Interesting stuff I found - February 2026
Google Technical Writing course
I am chewing through the course. Good tips, maybe you could distill it to a technical writing agent/reviewer?
Azure Verified (Bicep) Modules
When I was last deep in Bicep, sharing module definitions was difficult (GitHub submodules…), and best practice guidance was non-existant. It seems things got a lot better, and there is now lots of “Azure Verified Modules” (AVM) to get you going on the right path, and it is possible to consume modules via URL reference (not sure how the supply chain attack story is though…)
Still not convinced that declarative languages are the way to go for resource definition, I think the Aspire/Azure CDK people are closer to the optimal solution. At any rate, I am 100% convinced you need a strategy for applying your infra definition code continuously (periodically, also when nothing changes), otherwise it will bit rot and you will be afraid to apply it when it matters.
Passkeys
Working with a passkey rollout plan, and I am digesting the tome linked below, to come up with personas and a scenario test plan.
When they work, passkeys are wonderful and secure. But I think the mental model is very difficult to grasp for the average user - which can quickly translate to support needs when things start going south.
Azure Key Vault Emulator
Microsoft now supplies an Azure Service Bus emulator, but still no Key Vault emulator. This guy did the hard work, and that will come in handy with local-dev Aspire and not least using it in a TestContainer and the real-port hosting option for WebApplicationFactory in .NET 10.
Evaluating LLM coding agent innovations
Pete Hodgson argues that the real issues in LLM coding is context management and bad design taste. He uses that to evaluate which of the flavor-of-the-month techniques (e.g. Ralph) and innovations to track closely
Assessing the Latest AI Coding Hotness
AGENTS.md docs index vs skills
Picking up on the above, context engineering is obviously super important. Especially when it comes to new versions of frameworks, on which the LLM is not properly trained.
Vercel faced that issue with a new version of next.js, and ran experiments with Claude to see if skills were the right way to inject the appropriate context.
It turns out coding agents do not call skills reliably, so a compressed index of the next.js markdown docs in AGENTS.md worked better.
AGENTS.md outperforms skills in our agent evals
Writing a good AGENTS.md
Also in that area, this article considers what to put in AGENTS.md, and reminds that at least Claude (and presumably also Copilot, OpenCode etc.) will often ignore it if it determines it is not relevant.
I really try to grok the principles people are uncovering, and am experimenting a lot.
Writing a great AGENTS.md
From good to great, Matt Nigh from GitHub chimes in with an analysis of 2,500 AGENTS.md files and concludes that it must cover 6 core areas:
I got the link from How to write a good spec for AI agents, but I was turned off by his misquoting of the lethal trifecta (AI slop?) - and who seriously uses GPT 4 for anything now?
How to write a great agents.md: Lessons from over 2,500 repositories
Oh-my-posh visual configurator
Nice, vibe-coded app for building out your terminal. I will give it a shot if I tire of the default Aliens theme, which I recently started applying to all my machines with the Oh-my-posh DSC provider. (my basic setup of Aliens can be DSC-applied with this file)
Introducing Oh My Posh Visual Configurator
WinGet (DSC) Configuration
Picking up on that, nice to see some docs on DSC / winget configure- that would have been nice 14 days ago when I sifted through it!
Relationship between winget and DSC v2/v3 is still spotty (see comments), and there really need to be more non-imperative providers for dev stuff beyond “switch on dark mode”. Basically nothing seems to have happened on that front since the build video.
But with more eyeballs, maybe it will gain some traction?
WinGet Configuration: Set up your dev machine in one command
Context switching with AI agents
Nice treatise on how to handle the excessive context switching that arise from constantly waiting on (multiple) agent workstreams. The middle ground between “too slow to stare and wait, too fast to do meaningful work in the meantime” is a bad place, always has been (for builds, deploys, reviews etc. etc.)
The biggest obstacle for engineer productivity in 2026
Real-world apps (or: Medium clone built in … everything)
Interesting concept: Build the same app in different stacks. Great as a learning tool and to compare approaches
Playwright CLI
Spent a bit of time with an open browser window to the left, Playwright CLI in a VSCode windows (with Grok Code Fast, so free model) to the right. It is fun to describe what to do and have the agent do it in realtime. It seems there is quite a pivot from MCP to CLI-based skills at the moment.
