“It is never too late to do good.” But who gets to define what “good” looks like? A conviction or the person who chose to build something different? A second chance should have no ceiling: #SecondChances# #JusticeImpacted# #FromPrisonCellsToPhD#

full interview with @koolkrypto223 1:31 the $DRV bullcase 3:46 Derive can still 10x 8:32 why perps guys need options 11:43 the $1.5M ETH call spread 21:13 long AERO short UNI pair trade 23:49 the ETH to $7K bullcase 27:20 Solana is the short leg 30:31 Zcash has no ceiling or floor 35:57 $28M on the $HYPE airdrop 39:35 local top in two weeks ?

how i decide what to buy onchain. it's mostly intuition but here's the filter - find spots with NO ceiling. new mechanisms nobody has done before - ignore new pairs. let the market show you what's getting attention and volume - no sub $10m, i start looking once it's running

Today’s AI is the slowest you'll ever use. In 5 years, it will look like dial-up. Last week, I joined @Vercel’s panel on fast AI with @CompleteSkeptic, founder of @typesafeai. We discussed where AI goes next. We both agreed - people keep underestimating the demand for faster AI. There is no ceiling. 10x, 100x, 1000x. In the 1950s, computing experts guessed a handful of computers could cover a whole country’s needs. For 70 years, we have delivered more compute. And builders have used all of it. Every time. Demand for AI will be no different. Every gain will be spent on bigger problems: -Websites that rebuild their UI for each visitor, the moment they arrive. -Apps you can build as fast as you can describe them. In 10 years, we will look back at today’s AI the way we look at black and white TV. The future will be fast. Thanks for having us, @rauchg, @cramforce and @vercel.

# Decision Points in AI Agent Development # Synchronous vs Asynchronous ⚡ 🎯 The Hook The very first architectural decision for your LLM agent: should it respond synchronously or asynchronously? Get this wrong, and you'll be rebuilding your entire architecture later. Traditional web APIs assumed ~100ms responses. Agents? Their latency spans seconds to tens of minutes. That variance makes sync/async the unavoidable first fork. 📋 Overview Synchronous means the client sends an HTTP request, holds the connection, and receives the result as the response. State lives in-request scope -- no job queues, no checkpoint stores. Asynchronous means the client gets a job ID immediately (HTTP 202 Accepted), and background workers handle the processing. Results arrive via polling, webhooks, SSE, or WebSockets. Execution state is persisted as checkpoints in external stores. 🔍 Decision Points Two variables drive this decision. 1️⃣ **Latency budget** is the primary axis. It comes down to whether LLM p99 latency exceeds client wait tolerance. - Within 5-10s (user-facing) or 30s (API integration) → Synchronous - Exceeds the above, or duration is unpredictable → Asynchronous - Bimodal distribution (short path succeeds, long path fails) → Hybrid 2️⃣ **Reversibility / retry cost** is the secondary axis. - Failure permits full restart → Synchronous is sufficient - Mid-process resume needed; restart is costly → Asynchronous If human approvals occur mid-flow, holding a synchronous connection becomes impractical. Asynchronous becomes mandatory. 💡 Key Details 🟢 **Synchronous shines in simplicity.** Debugging follows stack traces. Testing validates function inputs and outputs. Deployments treat it as stateless HTTP. Fewer moving parts mean easier troubleshooting. It suits text classification, information extraction, basic Q&A, summarization, and structured output -- tasks completing in one LLM call plus 0-2 lightweight tools. 🟡 **Asynchronous shines in durability and scalability.** Processing time has no ceiling. Failed workers resume from the last checkpoint. Human approvals (minutes to days) don't consume workers. Horizontal scaling requires only adding queue workers. But it demands job queues (SQS, Redis Streams, Temporal), checkpoint stores, result stores, and notification mechanisms. Debugging requires distributed tracing across request-to-queue-to-worker-to-result flows. ⚖️ Trade-offs | Dimension | Synchronous | Asynchronous | |---|---|---| | Infrastructure complexity | Low (HTTP only) | High (queues + stores + notifications) | | Debugging | Stack traces | Distributed tracing required | | Fault tolerance | Crash = total loss | Resume from checkpoint | | Scaling | Connection holding is the bottleneck | Add workers horizontally | | Human approval | Impractical | Natural fit | 🛠️ Use Cases 🔵 **Synchronous fits**: Text classification, extraction, simple Q&A, summarization, structured output generation. Tasks that reliably complete in seconds. 🔴 **Asynchronous fits**: Multi-tool chains, cross-SaaS processes, human-approval workflows, tasks exceeding 30 seconds. 🟣 **Hybrid**: An internal async pipeline that auto-switches -- returns synchronous responses within the threshold, returns job IDs when exceeded. Especially effective for bimodal latency distributions. 📌 **Default strategy**: When in doubt, start synchronous. Migrating from sync to async when latency exceeds limits is far safer than the reverse. Sync-to-async migration is straightforward; async-to-sync rollback leaves unnecessary infrastructure behind. #AIAgents# #SoftwareArchitecture#

