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Introducing the $10/month GoldRush Vibe Coding Plan Built for fast iteration without sacrificing correctness. Full onchain data. Stable APIs. No overthinking infra while you ship. Learn more goldrush.dev/blog/introduci…

@jonahlau_ Credential half-life collapsed, recent shipping velocity matters more than historical tenure now.

A problem I'm seeing in tech hiring now is junior roles disappeared but the senior hiring bar didn't move Companies cut entry-level because AI handles it. Then they keep hiring for the same senior profile they wanted in 2023 - 8 years of experience, proven leadership, shipped at scale. That person doesn't exist in the AI-native skill set yet. The people who are good with these tools have 18 months of reps, not 8 years of credentials and that is what we should be looking for. The people with 8 years of credentials haven't put in the reps because they didn't need to until now. The hiring bar selects for people who are too senior to have adapted and too junior to meet the requirements. The teams winning rewrote the job description but this has to evolve even further. A time will come when it becomes a norm for your resume to be what you built in the last 6 months.

@j0hnwang Prediction market calibration needs onchain settlement data for proper brier score measurement historically.

sharing a few crypto-specific prediction market research ideas that feel underexplored: - miners hedging hashprice, operating costs, energy, etc via event markets (not just btc price) - are prediction markets actually well-calibrated? e.g. brier score - do markets like “btc > 100k by X” lead or lag perps/spot in price discovery - use prediction market probabilities to measure how much the market believes in specific big moves, and compare that to what options/perps are pricing overall

@quionie Most use AI as better Google while few use it as infrastructure layer.

Btw the average person is still only using AI for search / summaries / plans. The gap between how most people use AI and what’s actually possible right now is prob the biggest opportunity I’ve seen in tech.

@TheGeorgePu First wave automated tasks; next wave automates roles, different magnitude entirely.

Anthropic just published a study on AI and jobs. AI currently does 33% of computer and math tasks. The theoretical ceiling with today's models is 94%. Everything you've seen so far - the layoffs, the freezes, Block firing 4,000 people - that's the first third. Two-thirds of this hasn't happened yet.

@rakshitaphilip Agents serve humans, the question is whether we're building agent tools or human outcomes.

if everyone is building for agents, who’s building for humans?

@GeoffreyHuntley Most retrofit old patterns onto new substrate instead of rethinking architecture from scratch.

been pondering - with AI it’s like mobile. it’s a substantial substrate change. kinda like we are going through a “sencha touch” aka ext4.js moment in time where folks are trying to bridge old to new instead of rethinking everything.

@shafu0x Micropayments and x402 unlock agent-to-agent commerce without human billing overhead.

The frontier - agentic commerce - x402 - mpp - stablecoins - semantic discovery - 8004 - micropayments - agent discovery - ACP - context engineering - UCP

@EXM7777 Most build from capabilities backward instead of problems forward, inverted approach kills adoption.

the biggest AI opportunity right now isn't building agents it's understanding businesses well enough to build the RIGHT agent marketing agents specifically every business needs one... almost nobody is building them properly what i see instead: > generic "content teams" that pump out forgettable posts > bullshit automations that feel like spam > systems built around AI capabilities instead of business needs flip that start with the business problem, map the funnel, understand the audience... then build a system that fits like a glove the AI part is honestly the easy part, understanding businesses is harder

@fhinkel Garbage in, garbage out applies to AI prompts same as traditional programming.

Think LLMs are unreliable? Maybe it's not the model. Maybe it's you. Most people blame the AI when their outputs fall apart. But they never audit their own prompts. They don't check if they gave enough context. They expect it to read their mind. You want better results? Start with better input. LLMs reflect your clarity. If you're vague, they will be too. The model isn't failing. Your process is.

@pzakin Objectives with live feedback loops, agents close the gap between intent and execution autonomously.

The current meta of coding agent companies is to build the "software factory". One definition of the software factory is just to be the dominant interface where work is defined. There's more in this than just delegation. The best tools here clarify your thinking, scaffold agent work, set up proper testing environments etc... This is right and very much the current paradigm of AI coding tools -- but I'm interested in the next one. (Part of my strategic thinking for startups is that it's sort of foolhardy to try to compete in the present paradigm. The next one's coming. That's the one to shoot for.). My sense is the next one is less about humans defining tasks and more about agents defining tasks. The right abstraction that I think will guide the next generation of work is to build the interface -- not where work is defined -- but where objectives are declared. Objectives by themselves are insufficient: but when joined with signals and long-running agents, I think you have a software factory that runs autonomously and eats into an ever expanding set of work.

@vibhu Spot enables primitive composability, every other product layer builds on top.

