I want to walk you through exactly what happened, why it happened, and how you can engineer the same result for yourself. Because once you understand the system on the other side of the screen, getting matched to the right project stops feeling like a lottery and starts feeling like a craft.

This issue is free. The full prompt library, the resume template I now use, and the live “what’s working this month” updates live on the paid side. If you’ve been on the fence about upgrading, this is the issue I’d point you to first — because if even one of the sections below saves you a single rejection, you’ll have made back the subscription many times over.

Let’s get into it.

The offer that landed in my inbox before I even closed the tab

I’ll start with the moment itself, because it still feels strange to me.

I had spent maybe an hour the night before rewriting parts of my profile. Nothing dramatic — I didn’t add new experience, I didn’t take a new course, I didn’t sit a new assessment. I just changed the way my existing work was described. I rephrased my role, restructured my projects section, swapped out a few generic skill keywords for more specific technical ones, and re-uploaded a cleaner version of my resume.

The next morning I logged in to double-check that everything had saved. Before I had even finished scrolling, an offer notification appeared. An hourly project, in my domain, at a rate I was happy with, with the “instant offer” badge on it. Meaning: no live interview, no scheduling, no waiting for a recruiter to review me. Mercor’s matching system had already decided I was a fit, and the client had already pre-approved profiles that scored above a certain threshold.

I want to say it was luck. But I had been on the platform for weeks before this with a profile that, on paper, described exactly the same person. The version of me that got the instant offer was not a more qualified version. It was a better-described version.

That distinction matters more than almost anything else I’m going to tell you in this newsletter, so I want to put it in bold and let it sit on the page for a second:

Mercor is not evaluating you. Mercor is evaluating the document that represents you. And that document is being read by an AI, not a recruiter.

Once I internalized that, everything about how I approached the platform changed. The work I did didn’t become more impressive. The story I told about it did.

In the rest of this newsletter, I want to break down what’s actually happening behind the scenes, what specifically I changed in my resume and profile, the prompt sequence I now use to do this for every new role I target, and where I’m taking this next — including a Claude Code skill I’m starting to prototype that would automate the whole loop.

The thing nobody tells you: Mercor uses AI on both sides of the table

When most people think about Mercor, they think about the assessments. The recorded interviews. The little technical challenges. That’s the part of the experience that feels like the evaluation, so naturally that’s where people focus their effort.

But here’s the part that took me a long time to understand: those assessments are the second step. The first step — the one that decides whether you ever even see a role — is a matching layer. And that matching layer is doing two things, both of them with AI.

The first thing it does is parse every job description into a structured representation: required skills, preferred skills, domain, seniority, language requirements, project shape, rate band. The second thing it does is parse every candidate profile into the same kind of representation, then runs a similarity match. If you and the role score above a threshold, you’re surfaced. If you score above an even higher threshold, you get an instant offer with no human gate in between.

This has two very practical implications.

The first is that the parsing of your resume matters as much as the content. If the AI can’t extract a clean “Skills: Python, SQL, causal inference, Bayesian methods” line from your PDF, then it doesn’t matter that all of those words are technically somewhere in your bullet points. The system never gets to see them. PDFs with images of text, weird two-column layouts, custom fonts that don’t embed properly, headers that confuse the parser — all of these silently destroy your match score without you ever knowing.

The second implication is that you are, in effect, optimizing for a search engine. You don’t need to game it dishonestly — the assessments and the actual work will quickly filter out anyone who oversold themselves. But you do need to make sure that the keywords, framings, and structural cues that the AI is looking for are present, prominent, and parseable. Most people are losing matches not because they aren’t qualified, but because their resume is written for a 2015 human recruiter and not a 2026 LLM.

I think this is the single biggest gap between people who get instant offers on Mercor and people who don’t. It’s not talent. It’s not luck. It’s that one group has figured out they’re writing for a machine reader and the other group hasn’t.

Once you accept that, the entire game becomes: how do I make my profile maximally legible to an AI that is trying to decide if I belong in a specific project? And the answer to that question, it turns out, is something you can solve with another AI.

What I actually changed (and why each change works)

Here is the concrete edit list. I’m not going to bury the lede behind a paywall on this part because I want you to be able to make these changes today, even if you never upgrade.

