Replying to @ClaudeBindels @jeffbullas
Can you imagine asking someone to calculate an equation in their head first before confirming it with a calculator?
We are stuck believing that offloading cognitive ability will devalue us. We simply have no idea what challenges humans will face in the future, but I guarantee it will be something that requires humans to develop the skills to overcome them.
Those are the skills we should focus on. And we won't know what those skills are until we find peace in the delegation of our current skillset to AI.
ĐΞΞF retweeted
I'm watching Carney's speech to the European Parliament
This man is the greatest Canadian prime minister in our life time
ĐΞΞF retweeted
Denzel explica por qué usa la IA.
Un pequeña prueba explorando Minimax H3 en ComfyUI con mis nodos y métodos de inpainting.
ĐΞΞF retweeted
At this point I just want models to be faster and cheaper. I have enough intelligence. Please, size doesn't matter any more, I need performance.
ĐΞΞF retweeted
bookmark this:
the best AI prompt is not "act as an expert"
it's "here's the problem, here's what I tried, here's what went wrong, now help me"
context > roleplay
every time
ĐΞΞF retweeted
Introducing Headlong, an open source microharness for persistent agents: self-guided agents that think continuously.
Most agent harnesses are reactive: you send a task, the agent completes it, and then it sits frozen until the next request. Cron jobs and heartbeats wake it up to run a checklist and put it back to sleep.
A Headlong agent is never asleep. It keeps generating thoughts about whatever it decides is interesting, in a self-guided loop inspired by human inner monologue. Your message doesn't start a session. It's one more observation that lands in the agent's thought stream, and the agent decides if and when to reply.
Headlong is built on the idea of persistent agency: continuous inner thought generation between external interactions. The agent sets its own interests and priorities, comes up with its own projects, and sometimes pings you unprompted with progress.
To keep our prototype as simple and small as possible, we implemented Headlong as a microharness: a complete agent harness in under 10K lines of Bash, organized as a handful of small executables. It includes a loop that generates the next thought, shellm (a recursive language model written in Bash), a trajectory stored as a DAG of jsonl files, and context as a projection of that trajectory.
We've been running one Headlong agent internally at Laude for several weeks. The whole team talks to it over Slack and Telegram, and every conversation lands in its single stream of thought. It works in its own fork of Headlong and we've pulled over 50 of its commits into main.
One night, with nobody talking to it, it went back to check whether a recall process it had built was actually wired into its mind, found that it wasn't, diagnosed and fixed the bug, and verified the fix end to end. 48 minutes, no human asked for the fix or was in the loop at any point. Every step is a timestamped line in its log.
Things broke too, and we wrote those up. Background thinking costs us $1 to $2 an hour, our agent stopped its own service three times by accident, and self-delegation died on day one. Details in the post.
One line installs everything and starts an agent. Use a dedicated sandbox and spend-capped API key; it runs real shell commands and thinks around the clock.
Headlong is research software, be careful!
curl -fsSL headlong.ai/install.sh | bash
Launch post: laude.org/updates/headlong-a…
Repo: github.com/laude-institute/h…
Headlong is a @LaudeInstitute / MIT collaboration.
HyperFrames -> Video Agent
Our HTML motion graphics framework, now inside HeyGen
Prompt what you want, our agent builds the entire video
Avatar, graphics, captions, music
Infinitely customizable, just ask
Comment + RT "prompt" for a free month of HeyGen (must follow)
ĐΞΞF retweeted
I had early access to Gemini 3.6 Flash and found it to be very fast, but I did have problems with it. I reported technical issues with the visualisations as well as the usual context loss I always have with Gemini models.
But first though let's make it clear: Flash is designed for speed hence the name Flash. Comparing it to GPT Sol, Meta Spark, Claude Fable, and the other top models is just stupidity. Let's put this into perspective.
Gemini 3.6 Flash launched yesterday. It's Google's efficient workhorse - faster, cheaper, better at coding and knowledge work.
This *isn't* a frontier model, nor is it designed to be. It sits in the mid-tier efficient category. But the efficiency gains over 3.5 Flash are big.
On DeepSWE it jumped from 37% to 49% while cutting cost per task by 52% and output tokens by 65%. On the Artificial Analysis Intelligence Index it held at 50 but got 17% cheaper and runs at 280 tokens/sec.
Like-for-like it's right alongside GPT-5.6 Luna (51) and competitive with Claude Sonnet 5. If it's competing with Sonnet 5 while being faster and cheaper, that's solid for a Flash-class model.
The flat Intelligence Index score while improving speed and cost means Google optimised for deployment rather than benchmarks. For high-volume agentic workflows where you need fast, cheap, reliable performance, that makes sense.
Stats below.
We’re rolling out three new models to make AI agents faster, smarter, and cheaper at scale:
🔵 Gemini 3.6 Flash: It uses fewer tokens than 3.5 Flash to deliver higher quality work at the exact same cost.
🔵 Gemini 3.5 Flash-Lite: A fast, cost-effective option for everyday tasks like processing documents and agentic search.
🔵 Gemini 3.5 Flash Cyber: A cybersecurity model built to find and patch critical software vulnerabilities.
ĐΞΞF retweeted
Replying to @bindureddy
The comparison of that Benchmark Table is Apples vs Oranges.
It has different effort modes (thus different workloads) and does not show error bars on the results. Also the difference of 1 point in the regression part. Additionally, the cost claim is simply incorrect, as 3.6 Flash is less expensive than both 3.5 Flash and Grok/Luna.
Selectively pointing out one poor score and overlooking significant increases in productivity and development speed are not "forms of analysis" but rather headlines searching for "data".
ĐΞΞF retweeted
Fable 5 is INSANE for creating ads
i built an agent that studies your competition and thousands of viral ads, then gives you a full viral blueprint for your brand to copy
just feed it a product photo and a landing page link and competitors names, 3 minutes later you've got a proven creative playbook for your ads, here's how it works:
- scans your brand's own website (copy, offers, structure, CTAs)
- scans competitor websites (you list them, or Claude finds likely ones for you)
- pulls live ad data straight from Meta Ad Library + TikTok via spytools
- extracts proven hooks, scripts, and visual/creative patterns from every source
- synthesizes everything into one swipe-file library
- output is a ready-to-paste doc, drop it into Claude and generate new ad scripts from proven angles instantly
- runs locally, one command, your own API keys, no video generation step slowing you down
runs 100% local, without $300/mo on spytool subscriptions or agency fees, full control, and API cost only
RT + reply w/ "AGENT" and i'll send it to you so you can use it for your brand (must follow so i can DM)
ĐΞΞF retweeted
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ĐΞΞF retweeted
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ĐΞΞF retweeted
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Retweet
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for a bonus airdrop, rt + drop your SOL address
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you have 24 hours to fill out form.
for a bonus airdrop, rt + drop your SOL address
ĐΞΞF retweeted
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ĐΞΞF retweeted
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Giving away 10 FREE SOL to 3 random followers! 💰
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