. The CTO who can arbitrate a stack switch in 90 days today without breaking production has a 12 to 24 month product lead over the laggards.
My evidence
Anecdote 1 : Catching Tailwind v4 in preview to publish the first obfuscator
Mid-2025, my weekly watch caught a signal that flipped my schedule: Tailwind v4 was in public preview, fully rewritten in Rust/Oxide. The only existing obfuscator (unplugin-tailwindcss-mangle) relied on patching internals - and I immediately understood it would break the moment v4 went general availability. No market player was positioned on that transition.
I turned the watch signal into a concrete shipment in 6 weeks. Babel AST + PostCSS learnt from scratch, systematic validation against the Rust/Oxide Tailwind v4 engine, strict TypeScript, TurboRepo monorepo with 295 tests and 5 bundler plugins (Vite, Webpack, Rollup, esbuild, Nuxt module). I published to npm before the community had time to ship workaround hacks.
First Tailwind v4-compatible package on the market, 82K lines of TypeScript, picked up by external teams within the first weeks, organic mentions across multiple tech newsletters.
That episode showed me that the ROI of tech watch is measured in shipments, not in readings. The same watch also let me bring AI-augmented workflows into my delivery flow ahead of most CTOs in my network, and that is the posture I want to keep to stay relevant in the 2026-2028 market.
Anecdote 2 : Shipping 129K lines in 41 days with an AI-augmented workflow
Early 2026, a food-truck customer (Mon Camion Resto / MCR) needed a complete refit of their ageing WordPress site: 6 domains, 42 articles to migrate, 78 Next.js pages, 1,383 indexable SEO contents, multi-step forms, Stripe marketplace. The customer timing was 41 days. At my normal solo cadence that meant 6 months minimum.
I pushed to the limit the AI-augmented development chain I had been refining on other ACCENSEO engagements: Claude Code as primary pair-programmer, GPT-4 and Gemini on content generation and validation tasks. Modern stack Next.js 16 + Payload CMS v3 + Tailwind CSS 4 + PostgreSQL + Stripe + Terraform + GitHub Actions, 4 AI APIs wired into the CMS to generate articles, product descriptions, images. On every feature, I wrote a detailed instruction prompt and put every generated file through a manual review, with systematic verification scripts.
129K lines shipped in 41 days solo, 78 Next.js pages, 1,383 SEO contents, deployed to OVH VPS, and the actual productivity hovered around 3x to 4x compared to a non-augmented solo cycle.
That project locked in the conviction that well-tooled generative AI shifts the writing cost but not the review cost. That is why I keep coding in person rather than delegating: the watch tells me what to adopt, but the daily reading is what lets me judge what it is worth.
My self-critique
Level Senior. Structured tech watch since the Master ESIEA years, fed by a weekly cadence (RSS, specialised newsletters, OSS releases) and formalised in a quarterly personal tech-radar. What still needs strengthening: the public diffusion of the watch (newsletter, blog, talks) which would multiply its value.
Keeps the entire portfolio fresh. Without watch, a CTO ages within 18 months whatever the initial level. It is what prevents expertise from freezing and makes the other competencies (architecture, fullstack, AI) durable. and for a B2B scale-up CTO role, it is the lever that turns a weak signal into a 12 to 24 month product lead.
Reliability indicator
Catching Tailwind v4 in preview and shipping the first compatible obfuscator in 6 weeks, then bringing AI-augmented workflows into my delivery flow as early as 2024 when competitors were still at the demo stage. That is what validates the cadence of the watch, not the volume read, the lag between signal and shipment.
Distil, do not accumulate. Reading 50 articles a week is noise; writing one synthetic paragraph each week is signal. Keep a single canonical source. To others: pick 5 reliable sources and stick to them at least one quarter before evaluating, abandon generalist sources for practitioners, and always validate an innovation with a small personal project before bringing it to a customer in production.
My evolution in this skill
Innovation and tech watch keep the CTO scale-up profile viable beyond 24 months. They condition the ability to arbitrate a stack switch (Bun, edge runtimes, lightweight Kubernetes) within 90 days, hear a regulatory signal (NIS2, AI Act, e-invoicing) before the competition, and hire seniors who speak the same technical language.
The goal is to move from internal watch to public diffusion: personal tech radar published every quarter, at least 2 talks or long-form articles per year, and the ability to run an internal tech radar for a 10 to 30 engineer organization. The Senior-to-Senior+ shift is measured on the public dimension.
Weekly intake of releases from Anthropic, OpenAI, Mistral, Hugging Face and first-tier JS / TS frameworks (Next.js, React, Bun, Drizzle). Master in Software Engineering active until 2026, providing the academic frame to structure the watch.
Formal adoption of the ThoughtWorks Technology Radar methodology (workshops + tooling) planned 2026, advanced long-form technical writing training (Maven Technical Writing for example) targeted 2027 to move from internal tech radar to a published one.
Personal tech radar updated every quarter with explicit verdict (adopt / trial / assess / hold). Anchor reads: *Accelerating Innovation* and the public ThoughtWorks tech radars. Continuous follow of Hacker News, Lobsters, GitHub trending and scale-up blogs (Vercel, Supabase, Cloudflare).