Why is Claude so bad. It used to be good but the current models are just whack. The useage limits are insane and it keeps missing the mark. Clear guidelines, instructions and it still misses the fundamentals, then ends with one more thing. This is using Opus 5 on high
It’s like the narcissistic relationship you’re forced into and can’t leave…
What are your experiences????
Rant over
It’s been a few weeks and I’m tired and hitting a brick wall.
I’m trying to add Microsoft certifications for exams I’ve passed. I’ve tried Microsoft edge, chrome even tried incognito, safari, cleared the cache, logged out and back in. I’ve tried everything I can think of.
Each time I try and share or add a licence or certificate, I fill in the details and hit save.
Then the dreaded message.
🛑 Something went wrong. Please try again.
LinkedIn is this a known bug. Do you have a suggestion of solution. I’m tired now.
Thanks
I’ve been running Opus 5 against Fable 5 and GPT-4o in production workflows (commercial strategy, data analysis, content refinement). Here’s what I’m seeing:
The pattern: Opus 5 delivers high-confidence first outputs that require heavy iteration. On average, 2-3 follow-up prompts to close gaps (missed context, incomplete analysis, logic jumps). Each iteration costs credits.
Specific examples:
• Complex multi-step analysis: Opus 5 flags confidence at 90%+, then “Oh, I missed X detail” on follow-up
• Long-context documents: Skips sections, requires re-prompting with explicit “don’t miss” guidance
• Structured output: JSON formatting correct, but data completeness varies; Fable 5 catches edge cases Opus 5 misses
Cost impact: On a 10-task batch, Opus 5 runs 25-30 total calls (first pass + corrections). Fable 5 averages 12-15. At scale, that’s meaningful budget drift.
The ask: Would love benchmarks on first-pass accuracy for Opus 5 vs. predecessors. The capability is there, but the confidence calibration feels off users (especially in B2B/commercial work) are bearing the cost of iteration.
What’s working: Fable 5 is more conservative and nails it first time. GPT-4o’s pricing model makes the iteration tax visible, so users accept it. Opus 5 feels like it’s hiding the cost.
What are you experiencing?
I’ve been running Opus 5 against Fable 5 and GPT-4o in production workflows (commercial strategy, data analysis, content refinement). Here’s what I’m seeing:
The pattern: Opus 5 delivers high-confidence first outputs that require heavy iteration. On average, 2-3 follow-up prompts to close gaps (missed context, incomplete analysis, logic jumps). Each iteration costs credits.
Specific examples:
• Complex multi-step analysis: Opus 5 flags confidence at 90%+, then “Oh, I missed X detail” on follow-up
• Long-context documents: Skips sections, requires re-prompting with explicit “don’t miss” guidance
• Structured output: JSON formatting correct, but data completeness varies; Fable 5 catches edge cases Opus 5 misses
Cost impact: On a 10-task batch, Opus 5 runs 25-30 total calls (first pass + corrections). Fable 5 averages 12-15. At scale, that’s meaningful budget drift.
The ask: Would love benchmarks on first-pass accuracy for Opus 5 vs. predecessors. The capability is there, but the confidence calibration feels off users (especially in B2B/commercial work) are bearing the cost of iteration.
What’s working: Fable 5 is more conservative and nails it first time. GPT-4o’s pricing model makes the iteration tax visible, so users accept it. Opus 5 feels like it’s hiding the cost.
What are you experiencing?
Is anyone here using nourish care software and what are your thoughts?
Something really weird is going on and feel like Apple are defecting the iPhone 14 models. Ever since I updated, my phone is slow, it freezes, lag is insane and the GPS signal has a mind of its own. If tried a soft reset, hard reset and done a fresh install. Nothing seems to be working and the power seems to be draining really fast.
Anyone else experiencing this?