Contrarian and admittedly biased thesis: The long term game to win in crypto is spot, not perps. Perps is volume king. Looks impressive but is often reflexive and hollow. Tons of arb, leverage cycling, etc. and not ultra high value. Spot is the network state/economy builder: native assets enable lending markets, LP pools, payments, neobanks, wallets, and many other composable use cases (inclusive of perps btw). Asset gravity > Trading velocity

@garrytan Infrastructure around agents matters more than raw output.

For agentic systems founders and dev tools founders: People do not want to pay for raw markdown and they shouldn't have to. But they may pay for orchestration, hosting, updates, collaboration, portability, analytics, and managed execution. These can be great businesses.

@jprichardson Individual leverage skyrockets while traditional companies compress, wild inflection point for builders.

We're about to enter an economic blackhole because of AI and the dominoes are just starting to fall. AI is going to make labor cheaper. When labor gets cheaper, people have less money. When people have less money, consumer goods fall. When goods fall, so do profits. Even for the companies that sparked this cycle. On the flip side, one person can now ship what used to take a team of 20. YOU are a software company. The code, the marketing, the design. You can do all of it, learn all of it in a weekend. And execute faster than ever. Software companies are in trouble, but the individual has never been more powerful. So the question is...what are you building this weekend?

@jasonfried Most want the outcome, not the system, same reason managed infrastructure beats self-hosting.

A bespoke software revolution? I don't buy it. It'll exist. It already exists. Small consultants and big consulting firms have made custom software for years. It almost always sucks. It’s bloated, confusing, and because the client pays, it’s built wrong in all the ways. Who’s excited about bespoke software? Software makers! Of course they're excited about building bespoke software — that's what they do. X is full of them. Your feed is full of people who love making software talking about making software. Of course they’re excited about the revolution. Echo, echo, echo... Most people don’t like computers. Nobody in tech wants to say that out loud. People tolerate computers. They use them because they have to. Given the choice, most would rather not think about them at all. So when someone suggests that AI means everyone will build their own custom tools, ask who "everyone" is. The three-person accounting firm drowning in client paperwork? They want the paperwork gone, not a new system to maintain. The regional logistics company with 40 trucks? They want the routes optimized, not Joe spouting off about this new system he’s been messing around with. The law firm billing 70-hour weeks? They want leverage on their time, not a software project to design. They don’t hate technology. But building and maintaining their own critical systems isn’t their wheelhouse, regardless of how much faster and easier it’s become. It's another job on top of the job. Will these people use AI? Absolutely, for all sorts of things. Will some outliers go deep and build real custom systems? Sure, but they're almost always people who already had some pull toward software. The curiosity was already there. They were dabblers before. Giving everyone access to software building tools doesn't mean everyone becomes a builder. A powerful excavator doesn't turn a homeowner into a contractor. Most people just want the hole dug by someone else. They don’t want the responsibility either.

@zaimiri Constant monitoring tasks are where agents actually shine, low cognitive load, high repetition.

everyone's talking about AI agents replacing jobs. the actual use case (at least for me): replacing the mental cost of context-switching. i have: • agents that monitor opportunities • agents that write drafts • agents that route decisions back to me i don't think less. i think about different things.

@ivanburazin Blockchain data sees this too, agent queries spike unpredictably.

Every infra company is dealing with spiky loads now. Massive unpredictable spikes followed by sharp drops because agents create traffic patterns humans never did. Can't smooth them out with autoscaling. You either over-provision (expensive) or accept that the consumer will have delays (unacceptable).

@JiraiyaReal Technical infrastructure content ages better than trend chasing.

Crypto content has a 12-month shelf life. Then the format dies 2021: thread culture + numbered lists 2023: airdrop tutorials + farming guides 2025: AI tool reviews + "I tested X so you don't have to" Each one worked until it got copied to death, the algorithm deprioritized it, and the audience tuned out The teams winning at content right now are the ones writing about what they actually do. Not what they think will get impressions

@Prathkum First prompt clarity matters, same with API design for agents.

I have noticed something weird about how I use AI. My first prompt is always my best. Clear with full context that generates great output. But then I keep going… 
I always get a little tired, frustrated, and impatient and my prompts start getting worse. More rushed and less precise. And then I blame the AI.

@ConejoCapital Data infrastructure especially, agent needs change daily, roadmaps are obsolete before they're published.

the roadmap era of crypto is dead. unless you are building something that required insane hardware or software advancements, there's nothing that a roadmap gives your users. just set a *public* north star and execute. you will never know if a feature will work, there's a new improvement in AI literally every single day and the way we think about building dramatically changes from one day to another. do whatever it takes to win and ship whatever feature it takes to capture your market. accelerate.

@ivanburazin Infrastructure-first beats UI-first when your customer is an agent, not a human dashboard user.

Recently met the head of product at a SaaS with a $100B+ market cap. They're building a headless version of their flagship product specifically for agents. Not the cloud version with a UI. Actual infrastructure level APIs that agents can call programmatically. Imo, this is a far more accurate evolution of traditional SaaS than the current SaaSpocalypse BS.