Addy Osmani’s LLM Coding Workflow
Addy Osmani’s LLM coding workflow closely mirrors my own approach. He emphasizes clear plans before coding, small iterative chunks, extensive context, human oversight with testing and frequent commits.
My LLM coding workflow going into 2026
The art of KPop Demon Hunters
Very nicely done, love the music and looking forward to the lego sets.
AI-assisted coding: Same game, different dice
The article presents a contrarian view arguing that most AI teams see only 0.8x-1.2x productivity gains (not the promised 10x), and that success comes from fundamental practices like TDD, modular design, and small iterative chunks. I think that is a bit pessimistic, especially for resource constrained teams that struggle to fill all roles, but good balance to all the hype.
The AI-Ready Software Developer: Conclusion – Same Game, Different Dice
Canonical logs and structured logging
Excellent summary of canonical logs and related concepts, though implementing this pattern in .NET is challenging since standard libraries default to traditional structured logging rather than canonical logs.
Logging Sucks Evlog - Event-based logging tool
Vibe coding paralysis and managing workstreams
Trying to do too much at once with AI tools can lead to cognitive overload and unfinished work; it’s important to track what you’re building and read the generated code to maintain confidence and keep your skills sharp.
Vibe coding paralysis: When infinite productivity breaks your brain (Francesco Bonacci on X)
Summarize.sh: Fast, Scriptable Summaries
Summarize.sh is great at summarizing YouTube videos (and other types of content). I got it working with Azure AI Foundry GPT-5-mini with a bit of tinkering.
Sundhedsdatabanken
Drill into Danish medicine consumption in PowerBI. The Danish government has been tracking this stuff for 40 years, it opens up a lot of interesting possibilities for science.
Google A2 vs Microsoft Agents SDK
Erik Meijer contrasts Google’s A2 for dynamic with Microsoft Adaptive Cards (which I had never head of). Agentic UI is surely something that will become important as semi-autonomous agents starts to gain traction.
Google introduces A2 for dynamic UIs Microsoft Adaptive Cards Erik Meijer’s post on X
HTTP’s evolution: forced by reality
Great overview of how HTTP changed over decades, each version adapting to new constraints like latency, mobile, and unreliable networks—never by design, always by necessity.
HTTP Over the Decades: A Story of Physics, Latency, and Grudging Adaptation
2025: LLMs, agents, and everything else
Massive roundup of LLM developments, trends, and tools from 2025—so much happened it’s hard to keep up, and the links alone show the scale of change.
Simon Willison’s 2025 LLM Year in Review
Grounded AI adoption: Mitchell Hashimoto’s journey
Interesting and grounded take on the journey to see value in agentic coding, without drinking all of the “Ralph Wiggum” kool-aid.
My AI Adoption Journey – Mitchell Hashimoto
Shannon - autonomous LLM pentester
Shannon is an LLM-powered, autonomous pentester. Have not tried it out, but would be interesting to see it work against Supercar Showdown
Brace for the f***ening
What if the Tech CEOs ends up being right and white collar work disappears quickly? The most likely case is that they are inflating expectations to keep investments flowing (into the bubble) but what if…?
Outcome engineering and the o16g Manifesto
I respect Charity Majors, so I am inclined to take this seriously weight on this, even though it seems a bit ahead of things as they are. I certainly think there are other blockers than pure cost in development still.
Large Language Models Will Never Be Intelligent, Expert Says
It is hard not to be confused, I am thinking “two movies, one screen” here.
Large Language Models Will Never Be Intelligent
Amp drops VSCode plugins for CLI
Amp is killing its VSCode and Cursor extensions, shifting focus to a pure CLI approach.
Amp announcement: The Coding Agent Is Dead
Local CI
Safia, like DHH, advocates for “local CI” as the future of validation, moving away from slow PR-based loops. I think it makes sense if you run that verification in containers, and have a mechanism to attest that it happened (to prevent sloppiness).
The AI Vampire: Who profits from 10x output?
If AI coding agents can deliver 10x productivity, what is the cost? And who will profit?
The AI Vampire: Steve Yegge on value capture and burnout
Software is far from dead
Steven Sinofsky argues that AI won’t kill software, but rather increase the demand for it by moving functionality up the stack and making domain expertise more critical.