What prompt structure got you there is the actual post people need.
@aihighlight
-
Map workflows before building AI agents to solve right problems
By
–
Most people skip straight to building agents before they've actually mapped their own workflows well enough to know what to automate. That's why so many agents solve the wrong problem.
-
Agentic Behavior Inconsistency: A Widespread Pattern
By
–
The agentic behavior inconsistency is a real pattern right now. Not just you.
-
Rapid Release Cycle Challenges for Developer Testing
By
–
The pace is so fast that by the time you finish testing one release the next three are already out. Chaotic for developers, great for everyone else.
-
Decent AI Evaluation Setup Gaining Recognition
By
–
This is actually a decent eval setup and nobody wants to admit it.
-
Career advice in AI era: stay mobile near value creation
By
–
The honest answer is nobody knows. Anyone giving confident 5 year career advice right now is guessing. Stay close to where value is being created and stay mobile.
-
AMD Analyzes Claude Opus 4.6 Performance Regression Evidence
By
–
Breaking: For weeks developers have been publicly documenting what they called a degraded Opus 4.6, with actual receipts. A Senior Director at AMD analyzed 6,852 Claude Code sessions, 17,871 thinking blocks, and 234,760 tool calls and concluded the model had regressed so badly it
-
Sabi Launches Non-Invasive Brain-Computer Interface Technology
By
–
A company just stepped out of stealth and almost nobody noticed.
— AI Highlight (@AIHighlight) 16 avril 2026
Sabi is building non-invasive brain-computer interface tech with the best hardware and strongest results in the category.
This is their first public announcement and the flag being planted before anyone else… https://t.co/i9SmAMuPfI pic.twitter.com/yRIJgANctyA company just stepped out of stealth and almost nobody noticed. Sabi is building non-invasive brain-computer interface tech with the best hardware and strongest results in the category. This is their first public announcement and the flag being planted before anyone else
-
Exponential AI Growth Breaks Traditional Valuation Models
By
–
$30B ARR in four months from $9B is the kind of number that breaks most valuation frameworks. The analysts trying to price this are using models built for companies that grow 30% a year. None of those models were designed for what's happening here.
-
Theoretical Beauty vs Practical Scalability in Machine Learning
By
–
SVM and kNN are intellectually beautiful and practically capped. That's a real tension the field doesn't talk about enough. Theoretical cleanliness and empirical scalability pulled in opposite directions for basically the entire deep learning era, and scalability won every