JJ Maxwell

Q4 2026 Request for Startups

I've had a more downtime recently, which has led me thinking about companies to start. These are things I think should exist and will have value in our AI future, in no particular order.

- Charter: Instant Building Approvals and Inspections. AI will eat lots of architecture and engineering. The next step is software for planning departments to auto approve plans and inspect with drones/cameras remotely.
- Retort: On Demand Molecule Foundry. Automate as much of the molecule creation steps as possible, and let Claude hit an API to get new molecules made.
- Drawdown: Robotic Formulation Foundry: Similar, but lots of everyday items like paints, adhesives, lotions and foods as just a ingredient list that need to be mixed and tested. Do that via API call.
- Switchboard: Open Home Control. Home Control software (Crestron, Control4) are expensive and suck. Home Automation means you can pair 3rd party hardware and have it play nicely in one setup that can "do it all".
- Tender: Second Home Care. Similarly, I really see the need for a dedicated Second Home Care business for resort towns. Its property management mixed with better automation.
- The Settings: Custom Fine Jewelry. Apply SuitSupply's strategy to Jewelry. You can "talk to CAD" to design things pretty soon, so people customize things and cast them and ship quickly. Might need a real storefront but that could be fun.
- The Short List: Public Test Kitchen. Combining a kitchen goods store with a real "Test kitchen" and then sell the results to AI labs. Could be a media business as well. "Which Pan is best" can be really answered with enough tests.

Published with more details on each here: jjmaxwell4.com/ideas/index.ht…

How to make more money on consumer subscriptions with Crew Plans™

• I noticed something really smart my local gym started doing recently to improve retention.
• It's a bit like a family plan, but they market it to friends as well.
• The gist is that for every member that joins a "crew" (my term), the price decreases by some set amount. AKA a membership is $300/month, but if 2 of you join, each membership is $280/month. And it keeps decreasing the more people you have tied to the crew. While decreasing the overall price, this does 3 things:
• Existing crew members cancel less, because leaving causes their friends' prices to go up.
• The existing crew has a meaningful ongoing incentive to refer friends. Rather than a one-time thing, this is a $20/month benefit for as long as you're a member. I'd expect a 5-10% increase in new members via referrals.
• When someone drops off a membership, the existing crew has an incentive to find a replacement. This effectively directly reduces churn and can be modelled as a "Chance a departing group member is replaced," which I think would be somewhere in the 10%-20% range.
• The tradeoff is you are giving out a discount, so there is a direct upfront cost.
• If you model this out for a system like $GRAB Unlimited, which charges about $4/month, you get the following (see images, or check out the spreadsheet and copy it to play with the inputs yourself: docs.google.com/spreadsheets/d…):
• Long run: about +13% monthly contribution once crews reach full adoption.
• Short run: cumulative contribution is down for nearly four years, and payback is around month 24. The discount costs about 19% of contribution right away, while the extra members build up slowly.
• What pays for it: lower churn alone doesn't cover the discount. Replacements and referrals tip it positive.
• You could couple the launch of a program like this with a slight price increase to help speed up the turnaround time.
• This is a different type of referral program, and it's decidedly different product-wise IMO from a family plan. Family plans are about consolidating billing and ideally also getting a discount.
• This is about trying to incentivize your existing users to become your sales force, replacing churned users and recruiting new ones.
• I think this could relatively meaningfully change the shape and performance of many subscription plans, especially if they are high-margin, high-churn products that people use together.
• Phone carriers have done this with family plans forever, but it hasn't really expanded beyond that. Also there's a meaningful marketing difference between family plans and this idea. I think marketing these as Crew Plans would help meaningfully increase adoption.

Costs in the US Healthcare system

- my Speech Therapist was having me build a device for stretching my jaw out of popsicle sticks. Thought there must be a better way.
- device built for this costs $3000
- found a Chinese one on Alibaba for $60, took 2 weeks to arrive, mandarin instruction manual.

Why is the US version $300? Because most people get insurance to pay and thus the manufacturer wants to obfuscate the price? A bit like ski hills charging $250 for a day pass. The goal is to have you do something else (buy a pass or use insurance)

Hiring Your First Employee - 2026 Version

A companies first hire sets the standard for everyone that comes after it. They can really mean the difference between success and failure. I’ve started a few companies, including Double (W24) and Jetfuel (Acquired by LFTO). Some of these succeeded and some did not.

