lama 📿

Attending the @aiDotEngineer summit back in February was a huge boost for @ProbeAgi ( for building @agiObjective ) . The connections, the deep tech conversations, and being at the epicenter of top AI giants and the brightest minds directly shaped our direction and strengthened our resolve to build ProbeAgi and Objective into what they are becoming. Speakers this time specially Jensen Huang (@nvidia) has been amazing. I missed this one live, but I will not miss the next. Agents, swarms, and vast frontiers of technology remain untouched. We are only beginning to see their true power. While we advance toward generative AI, the real question is how institutions and individuals can use it better. That challenge is still a vast and open playground. World is prepping for better usecase for Ai now! Future towards AGI is not just a better chatbot . It is a thinking engine that can reason, learn, and act across any field with human-level or greater skill. It can solve any problem, adapt in real time, and create solutions without being locked into one role. AI answers often match the quality of our questions, but real progress is when they go beyond, reading context, sensing nuance, and choosing the best path forward. That is the doorway to the future of AI and a step toward Artificial General Intelligence. All LLMs now seem to agree on this. Laughs, yes, it was once all about self-promotion, but those days are behind us as the community becomes more aware. Now imagine a hive of leading LLMs @xAI @OpenAI @AnthropicAI and more in constant feedback loops, refining each other’s answers and converging on the optimal result for every challenge. This is @AgiObjective, a collaborative intelligence engine where efficiency and outcomes matter most.

Towards

@yoheinakajima x.com/charmlama/stat…

great article, mostly focused on coding agents but applies elsewhere impo. aligns w a lot of my prior thoughts: - agents need scaffolding, not just smarter models - failures should become durable improvements - tools/functions should be small, reusable, and logged - execution environments matter - tests and deterministic checks are essential - memory should live outside the model - agent systems should improve through use

@mdudas Analyze - learn -> apply -> improve -> expand loop. Said same in 24’, if anyone chases effect & development instead of r&d, it’ll be one way ticket to going obsolete .

entire model of the organization and technology diffusion is changing research lab -> intelligence -> deployment company

openAi : x.com/openai/status/…

@0xmaz_ Goat

1 day later we're at 80k users that's a 400% growth rate if sustained will reach 1 billion users in 8 days

@mert SoLocked

someone give me a good name for a privacy protocol on solana

Urgency is the best predictor of personal success.

Jack’s example can be easily understood as @illscience posted more about it .. ( more related to 4th diagram ) x.com/illscience/sta…

Since then, KBs / context graphs became public consensus once @karpathy pointed them toward personal knowledge bases. [ x.com/karpathy/statu… ] But it is only one direction. That direction matters: inward, archival, content-addressed. Context graphs unlock more when they stop being treated as retrieval structures. Temporal salience matters as node activation shifts with intent and recency. Recursion compounds - personal graphs become nodes inside team and organizational graphs. It’s a crime that they’re not being treated as what they are : orientation structures. It’s 4D & not a 2D structure. ( Connections - retrievals - search - paths ). Leading to “Substrate” is the right word, @jack’s example in comment. A clay.

Re , Director of GoogeCloud Ai : x.com/addyosmani/sta…

agentic era doesn’t mean agents are the whole system 🗣️ Saying “we built agents” & pushing it a car is 🦼psychosis mostly. intelligence is a system property, not a component label. System = [ Model(s) + Agent(s) + Tool(s) + Orchestration(s) ] + Harness + Foundation Layer(s) focus on 1 thing again = golden ticket to being obsolete in 6 months. by no means have we fully explored agents… but exploring agents requires exploring systems too. while wondering how claude keeps on dropping updates, all hell will break loose the day we actually start checking google ai dev resources

@nikitabier Help me sensei, i cant find doors rn 😂 shadow banned

The value of an X account can be measured by what doors it opens for you in real life.

@0xmaz_ Yo.

Just me and codex with 200x usage

what if everything goes right

@jason_haugh Being frontend of anything, isn’t that one of the major interaction interface we’re moving towards

@CharmLama The hardware advantage matters when local models can carry the workload. Right now they can't. Until that changes, Siri's the front-end for someone else's model. That's what people are reacting to.

Apple winning agentic battle with hardware Anyone looking down on siri, seriously have no depth of agents or Ai

@JasonrShuman I believe your market research is lagging ^^ It’s a tad bit cheaper

Cost of robotics training data plummeting Cost to generate 1 hour of robot training data: — Early 2024: $340/hour — Q4 2025: $136/hour — March 2026: $118/hour That’s a 65% cost drop in 24 months.

@boldleonidas @krakenpro LMFAO

"The world belongs to the fast. The people who iterate. The people who adjust."

Most of the crypto industry is dead and never coming back. Eventually people will realize it.

Some earlier, some later, but finding out is the best part as it helps a lot x.com/cursor_ai/stat…

orchestrator | agents | task division [ non parallel] orchestrator reviews : you save time. For : Video frames | Research | Code | Doc management | Writing | World’s your playground Parallel tasks : time waste. I believe it’s time people start doing it at scale.