
Ted Scheckler
2.8K posts

Ted Scheckler
@ImGregPartlow
developer | web3 connoisseur | in the trenches | solana 100x memecoin seeker | $realis




Yesterday @slingoorio included me in the experiment for Skill issue, I have 1% and decided to extend the experiment to a larger audience so from the day the unlock will start I will send 90% of my allocation to ppl who deserve it the most which is skill issue bagworkers. If you have nothing from me I’m sorry SKILL ISSUE 🤷♂️ app.streamflow.finance/contract/solan…











The most important material for building an AI-native company is the record. Conversation, email, Slack, customer signals, and more. But you need an organized knowledge layer because you can't just dump thousands of raw sources into your loop. All records should be summarized, linked to one another, updated as progress is made, and converted into agent-ready data types. That's what @mem_base has automated for personal use with no setup, and we're bringing this to teams. DM me if you want early access.





43 thousand followers, yet one of you must be the sweetest.


1/5 New paper argues we’ve been looking at LLM post-training wrong. It’s not mainly about SFT vs RL vs distillation objectives. It’s about which states you apply supervision on. Fresh work by Dong Nie (May 2026) → arxiv.org/abs/2605.22731



windows RDP is an impossible task. it says my password is wrong but its definitely not lol. why is this so hard please





College CS enrollment is declining Charts of the Week: a16z.news/p/charts-of-th…






Once upon a time there was an Lead AI Developer who's AI was not getting impressive benchmark results. That evening, all of his neighbors came around to commiserate. They said, "We are so sorry to hear that deep learning is hitting a wall. This is most unfortunate." The Lead Developer said, "Maybe." The next day the LLM came back bringing seven massive benchmark scores and even got 90% on the LSAT. I the evening everybody came back and said, "Oh, isn’t that lucky. What a great turn of events. You now are really close to AGI!" The Lead AI Developer again said, "Maybe." The following day his son tried to train the next successor model, and while training it, he found that 10x'ing pre-training compute wasn't giving results anymore. The neighbors then said, "Oh dear, that’s too bad. Deep learning is hitting a wall." and the Lead AI Developer responded, “Maybe.” The day after, the Lead AI Developer announced they'd achieved breakthrough results by adding inference-time compute, RL scaling, and tool use. The neighbors came around and said, "Oh wow, AGI is soon!" The Lead AI Developer said, "Maybe."








