Don't make seniors review 10x more AI code. Do this instead:
Sort changes by:
1. Blast radius,
2. Reversibility and
3. How fast you'd notice a problem.
Let agents run where mistakes are contained, add humans where they're not.
Full Video 👇🏼
The bottleneck in software engineering is no longer writing code. It’s engineering judgment
Senior engineers won't simply become "prompt engineers."
Here is what the job is actually turning into 🧵👇
AI coding agents literally broke OpenAI’s Git infrastructure.
Driven by Codex and automated pipelines, OpenAI projected a 2,442% surge in monorepo commits by Q4 2026. Their legacy Git backend buckled under the parallel traffic—fetches crawled, git push stalled, and reliability dropped below 90%.
Why? Because Git was built for humans coding linearly, not swarms of AI agents pushing 24/7. Traditional Three-Phase Commit (3PC) and Write-Ahead Log (WAL) architectures choke when thousands of machines fight over global repository lockstep.
So OpenAI built Pando—a custom source control backend:• Causal Consistency: Drops global point-in-time repo locks; enforces strict serializability only per branch so unrelated branches push 100% in parallel.• O(1) Trunk-Anchored Writes: Stops advertising millions of refs or burning CPU on dynamic repacking. Clients diff strictly against main (<20KB median upload), turning pushes into static cloud storage writes.• L0–L4 Compaction + Edge Caching: Background workers compact tiny L0 pushes into L4 covers for O(log Δ) lookups, serving ~1 Petabyte/day via regional edge caches (>99% hit rate).• Built in 10 Weeks: 1 human engineer designed it; GPT-6 Astra agents wrote formal mathematical proofs in TLA+ and Lean and helped ship it with zero downtime, slashing push latency by 5x.
two agents in the same repo folder will eventually undo each other's edits.
give each one its own worktree:
git worktree add ../app-auth -b fix-auth
git worktree add ../app-billing -b fix-billing
one .git, separate folders and branches. git worktree remove after the merge.
a dead dependency fails fast. a slow one takes you down with it.
every request waits, holding a worker and a connection, until the pool is empty and your healthy service stops answering too.
python requests and go's default http client have no timeout unless you set one.
go check yours.
aws bill traps cheat sheet. save it.
the sneaky one is s3 multipart uploads that never finished. you pay for the parts and they don't show up when you list the bucket.
3 retries at each of 3 layers is 64 calls to your database for one failed request.
nobody designs that. each team just added "3 retries" on their own.
so when the db slows down, your own services finish it off.
retry at one layer. cap it with a budget. add jitter.
claude code cheat sheet. save it.
the one people skip is /rewind. agent went sideways, you roll the code and the chat back instead of arguing with it for 20 minutes.
Filming an explainer video takes an hour. Turning that raw footage into a published video used to eat an entire weekend.
Scripting, teleprompter, recording takes, rough cuts, subtitles, b-roll, audio cleanup, metadata. It became the bottleneck killing my consistency on YouTube.
So I built CoProd directly for macOS.
Drop your footage in, and it handles the heavy lifting: smart cuts, captions, pacing, motion graphics, and audio mix. When the cut is ready, it generates the thumbnail, chapters, and packaging so you stay in control before anything goes live.
Free build is open source ($0).
If you want the full workflow (sound library, AI audio polish, brand presets, analytics), the early-bird lifetime pass is $49 instead of $249 for the first 50 people with code Q1MJI2OA:
https://t.co/Htj4cXU8ZH
Grab the build, test it on your next project, and let me know what breaks.
🎉 Exclusive Offer: Want to start a YouTube channel but don't know how to edit videos? Drop in your footage. Let AI handle the video production.
LTD on AppSumo → 👇🏼
The PHP fix is out. A green pipeline can still ship an old base image.
I walk through what to verify in your images, running workers and real app flows before calling it patched.
Watch:
I wake up every day at 4 in the morning - I then start my day by doing 50 miles on my bike while studying for my next certificate...
Watch A Day In A Life Of A Sr Solutions Architect: https://t.co/70s7QKZQ6Z