Quick proposal: it's time to give up pull requests. PRs were built for a world where a human wrote code slowly, thought hard about every line, and needed a review gate before merge. That world's gone. Now half our diffs are LLM-generated, shipped in minutes, and iterated on faster than any reviewer can meaningfully read them. We're running 2024 process on 2026 output in a world every month is the equivalent of a decade of the 90s or 00s. Why it's broken: - Reviewers are rubber-stamping 400-line (or 1600-line) AI diffs because there's no time to actually understand them - The PR queue has become a bottleneck that punishes speed instead of enabling it - "LGTM" now means "I trust the model" not "I read this code" - We're optimizing for a review ritual, not for actual correctness or safety What to do instead: 1. Replace pre-merge review with continuous, automated verification — tests, type checks, behavior diffs, and LLM-based reviewers that actually read every line (they can, we can't) 2. Merge to main by default, gate releases instead of commits — ship fast, catch issues at the release boundary with real monitoring 3. Reserve human review for architecture decisions and irreversible changes, not routine feature work 4. Treat code as disposable and regenerable — if an AI wrote it in 10 minutes, the fix is often just regenerating it, not painstakingly patching a diff The goal isn't less rigor, it's rigor that matches the actual speed and nature of how code gets made now. PRs made sense when writing code was the bottleneck. It isn't anymore so maybe let's stop pretending our process should look the same? But hey, throw a proposal this way I'm open to alternate solutions to the current mess.

I am always intrigued by the mental disconnect of leaders who initiate layoffs (especially when they're financially not needed) and then expect the work those people were doing to still continue and finish on time. It's like a distinctive disconnect between reality for those leaders. Watching them unwind as their projects implode is a fascinating psychological observation. The other part of that which is fascinating is watching leadership go through with layoffs and then realize they have software that is largely untenable - the knowledge to run said software is gone and they're now stuck in a desperate situation of either having talent reverse engineer it (a hard task) or outright replace that software. So many large companies have done just that too. It's almost like AI, with an introspective hook into systems, could do the job of CEO if managed by the board better than a CEO can do those things. Actually no, it's not *like* AI (LLMs etc) could do it better, they easily could. We're already giving them access to many of the underlying systems (Github, Jira, Linear, etc) that they have a dramatically more intimate level of knowledge about who is doing what than the CEO could ever possess. The biggest gap right now is CEO's and other leadership aren't using it effectively for allocation of their people. Thus we still have vast inefficiencies in organizations and in all seriousness, as I've said time and time again, LLMs and what they can do has only amplified - many times over - how inefficient the organizations are allocated and setup. The questions now are; * how do we shape this change? * how do we make it serve us (org, people, customers, etc) * how do we identify the cruft to remove or reallocate? ....and so on. It's a wild time to be in tech right now. I haven's seen it this wild and insane since the early 90s when Microsoft got to the point of seeing a computer in every home. Back to the headwind, it's gonna be rough seas!

A post I wrote about the Gen AI/LLM gap between teams using it effectively - or even slightly - vs. those that aren't. That Gap Is Still Widening, But The Bottleneck Was Never Engineering https://compositecode.blog/2026/08/10/that-gap-is-still-widening-but-the-bottleneck-was-never-engineering/

Closing the Management Gap: Overcoming Organizational Bottlenecks

Discover how Generative AI reveals management inefficiencies and why organizational systems, not engineers, hinder productivity.

compositecode.blog

I’ve Been Brainstorming Durable AI for InterlinedList, and It Kept Pointing at Temporal. Thus, like I usually do I've been using InterlinedList to collect my thoughts and write up some posts. I've started publishing these on my blog at https://compositecode.blog and the first is live here: https://compositecode.blog/2026/08/11/durable-ai-for-interlinedlist-and-it-kept-pointing-at-temporal/

Adron's Composite Code Technological and coding misadventures!

Explore how to integrate Temporal with Vercel's serverless framework, ensuring durable AI execution without losing state or efficiency.

compositecode.blog

Building Durable AI in a Serverless Environment for InterlinedList

Explore the challenges of integrating durable AI into InterlinedList's serverless architecture, and discover effective design solutions.

compositecode.blog

It seems like there are a billion different folks babbling on in polished and fancy YouTube videos these days about how LLMs are doing work for em'. Some those are great videos with good information. A lot of other ones are just the same ole' same ole' repeat of many of the others. It's hard to truly make a good run of solid, reliable, and trustworthy content. It's also extremely difficult to watch videos and retain a lot of useful and significant information. MOST videos would be fine as a blog or email at a mere 3-4 paragraphs. Do you have any suggestions for GOOD video content that you find useful to watch? Even as background rambling? I'm in the process of collecting, and will be sharing my results in the near future! I'd however LOVE your help in putting together a more solid list beyond just what I myself have found. 🚀

Legit question here. There are studies and reports that have a vast number of people coming out of the education system with low reading and comprehension abilities. It was already a pretty significant problem in previous years, but now it is reportedly worse. If Gen AI/LLMs are basically just pushing us and leading many of us, much of what we do is read, respond, and then trust and verify what the LLMs are creating for us. How on Earth with this cratering comprehension among most people are we - as a society - supposed to maintain any reasonable and capable verification of the results LLMs provide us? The simple answer is we won't and can't expect that. It seems that might be the case. What is the resolution here? Emphasis on resolution vs. solution, because it's going to unfold however it does, it's clearly not in the wheelhouse of humanity to proactively do something about this now. What are your thoughts?