Experimenting in AI Founding DevRel @LiteLLM
Vancouver, Canada
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- Following 838
- Followers 8,477
- Likes 5,852
Opus 5.5 is def very good with animations!
Gemini 3.8 Flash TTS + Opus 5.5 = Animated explainers!
Grandpa explains how rotary phones worked back in the day.
Prompted Opus 5.5 to explain rotary phones as a conversation, using Gemini 3.8 Flash TTS via @LiteLLM gateway.
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Gemini 3.8 Flash TTS + Opus 5.5 = Animated explainers!
Grandpa explains how rotary phones worked back in the day.
Prompted Opus 5.5 to explain rotary phones as a conversation, using Gemini 3.8 Flash TTS via @LiteLLM gateway.
Introducing Gemini 3.8 Flash and Flash-Lite TTS, our new SOTA text to speech model with:
- a new voice design experience
- 2,000+ production ready voices
- voice replication
- support for 100 languages
- voice remixing (soon)
- #1 spot on Hume AI's voice benchmarks
and more!!
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Claude Opus 5.5 is INSANE at recreating animations and video edits!
I asked Claude Opus 5.5 to mimic its launch video and it one-shotted this video.
Turned it into a skill here: github.com/misbahsy/claude-h…
Used it for the announcement of Day 0 support on @LiteLLM
Introducing Claude Opus 5.5, the first model in our new Claude 5.5 family.
It performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5.
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A simple illustrative guide for Devs to build with Jev @typesafeai
(agent-friendly)
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Jev is a super fast video editor!
Edited this entire video in less than a minute, and here's how:
First, I transcribed raw vid locally with word timestamps, cut it into 16 beats, then asked Jev these seven questions about every beat:
does this line need a visual at all?
which card template? (18 to pick from, premade)
which text effect?
which transition into it?
how hard do we punch in on the face?
which sound effect?
which word gets emphasised?
Plus five about the video as a whole. Style, colour, caption treatment, energy, progress bar.
117 questions answered by jev < 1 s ~ $0.0017
Using @typesafeai via @LiteLLM
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Inspired by the work of @jackcheng
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Doc-OCR router using Jev @typesafeai
A Jev-powered router that looks at a PDF page by page, decides which pages actually need OCR, extracts the rest locally.
Result: save cost on # OCR pages + speed
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Measured on 19 documents / 155 pages, mistral-ocr-latest through a @LiteLLM gateway:
OCR-only vs Jev-router
155 pages billed down to → 87
19 API requests down to → 13
35.6s → 20.7s (1.72x speed)
$0.3100 → $0.1783 (1.74x savings)
Repo: github.com/misbahsy/doc-rout…
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TIL - Noul
If you are gonna be using Jev, you might hear this too.
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
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41 common ai slop patterns from ai writing
remove it with this one skill.
@LiteLLM for multiple reviewers
anti-ai-slop: a 4 staged skill to remove any AI slop from your codex/cc writing.
catches 41 different slop patterns:
• ~120 ai words, ~100 phrases
• em dashes, emoji bullets, title case headings
• watermarks, negative parallelism, colon reveals, throat-clearing openers
4 gates:
1. sanitize invisible chars
2. remove common ai words/chars
3. an agent reviews original vs rewrite, loops back for failed reviews
4. optional: a parallel agent uses a different model to generate additional review + score
Works with any of your AI agents.
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A gift for your agents...
(in case if you missed)
github.com/misbahsy/anti-ai-…
anti-ai-slop: a 4 staged skill to remove any AI slop from your codex/cc writing.
catches 41 different slop patterns:
• ~120 ai words, ~100 phrases
• em dashes, emoji bullets, title case headings
• watermarks, negative parallelism, colon reveals, throat-clearing openers
4 gates:
1. sanitize invisible chars
2. remove common ai words/chars
3. an agent reviews original vs rewrite, loops back for failed reviews
4. optional: a parallel agent uses a different model to generate additional review + score
Works with any of your AI agents.
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anti-ai-slop: a 4 staged skill to remove any AI slop from your codex/cc writing.
catches 41 different slop patterns:
• ~120 ai words, ~100 phrases
• em dashes, emoji bullets, title case headings
• watermarks, negative parallelism, colon reveals, throat-clearing openers
4 gates:
1. sanitize invisible chars
2. remove common ai words/chars
3. an agent reviews original vs rewrite, loops back for failed reviews
4. optional: a parallel agent uses a different model to generate additional review + score
Works with any of your AI agents.
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Phew… Finally Gemini and XAI can catch up now
I agree with Dario that we need to pace the frontier. This has been a primary topic of discussions we've had at OpenAI in recent weeks.
Committing to having independent evaluators with employee-like access is a great idea, and we will do the same. We'll have more to share soon.
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For the sake of flykind, I trained a fly brain to find its way out of a room through open doors and windows.
It scans the room, detects available exits, navigates around obstacles, and escapes.
No more buzzing into walls and closed windows. Now I just need to pass the training to the rest of the fly community.
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