The beauty of a rooftop garden 🪴 There is something quietly radical about growing something green on top of concrete and steel. A rooftop garden doesn’t just add beauty to a building. It reclaims it. Beyond the aesthetic, the benefits are real. Rooftop gardens regulate building temperature, reduce noise, and improve air quality. But perhaps more importantly, they give city dwellers something increasingly hard to find. A place to breathe. There is also something deeply psychological about being surrounded by plants at height. The elevation creates distance from the noise below, while the greenery grounds you. It is the kind of contradiction that only good design can pull off. A rooftop garden reminds us that no surface is wasted and that nature will find its way into any environment you invite it into. Sometimes the most beautiful room in a building has no ceiling at all. The beauty of a rooftop garden 🪴 There is something quietly radical about growing something green on top of concrete and steel. A rooftop garden doesn’t just add beauty to a building. It reclaims it. Beyond the aesthetic, the benefits are real. Rooftop gardens regulate building temperature, reduce noise, and improve air quality. But perhaps more importantly, they give city dwellers something increasingly hard to find. A place to breathe. There is also something deeply psychological about being surrounded by plants at height. The elevation creates distance from the noise below, while the greenery grounds you. It is the kind of contradiction that only good design can pull off. A rooftop garden reminds us that no surface is wasted and that nature will find its way into any environment you invite it into. Sometimes the most beautiful room in a building has no ceiling at all.

$TSM released earnings today. I was more curious about commentary given recent the market panic. For analyst Q&A rounds: Q: Citi explicitly challenged TSMC on AI financing, HBM, CoWoS, lasers and the risk of overbuilding capacity A: $TSM assessed CSP capex, DC construction conditions, customer financial conditions, and supply of critical components. Management's conclusion is still that "demand exceeds supply". As well as that AI accelerator revenue growth could exceed its previous 50%+ CAGR projection through 2029. This is a more meaningful statement since it addresses some concerns regarding recent selloff. Q: JPM asked if wafer supply could be tighter in 2027 than in 2026 (demand visibility) A: Wei (Chairman/CEO) stated $TSM even sends staff to verify DC construction progress on site. And after assessing all the factors, TSMC believes gap between supply and demand remains substantial. It could not determine whether the extent of the gap given customers continues to increase demand. Q: On pricing power: A: Wei responded that there is "no ceiling on TSMC's profitability" but that profits will not surge dramatically overnight. (Source: NextApple, Taiwanese press) Regarding earnings, very strong: as usual - TSMC record profits of $23.6B (68% Y/Y growth), and revenue jumping to $46.72B, beating expectations. - Q4 Guidance was $52.3-$54.3B revenue off 65-67% gross margins. TLDR: - No signs of any slowdown or collapse as AI demand far exceeds supply for foreseeable future. $TSM is probably the fundamental proxy/canary to how the overall AI semi trade is doing. - On financing concerns and fear of overcapacity showing up in semiconductor demand: $TSM specifically examined the risks investors are concerned about now and assessment still points to unmet demand. During the Q&A session, Wei said AI demand was "very, extremely strong," with absolutely no signs of slowing. Underlying AI semi supply chain growth is healthier than recent market panic suggest.