Hottest thing in inference right now: “we serve model X at Y tok/s.” Yeah cool bud, at what concurrency, on how many GPUs, and at what cost per million tokens? Y tok/s != we are a good provider

Setup Boundless inference with one command from the terminal

RL + OS models is the enterprise stack of the future

Live and scaling up on @vercel AI gateway this past week. Serving the most popular OS models competitively amongst the best AI infra providers in the world.

Boundless is now live on the @vercel AI Gateway. Starting with: → DeepSeek V4.1 Flash: $0.20 in / $1.00 out → GLM 5.3 Flash: $0.12 in / $0.40 out More to come. Get access below.

Christmas for any company with Agentic RL needs

A PM who can turn user pain points into evals might soon be worth more than a top 1% ML researcher.

I’ve published the initial work here: github.com/JacobEverly/long-… The repository includes: - The supervisor and evaluation harness - Results from four model deployments across 18 sealed tasks - Completion-versus-cost comparisons - Roughly 172 hours of redacted agent trajectories - External-verification outcomes - Reproducible analysis and visualizations

AGI at home in <6 months

This reflects how I think these models are best used today: an almost infinite sea of interns that can take on grunt work, as long as you give them the right direction.

Is instinct just @NousResearch with a different GTM motion and PMs?

We are working with teams where inference is core to the product. If that’s you, reach out. We built an inference platform, but we’re not a neo-cloud selling cheaper tokens. We work hands-on with teams across product and engineering to integrate, tune, and operate models in production. Resulting in better performance and reduced costs.

I don't know about others, but Fable 5.1 was the first time I didn't switch to @AnthropicAI from @OpenAI for knowledge work. The desktop apps have crossed a real stickiness threshold. A model advantage probably needs to be sustained for weeks now to cause a switch for many

We’ve been building Boundless AI, the inference partner for AI-native startups. Boundless helps teams run open-weight models tuned to their product, for better economics on frontier intelligence. boundless.network

Now serving GLM 5.3 Flash at @BoundlessHQ. We’ve found it sits on the Pareto frontier for agentic coding and everyday knowledge work. We’re onboarding more users to our closed beta every day. If you’re building with AI but haven’t found a neo-cloud that works for you, reach out

Regret the tone of my post on data centers yesterday. What I should have said: There were reasonable concerns about data centers 18ish months ago: water, taxes, jobs, electricity prices, the environment and what they would do to small towns. Well-structured data center projects have largely addressed these concerns today and we should be celebrating this. On balance, data centers are awesome for America in every way. On water: U.S. data centers use a fraction of what golf courses use. A lot of the numbers from 18 months ago were off by over 1000x. Newer data centers use closed-loop systems or recycled water. Should be required by every town approving a data center project. On taxes: looking only at sales-tax exemptions, as Ronan Farrow did, is the wrong way to evaluate this. Data centers pay significant property taxes. Loudoun County, which is the wealthiest county in America, now collects on the order of $1 billion a year from data centers. In Quincy, WA, data centers are more than half the property-tax roll. Over time, property taxes can go to zero while government spending increases in these towns. On jobs: this has been unambiguously awesome for blue collar Americans. Demand for electricians, plumbers, welders, HVAC techs, and contractors has gone vertical, and it is not a one-time construction job. These buildings get upgraded and expanded over time. That is why the building trades are fighting for them, and why some unions are now treating opposition to data centers as a reason not to endorse politicians. On power: the original fear was that households would pay for the incremental electricity demand in the form of higher prices. That is why the ratepayer-protection deals and the new large-load tariffs exist. The right structure is: the data center brings or pays for new generation and signs a contract long enough that existing customers are protected. Where that is happening, utilities are cutting or freezing residential rates and saying so on the record. Where it is not, people are right to object. Electricity prices are going down *today* in a number of large states because of data centers. 
On the environment: data centers overwhelming use natural gas today, which is the cleanest power source outside of nuclear, solar and wind. And the companies that are building the data centers are committed to carbon neutrality such that an equivalent amount of solar will likely be built. Maybe more importantly, the data centers need batteries to function effectively and these batteries can also sell energy back into the grid (which recently prevented blackouts in Texas). Over time, data centers will run on solar plus batteries. On the towns: Poverty in Quincy, WA fell from 29% to 6%. Data center taxes paid for a new high school, a hospital, a library, police and fire stations. This is happening in many left for dead former mill and farm towns that had no other bidder for the land. Data centers are actually reindustrializing parts of America and creating the kind of working-class jobs both parties have spent decades claiming to support. That should not be a partisan issue. Data centers can and should be awesome for America and they increasingly, overwhelmingly are. Supporting the outsourcing of data centers to China will likely age just as well as support for the outsourcing of high quality, blue collar manufacturing jobs to China has aged. When the facts change, I change my mind. I hope that reasonable people who had good faith reasons to oppose data centers at least consider updating their beliefs given the change in the facts over the last 18 months. This really matters for America. I will say I also think the idea of making data centers beautiful is a good one that has yet to be implemented. Data centers should be just as beautiful as Grand Central Station. We can learn a lot from the railroad buildout. Neoclassical revival ftw. Might write up open-weight AI tomorrow as this is equally essential to America.

How long until model companies start selling space in their reward functions, letting brands pay to be recommended more often?

Post-training will be one of the most important areas for PMs to understand over the next few years and one of the most powerful ways to meet user needs.

Paris Hilton in, Jensen Huang out 😭

Glad to see agents have the same decision making process as the lads on a Friday night