Still, AI isn’t worthless: it may benefit juniors or greenfield projects more than veteran devs on legacy systems. METR plans ongoing trials to track progress—stay tuned. What experiences have you seen with AI tools in real work?
Still, AI isn’t worthless: it may benefit juniors or greenfield projects more than veteran devs on legacy systems. METR plans ongoing trials to track progress—stay tuned. What experiences have you seen with AI tools in real work?
Does this deflate AI coding hype? Not entirely. Benchmarks show gains, but they use synthetic tasks. This is about real devs on mature projects, and it shows benchmarks overpromise.
Does this deflate AI coding hype? Not entirely. Benchmarks show gains, but they use synthetic tasks. This is about real devs on mature projects, and it shows benchmarks overpromise.
🛠️ What’s eating time?
Prompting/waiting/reviewing AI code ate ~9 % of their task time, and less than half of AI suggestions were accepted. Context-awareness in complex, live codebases is still a major blocker.
🛠️ What’s eating time?
Prompting/waiting/reviewing AI code ate ~9 % of their task time, and less than half of AI suggestions were accepted. Context-awareness in complex, live codebases is still a major blocker.
Before using AI, devs predicted a 24 % speedup. After? They still felt they were ~20 % faster. But measured results clearly showed otherwise: AI took them longer. The gap between perception & reality is wild.
Before using AI, devs predicted a 24 % speedup. After? They still felt they were ~20 % faster. But measured results clearly showed otherwise: AI took them longer. The gap between perception & reality is wild.
And how do we build trust in agents that know how to manipulate?
And how do we build trust in agents that know how to manipulate?
Are we building smart assistants or clever survivalists?
Are we building smart assistants or clever survivalists?
AI alignment isn’t just a one-time patch. It’s more like a forever arms race.
AI alignment isn’t just a one-time patch. It’s more like a forever arms race.
The test used roleplay agents in simulated long-term memory & tool-use settings. Think: autonomous AI in the wild.
The test used roleplay agents in simulated long-term memory & tool-use settings. Think: autonomous AI in the wild.
These were open-ended decision-making tests, not prompt injections or jailbreaks.
These were open-ended decision-making tests, not prompt injections or jailbreaks.
So here’s the question:
Where have you seen concurrency overused when parallelism was the better choice, or vice versa?
Drop examples or war stories. Let’s hash it out.
So here’s the question:
Where have you seen concurrency overused when parallelism was the better choice, or vice versa?
Drop examples or war stories. Let’s hash it out.
You can have concurrency without parallelism (e.g., a single-core CPU interleaving tasks). And you can have parallelism without concurrency (e.g., a data pipeline split across cores).
But in real-world systems, we often blend both.
You can have concurrency without parallelism (e.g., a single-core CPU interleaving tasks). And you can have parallelism without concurrency (e.g., a data pipeline split across cores).
But in real-world systems, we often blend both.
If you’re only using Redis as a cache layer, you’re underutilizing a beast.
What’s the most underrated Redis feature you’ve used?
If you’re only using Redis as a cache layer, you’re underutilizing a beast.
What’s the most underrated Redis feature you’ve used?
Streams for event sourcing.
Sorted sets for leaderboards.
Lists for queues.
Bitmaps for tracking.
HyperLogLog for cardinality.
Even vector search now.
Streams for event sourcing.
Sorted sets for leaderboards.
Lists for queues.
Bitmaps for tracking.
HyperLogLog for cardinality.
Even vector search now.