Here’s what I think you should do to hire your first employee in 2026.

- Traditional interviews are required for social reasons but relatively useless
- First, decide what you want this person to do. It can be as broad as “build the product with me” or “own the backend” or as detailed as “focus on our search infra which is really important”.
- If you put up a job post, you will have many applications but only a few thoughful ones where the person actually put in some effort. A non-AI cover letter for example. I’d put in the job description some sorta “proof of life” test asking the applicant to do something meaningful in addition to applying to the job itself.
- Try and pick out the most thoughtful ones - use AI for this obviously.
- At the same time, try and do some form of outbound. Instead of cold DM-ing people on LI, I’d think through every smart person you know, and send them an email/text asking if they know anyone smart who might be open to working together. You should do this with almost everyone you meet as well. You can lower the stakes by just asking anyone who works in tech for the 3 smartest engineers they know. You can then reach out directly, referencing your friend or just saying I’ve heard great things about you from others. This has much better results compared to cold outbound IMO.
- Now that you have a bit of a funnel growing, identify 5-10 promising candidates and talk to them. This can be quick and is really just a gut check. Ask them what they’ve worked on and why. Drill down into specifics. Keep asking questions and make sure they can explain things and we’re doers on the team not just spectators.
- I think 2/3rd of people should fail this stage. Keep the bar high here to preserve your own time and sanity. “Proof of work” follow ups from candidates are nice but not always sufficient here as they usually signal despiration more than anything.
- Now the goal is to test their “work product” as close as possible. This could be a takehome but I’ve found those hard to calibrate across people as it’s hard to know how long they spent on a task unless you time it. Better is a work trial of 1-4 days. Give them a real task. You will need to setup some infra for this beforehand so most of it isn’t bogged down in permission hell.
- If they don’t want to do a work trial, try and figure out why. You should be flexible here but never remove the work product aspect. If they have a job, see if they will do a weekend. If they have kids and a busy family, ask for 3 hours from 8-11pm a few nights. Some one will need to be online/around while they are working to answer questions and unblock permission stuff.
- The work product is really the interview. If you or your cofounder did that work, what would you think of it? Only lower the bar from this about 10-20%. Were they fast? Was it done with quality? Did they seem to care about it or was this just another interview from them? DId they ask good follow up questions. We’re they mad at themselves they didn’t get more done?
- Optionally here is reference checks. I’ve had a mixed bag on references generally. Usually you get too positive of a response, even if you try and calibrate this out. Backchannel checks are best. If you can find their former founders number, sending them a quick text asking about the person has been the best for me. Ask them to rate their importance to the overall company. Discount this by a decent amount. If you still want to make the hire, follow your gut.
- I never ask someone directly for references as I’m not sure that provides much signal.
- Decide quickly and decisively. If it’s a yes, move with speed into sell mode.
- Figure out what will make a compelling offer (stock, cash, rough amount needed). And then push to close. Call your investors for help closing. Call your friends for help closing. Show up at their home with a gift. Whatever you think “going the extra mile” is, double it. Try and do this all in person or over the phone, not via email which sucks for this.

Do Data Labs have Terminal Value: Part 2

Some people seem to think we’ll have the data business be a $1t/year long term. This is possible, although I think not probable. See the tweet from Ali for a version of this argument: x.com/aliansarinik/s…

Let’s say it is true, and data labs business will and make an analogy to the Oil Industry.

The oil industry is about a ~$4T a year business. But where does the Profit go? Most of it ends up with governements surprisingly, and then producers get about 25%, midstream companies get about 7% and Services companies get about 2% of that!

Data labs are oilfield services in this analogy. They are paid per project from someone else's capex budget, they don't own their output or their workforce, and they sell to a handful of buyers who can bring the work in-house whenever they want. Also, every barrel of oil used needs to be replaced. Once a model learns calculus, you don’t need to teach it calculus again. You might want to teach it something else, so there is more service work to do, but it’s not like a refinery where you can reuse the asset again and again.

Right now they are making a absolute killing. Good for them! They should rake it in. I think they should move to trying to own as much of the verification of “what good is” as possible though over time. I imagine many are trying to do this by providing verification on top of the data they are producing for labs. They should do more of that.