Technology

The release of a new Terminator sequel has become a familiar ritual: The latest filmmakers acknowledge the greatness of the first two movies, then mumble awkwardly about the other sequels — which are inevitably ignored, because they assure us that this time, they&ve created the sequel we&ve been waiting for.

I can&t tell you whether &Rise of the Machines,& &Salvation& or &Genisys& deserve to be dismissed like this, because I haven&t seen any of them. (I did watch the TV spin-off, &The Sarah Connor Chronicles,& which was pretty good.) But I can say that the latest installment, &Terminator: Dark Fate,& delivers on the promise of a worthy sequel.

It helps, of course, to see the return of some familiar names — not just Arnold Schwarzenegger, but also Linda Hamilton, who takes up the role of Sarah Connor for the first time since &Terminator 2.&And then therefranchise creator James Cameron, who was apparently too busy with his &Avatar& sequels to direct (&Dark Fate& was helmed by &Deadpool& director Tim Miller instead), but who stayed involved as a producer and story writer.

Not that the story is really the selling point: The big emotional moments can feel clumsy and rushed, and some of the dialog is genuinely groan-worthy.

All the script really needs to do, though, is give us a reason for those familiar faces to be back on-screen together, and to convince us that itnot totally pointless to watch another Terminator movie. In that, it succeeds — with a few nods toward the changing technological and political landscape thrown in for good measure.

Arnold Schwarzenegger and Linda Hamilton star in Skydance Productions and Paramount Pictures& &TERMINATOR: DARK FATE.&

In the filmopening minutes, we learn that Sarah and John Connorefforts at the end of &Terminator 2: Judgment Day& have succeeded in averting a nuclear apocalypse. However, for reasons that only become clear later, those pesky Terminators keep showing up.

The story proper kicks off in Mexico City, where a young woman named Dani Ramos (played by Natalia Reyes) becomes the latest target of a cyborg assassin. Her pursuer (Gabriel Luna) is an advanced model whose skin and skeleton can function as two separate bodies, and shesaved by not one but two protectors — Sarah Connor, along with a cybernetically enhanced soldier named Grace (Mackenzie Davis), plus the late-film addition of an old-model Terminator (Schwarzenegger, naturally).

There are more revelations as the story unfolds, but one of the best things about &Dark Fate& is the simplicity of its storytelling. Like its first two predecessors, it doesn&t overcomplicate the formula: Therea killer cyborg, an innocent target and an overmatched guardian; mayhem ensues.

Itin the depiction of that mayhem that &Dark Fate& excels. The film has plenty of CGI (I&d argue too much), but it feels very different from the weightless, super-powered battles that have become the big-screen norm, and even from the balletic killing sprees of the &John Wick& movies.

Instead, the action in &Dark Fate& feels like a throwback, specifically to those Cameron-directed Terminator movies, where a great deal of thought and ingenuity was devoted to coming up with all the different ways that a relentless murder machine might wreak havoc.

Hamilton, by the way, seems completely at home in these scenes. And although Schwarzeneggerperformance was gratifyingly funny and loose, &Dark Fate& is absolutely her film.

Meanwhile, I&m still a little fuzzy on the details of how LunaRev-9 actually works, but it makes for a striking and unsettling visual. The finale, in particular, offers a masterful escalation of jeopardy and destruction, as Rev-9 tears through one environment after another in pursuit of our increasingly desperate heroes — almost convincing you that this time, the Terminator really might be unstoppable.

I don&t want to overstate the case here: &Dark Fate& doesn&t quite replicate the perfect mix of violence, terror and melancholy that made those first two films so memorable. But it can hold its own in a fight.

Why do serial entrepreneurs keep jumping back in? What things might you learn the third, fourth, or fifth time around?

To find out, Extra Crunch Managing Editor Eric Eldon spoke to Drift CEO and founder David Cancel at TechCrunch Disrupt San Francisco. Cancel has spent more than 20 years founding SaaS companies, with exits including Compete (acquired by TNS), Lookery (Acknowledge), Ghostery (Evidon), and Performable (Hubspot.)

In their thirty-minute conversation, they cover everything from finding your first customers, to what heseen change over the last two decades in the industry, to why hewilling to cut a check to employees who want to leave. Rather watch them talk for yourself? We&ve embedded a video of their chat at the end of this article.

To find what people really want, ask for money — any money.

One thing Cancel says helearned over the years: when you&re just getting started, you need to charge for your product right off the bat because you never know how someone really feels about a product until you ask for money.

&If you&re creating a paid-for product, you have to start charging from day one,& he says.

He outlines an experiment he calls the ‘dollar test,& where if someone seems interested in a product before iteven available, he&ll promise them lifetime access if they&ll hand over whateverin their pocket — be it a dollar, ten, twenty, whatever.

&What it teaches the entrepreneur is that most of the people who will tell you that they love this thing will not give you a dollar,& actionable information that can save time, money and stress. The dollar test &shortcuts things; most people will end up spending so much time coming back to you because you keep telling [them] you love it, because you&re a nice person and you don&t want to hurt [their] feelings.&

Cancel also uses this approach after a product launches, using it to gauge which new feature requests customers find most important.