Change one: I reframed my role. My old summary led with my job title and industry. The new one leads with the methods I use. Instead of “Marketing Data Scientist with five years of experience,” it reads as a person whose core competencies are mathematical modeling, statistics, causal inference, optimization, and structured reasoning — who happens to have applied those skills in a marketing context. Same person. Completely different match signal. The matcher cares about what you can do, not what your previous employer called your seat.

Change two: I built a real projects section, and made it the biggest section on the page. This is the change that, if I had to pick one, made the biggest difference. I took work I had already done at past jobs and at Mercor and turned each one into a discrete project with a name, a one-line description of the technical approach, and a one-line description of the outcome. Budget optimization became “constrained optimization across a fixed-budget allocation problem, modeled in Python, reduced cost-per-acquisition by X%.” Causal analysis became “experiment design and statistical inference on a multi-arrm test, using difference-in-differences to isolate treatment effect.” Each project is a dense little bundle of keywords plus evidence that I actually executed.

The matcher loves this format because it’s exactly what a job description looks like — a problem, a method, a result — just from the candidate’s side of the table. It’s the only resume section that maps one-to-one onto what the AI is comparing against.

Read more

If you’re an AI-powered nomad, you’ve felt this gap. You’re a researcher in Beijing weighing a Bay Area infra startup. An engineer in Lisbon eyeing a stealth Series A in Tel Aviv. A PM in Shenzhen who wants to know what’s actually open at the frontier AI companies this week — not what was open three months ago when some aggregator last crawled the listing.

The opportunities you actually want move in days. The tools you have to find them are stuck in 2019.

Traditional job boards give you volume. What they don’t give you is context. They don’t tell you that the ex-CEO/CTO of Twitter is quietly hiring his founding AI team in Palo Alto. They don’t tell you that an autonomous-swarm defense startup just opened a fully remote Forward Deployed Engineer slot. They don’t tell you that Spotify is staffing a brand-new “AI Fleet Management” engineering org with a worldwide remote hire.

Context is what separates a job listing from an opportunity.

That’s what semidiffusion is building. In a 2026 job market where remote work listings churn weekly and AI startup roles close in days, I do the work that job boards won’t: I verify that the role is actually open right now, I trace the funding and the founders, and I tell you why the opportunity matters — not just that it exists.

This is the May 10 Job Posting edition. Two categories, twenty roles, every single one verified open within the past seven days.

AI Startup Jobs — Founder-Led, Hiring Now

These roles come from founder-led companies actively scaling their teams this week. Every company below is funded, building, and visibly recruiting right now. The window on these is narrow: startup hiring moves fast, and most of these roles will close in days, not months.

1. Member of Technical Staff, AI — Parallel Web Systems

Parag Agrawal — yes, the ex-Twitter CEO/CTO — is building Parallel as an AI-native web platform out of SF / Palo Alto. The MTS-AI seat is a foundational engineering role: shape model architecture, define how Parallel’s agents interact with the open web, and own systems other startups will eventually build on top of. If you wanted a “founding-team-with-real-distribution” bet, this is one of the few in 2026. Apply: https://jobs.ashbyhq.com/parallel/e15b451f-8c56-4747-a1b6-1f2c0fa47ef3

2. Senior AI Engineer — Doctronic

Doctronic is building AI-augmented primary care, and this senior engineering hire owns the model layer that sits between physicians and patients. NYC-based with a small team — meaningful equity, real product surface. If you’re an ML engineer who has been waiting for a healthcare role that actually ships product (not just papers), this is the one. Apply: https://jobs.ashbyhq.com/doctronic/a1f7662b-af9c-4705-b168-9ca12c3854ce

3. Forward Deployed Engineer — Swarm Aero

Swarm Aero is building autonomous swarming aerial systems for the US military. This Forward Deployed Engineer role is fully remote and acts as the bridge between Swarm’s software stack and operators in the field. You’ll embed with mission teams, write code that flies, and ship updates that matter inside hours, not quarters. Apply: https://jobs.ashbyhq.com/swarmaero/60050a43-819f-41fd-a02b-a652d7461dce

4. Founding Machine Learning Engineer — Shepherd

Shepherd has quietly become the AI-native insurance carrier for the construction industry. The Founding ML Engineer slot in SF means you own the underwriting models from the ground up — the loss data, the feature pipeline, the agentic risk assessment. Insurance is one of the largest, slowest verticals on earth, and Shepherd is the AI-native incumbent in waiting. Apply: https://jobs.ashbyhq.com/shepherd/797316b4-bdcc-4c0c-8bc2-46d4648db240

