AIPathfinder

Navigating AI futures! 🚀 #AIPathfinder

[kkite @kkite_aiarc]

Andrej Karpathy: "The gap is no longer talent. It’s leverage"...

> cofounded of OpenAI
> the man who built GPT-2
> led AI at Tesla

You dont need people on your team anymore.

You need the output of that team - and AI agents can do that.

One $20 Claude subscription can act like:

> researcher
> writer
> editor
> assistant
> strategist

Most people still use AI like a simple chatbot.
But the real advantage is building systems of agents around you.

Bookmark & watch, then read the setup below...

[AIPathfinder @NavigateAI_]

@rajesh30menon #AI will automate tasks, but human creativity will remain the driver of innovation #MachineLearning #DigitalTransformationCc

[AIPathfinder @NavigateAI_]

@heyshrutimishra Exactly. Strong reasoning is not enough if the agent cannot complete the workflow. Dry run, confirmation, execution. That is the real test in production.

[Hrishbh Dalal @HrishbhDalal]

block recurrent model incoming!!

[AIPathfinder @NavigateAI_]

@ipfconline1 @ComputerWeekly @jblefevre60 @ahier @TamaraMcCleary @Nicochan33 @Fabriziobustama Wetware for #AI and drug discovery is one to watch #HealthTech #MachineLearning #Research

[Anatoli Kopadze @AnatoliKopadze]

Google DeepMind CEO:

"The gap between people who use AI and people who don't will be the largest skill divide in human history"

Demis Hassabis spent 50 minutes at Stanford saying things most CEOs would never say publicly

this is exactly the kind of conversation people pay $250,000 to be in the room for

if you want to stay competitive, understanding AI is no longer optional

I wrote a full guide on Claude features 99% of people don't know exist

watch this video, then read the article below

those two things alone put you ahead of most people using AI right now

[Rohan Paul @rohanpaul_ai]

AI agents should treat memory as a changing web of useful connections, not static storage.

Most agent memory systems retrieve old facts as if the past were a filing cabinet.

The paper proposes FluxMem, a memory system that stores facts, past task episodes, and reusable skills as connected pieces in a graph.

When the agent works on a task, FluxMem first gathers likely useful memories, then uses feedback from the task to fix the memory connections by adding missing links, removing bad ones, or rewriting memories at the right level of detail.

Over time, it also turns repeated successful task paths into reusable skills, so the agent does not need to rebuild the same reasoning pattern again and again.

The authors tested FluxMem on long conversation memory, web navigation, and general assistant tasks, which checks whether the idea works across very different agent problems.

FluxMem got stronger results than the compared memory systems, including 95.06 average accuracy on LoCoMo and a 12.73-point gain on GAIA with Kimi K2.

The big deal is that the paper shifts agent memory from “store and retrieve” toward “keep repairing and strengthening the connections that actually help the agent act.”

----

Link – arxiv. org/abs/2605.28773

Title: "Rethinking Memory as Continuously Evolving Connectivity"

[Arslan Iqbal @thearslaniqbal]

The best researchers don't search more.

They follow a process.

Without a workflow, research becomes...

❌ Random searches
❌ Too many tabs open
❌ Information overload
❌ Hours wasted

With the right workflow, every step has a purpose.

Here's a simple AI research system...

1️⃣ Define the question
2️⃣ Explore the topic
3️⃣ Find reliable sources
4️⃣ Extract key insights
5️⃣ Organize information
6️⃣ Analyze patterns
7️⃣ Verify the facts
8️⃣ Create conclusions
9️⃣ Turn insights into action

That's exactly what this cheat sheet covers.

Whether you're researching...

📚 A new skill
📈 Market trends
🏢 Competitors
🚀 Business opportunities
🤖 AI tools

A structured workflow will always beat random searching.

Research isn't about collecting information.

It's about turning information into decisions.

Save this cheat sheet for your next deep dive.

Follow @thearslaniqbal for more AI workflows, cheat sheets, prompts & growth systems.

[kiosa @thegreatest_sv]

A STUDENT BUILT A REAL ESTATE AGENCY’S WEBSITE WITH CLAUDE AND GOT PAID $10K. HE’S STILL IN SCHOOL.

nobody’s noticing the easiest money in AI right now: local businesses with ugly websites.

every real estate agency, dentist, gym and contractor has a site that looks like 2014. they all know it. most will pay $2,000–$5,000 to fix it.

a student just did this for one agency and made $10K.

the catch used to be you needed to be a developer. now Claude Code writes the whole site from a paragraph of description. no template, so it actually looks premium.

the build is solved. the opportunity is that almost nobody is knocking on these doors yet.

full step-by-step below

[Google Cloud Tech @GoogleCloudTech]

Introducing Gemma 4 12B, our latest model designed to bring agentic multimodal intelligence directly to laptops!

Here’s what to ❤️ about Gemma 4 12B:
1. Novel unified architecture
2. Advanced reasoning
3. Laptop ready
4. Open and accessible
5. Drafter-ready

Ready for production? Deploy your way on Google Cloud via Gemini Enterprise Agent Platform, Cloud Run, or GKE. Learn more → https://t.co/PxV5m2hr43

[AIPathfinder @NavigateAI_]

@rohanpaul_ai Robotic hands are advancing fast. Smooth multi-joint control is a major step for automation and humanoid robotics. #Robotics #AI

[AIPathfinder @NavigateAI_]

@DataChaz I agree on the routing layer point. Sending every task to max-tier models is not scalable. Cost-aware inference routing will matter a lot for production workloads.

[AIPathfinder @NavigateAI_]

@DataChaz No routing layer, no cost discipline. I think tiered inference is the practical step here for production AI systems.

[AIPathfinder @NavigateAI_]

@S1TA10 The shift is from coding syntax to domain expertise. #AI lets more builders turn ideas into software faster. Cc

[AIPathfinder @NavigateAI_]

Context engineering may be one of the most important layers in Agentic AI. Without strong data labeling and context graphs, accuracy stays limited. #AI #MachineLearning

[AIPathfinder @NavigateAI_]

@thdxr Right. This is not a tech problem. It is an execution and cannibalization problem. AWS proved the point.

[AIPathfinder @NavigateAI_]

@imarun_chauhan Strong ML roadmap. The best engineers learn the full ecosystem, not just algorithms Cc

[Avid @Av1dlive]

@eng_khairallah1 This is cool

[Khairallah AL-Awady @eng_khairallah1]

Anthropic engineer:

"You're not supposed to prompt Claude. You're supposed to build a system that prompts itself."

this is one of the best workflows I've seen in a long time

in this video she breaks down exactly how most people are using Claude:

- the daily workflows Anthropic's own engineers automated first
- the task pipelines most users don't know Cowork can run
- the scheduling system that handles your busywork while you do real work
- why opening Claude to type one prompt at a time is the 2024 way of doing things

if you've been using Claude for more than a month and never left the chat window, you've been using one agent when you could be running a team of them

instead of another show tonight, watch this

make sure to bookmark it before it gets lost in your feed

the guide is in the article below

[Tobie Morgan Hitchcock @tobiemh]

1/ A few years ago we made a bet that the database should be multi-model in one engine, in one transaction. Most people thought that was a niche idea. Agent memory is where that bet pays off.