&They&d say ‘I love your product, but it doesn&t do X, Y, or Z. My company is special, we need X, Y, or Z feature.'&

&Letsay they were paying us $5,000 a month. I&d say, ‘itonly going to be $20 more a month, then we&re going to build it for you and you&ll be the first ones to have it.'&

&What would happen, almost every single time, is there would be this awkward pause. They&d say ‘I have to go talk to my manager, I need to go talk to someone, I&ll get right back to you,'& he said, adding &Almost every single time that person continued to be a customer and never asked for that feature again.&

&When itfree to ask for anything,& says David, &people will just keep asking.&

Letting people go isn&t always a bad thing

If someone asks David for a recommendation on an engineer, hewilling to recommend his own employees.

His reasoning is twofold; on one side, it means he knows his teams are made up of people who want to be there; on the other, it means employees know helooking out for them.

&I want people on the team who want to be on the team. If people ask me, ‘hey, do you know a really great engineer who does X, Y, Z?'& I say ‘Eric does, and Ericon my team.& I&m like, you should talk to him. And if Eric wants to go, he should go, because we only want people who actually [want] to be there. Then that person knows that I&m looking out for the best interests of them, for them — and even if they go, we may end up working together again later.&

Similarly, if an employee says they want to leave and start their own company, David says heoften the first to write a check:

&We would attract, in the early days, people who wanted to learn how to start their own company. One of the things I would say, and I still say to everyone: Look, if you come on board, and work with us for some days, if you want to leave at any point and start a company, myself and my co-founder Elias will be the first checks in whatever you want to start, no questions asked.&

&And so we have done that for companies in Boston, companies in San Francisco, companies all over the place. And we continue to do that.&

For finding customers and employees, he turns to LinkedIn

Thanks to recruiter spam and &work anniversary& notifications, LinkedIn tends to be the butt of a lot of jokes — but Cancel says, used right, itstill quite valuable.

&We built a lot of marketing within LinkedIn, which I think is a place that I would advise people to go spend time on now. You can find your buyers, you can find the people that you recruit.&

LabGenius, a London-based startup applying AI and &robotic automation& to protein drug discovery, has raised $10 million in Series A funding.

The round is led by Lux Capital and Obvious Ventures, with participation from Felicis Ventures, Inovia Capital, Air Street Capital and existing investors. Also investing is Recursion Pharmaceuticals& founder and CEO Chris Gibson, as well as Inovia Capital General Partner Patrick Pichette, who was formerly GoogleCFO.

Lux CapitalZavain Dar and Obvious Ventures& Nan Li will join the LabGenius board of directors. Notably, the U.K. companyearly investors include Nathan Benaich, Torsten Reil, EFMatt Clifford, and Philipp Moehring, to name just a few.

&LabGenius is a full-stack protein engineering company: we combine artificial intelligence (AI), robotic automation and synthetic biology to evolve next-generation protein therapeutics,& founder and CEO Dr. James Field tells me.

&My central thesis, the thing thatreally the driving force behind the company, is the conviction that we&re entering an age in which humans will no longer be the sole agents of innovation. Instead, new knowledge, technologies and sophisticated real-world products will be invented by smart robotic platforms called empirical computation engines. An empirical computation engine is an artificial system capable of recursively and intelligently searching a solution space.&

LabGenius& flagship technology is called &EVA,& which Field describes as a &machine learning-driven, robotic platform& capable of evolving new proteins. &As a smart robotic platform, EVA is capable of designing, conducting and critically learning from its own experiments,& he says.

The goal: to discover and develop new protein therapeutics that are currently hard for humans alone to find.

&For decades, scientists, engineers and technologists have dreamt of building ‘robot scientists& capable of autonomously discovering new knowledge, technologies and sophisticated real-world products,& explains Field.

&For protein engineers, that dream has now entered the realm of possibility. The rapid pace of technological development across the fields of synthetic biology, robotic automation and ML has given us access to all the essential ingredients required to create a smart robotic platform capable of intelligently discovering novel therapeutic proteins.&

To that end, Field frames the development of EVA as a &long-term, ambitious undertaking& that he says will enable the startup to address previously unsolvable protein engineering challenges and in doing so, develop urgently needed therapeutics.

&My ultimate goal for LabGenius is to establish a fully integrated biopharmaceutical company powered by the worldmost advanced protein engineering platform,& he adds. &Quite honestly, this is a gargantuan undertaking and, while we&ve already established one of the worldmost technically sophisticated protein engineering operations, we&re only just scratching the surface of whatpossible.&

More broadly, there is a tension that many deep tech companies face, which is determining how best to develop technology thattightly aligned to real-world commercial needs (before running out of capital!). &For LabGenius, we&ve achieved this in a highly intentional way by undertaking a series of commercial projects of increasing complexity from the companyearliest days,& Field says.

One on-going project is with Tillotts Pharma AG to identify and develop new drug candidates for the treatment of inflammatory bowel disease (IBD).

&Our business model is pretty simple,& says the LabGenius founder. &We use EVA to discover and characterise new drug molecules and then partner with pharma companies who can take these molecules to market. For example in a typical partner-financed early discovery program, we&ll take a project from concept to early pre-clinical stage. Typical deal structures include a blend of R-D payments, milestones - royalties.&

Meanwhile, LabGenius will use the capital to scale its team, expand the scope of its discovery platform and initiate an &internal asset development program.& The next goal is to evolve novel antibody fragments capable of treating conditions that cannot be addressed using conventional antibody formats.