@argofowl I’ve seen people say this about other models in the past but could never really tell if it was real or just my imagination. Fable 100% felt dumber this week.
@ScrapingBee Is the Google Maps endpoint down? I’ve been trying to use it for a few hours but keep getting back a 500 response. The endpoint isn’t on your status page.
Max Verstappen says a F1 car has the speed of a F3 car and I agree with him.
Max also said: "I don't want to sit here and complain again because someone will probably shoot me outside the door."
Belgian Grand Prix.
Spa has a reputation as one of the greatest race tracks on the planet, the track's most iconic corner, the flat-out swerves known as Eau Rouge, the most challenging corner of the track, the fast downhill double left-hander known as Pouhon.
Not anymore.
Formula 1 is about speed and at the moment, it is like a tortoise who tries to run for a second, rest for an hour to regain its energy, run again for a second, rest for an hour.... Well, you get the picture.
I am going to make the obvious question because I genuinely would like to know your answer.
How are fable and GPT-5.6 same/different when it comes to development speed?
Meaning if you were going to create a complex system from scratch, start to finish. How much faster/slower would using only 5.6 be compared to using only Fable?
The last two months, every waking hour I'm either:
1) fucking around with AI, or
2) feeling like I'm wasting my time because I'm not fucking around with AI.
Am I the only one?
Been heads-down building with AI agents lately, and this is pretty cool:
Sometimes working with a multi-agent system feels less like “running software” and more like exploring a brain.
Different regions specialize, signals route, memory reinforces patterns, and if you don’t maintain the system state… coherence degrades.
That insight is why we built Brain Pulse into our CLM stack.
What Brain Pulse does:
• periodically snapshots decisions
• persists current guardrails
• records blockers + risk posture
• stores next executable actions
So instead of agents only carrying transient chat context, we give them structured continuity.
We run it in 2 modes:
1) Global pulse
- system-wide reconciliation across agent workspaces
2) Isolated pulse
- project-scoped memory only (strict boundaries)
How to implement (practical version):
1. Create a dedicated pulse agent
2. Define strict scope policy (paths + agent prefixes)
3. Trigger hourly + or manually by asking openclaw to trigger it
4. Persist to durable memory/state files
5. Surface pulse count + pulse events in your dashboard
I expected this to be “nice to have.”
It turned out to be core reliability infrastructure.
If you’re orchestrating multiple agents for whatever reason you probably want something like this earlier than you think.
#AI #AgenticSystems #OpenClaw #Software