5. Agent Product Manager — Notch

Notch is building production AI agents out of Ramat Gan, Israel — the same talent pool that produced Wiz, Lightricks, and most of the world’s enterprise security infra. The Agent PM role is the rare PM seat where you actually define the agent’s behavior, evaluation harness, and customer-facing surface area. If you’ve been a PM for an LLM-wrapping product and want the real thing, look here. Apply: https://notch.cx/careers/agent-product-manager

6. Founding Talent Lead — Conduit Health

Conduit Health is scaling a clinical network and needs a Founding Talent Lead in NYC to build the recruiting engine before the company hits Series B. This is a “build the function from scratch” role — you set the bar, the comp bands, the loop. Strong fit if you’ve recruited at a healthtech that grew from 30 to 300. Apply: https://jobs.ashbyhq.com/conduit-health/6afbd685-f821-4dd6-b486-1a877168aa38

7. Senior Software Engineer, Infrastructure — Sift

Sift is building telemetry infra for hard-tech companies — think the observability layer for rockets, robots, and reactors. This Marina Del Rey-based role owns the ingestion pipeline that processes millions of sensor channels. If you’ve been doing distributed systems at a hyperscaler and want hard tech without leaving the SoCal lifestyle, this is a clean fit. Apply: https://jobs.ashbyhq.com/siftstack/64da755e-5cd8-4e65-a475-fdc6055fa33b

8. Forward Deployed Engineer — PointOne

PointOne is the vertical AI platform for legal operations, and the FDE role in NYC is the highest-leverage seat in the company. You sit inside law firms, watch the workflow, and ship custom integrations that turn $800/hour billable work into $80/hour AI work. You’ll also be the loudest signal back into product. Apply: https://jobs.ashbyhq.com/pointone/834a8648-5581-4d69-80cb-41382928d220

9. Founding Account Executive — Hanover Park

Hanover Park is building modern infrastructure for fund administration, and the Founding AE in NYC will close the first wave of mid-market hedge fund and private credit clients. Strong fit if you sold to CFOs or fund ops at Carta, Allvue, or Addepar — you’ll have inbound from day one and equity that matters. Apply: https://jobs.ashbyhq.com/hanover-park/59a752d8-5608-4788-a67c-e2ece03e29b7

10. Lead Product Designer — Sandbar

Sandbar is building wearable AI audio hardware out of NYC — small team, real device, shipping. The Lead Product Designer role owns the entire app surface plus a meaningful slice of the hardware UX. If you’ve been designing software all your career and want a product you can hold in your hand, this is one of the cleanest hardware-software design roles open this week. Apply: https://jobs.ashbyhq.com/sandbar/f9d9661c-526c-42e1-9171-17c48e5e66f9

Remote Jobs Hiring Worldwide — Verified Open This Week

These ten roles were all posted on May 10, 2026 and verified live against the source job pages. Every link below points to the canonical RemoteOK posting, which then routes you to the company’s own application system. Worldwide remote, no relocation expected.

1. Engineering Manager, AI Fleet Management & Honk — Spotify

Spotify is staffing a brand-new engineering org around AI fleet management — the systems that manage Spotify’s growing fleet of internal AI services. EM role, worldwide remote, real budget. Strong fit if you’ve managed an SRE or platform team at a consumer-scale company. Apply: https://remoteOK.com/remote-jobs/remote-engineering-manager-ai-fleet-management-amp-honk-spotify-1131520

2. Senior Manager, Government & Industry Affairs Operations — VGW

VGW (the Australian gaming giant behind Chumba and Global Poker) is hiring a senior ops manager to handle government and industry affairs across multiple jurisdictions. Worldwide remote, regulatory-heavy, high-leverage role. Apply: https://remoteOK.com/remote-jobs/remote-senior-manager-government-industry-affairs-operations-vgw-1131518

3. People Operations Lead — Defense Unicorns

Defense Unicorns is the open-source DevSecOps company building Kubernetes-native software for the US Department of Defense. People Ops Lead role, fully remote, high-trust environment. Strong fit if you’ve done People Ops at a fast-growing engineering org. Apply: https://remoteOK.com/remote-jobs/remote-people-operations-lead-defense-unicorns-1131517

4. Web Development Specialist — Marketers in Demand

Hands-on full-stack role at a remote-first agency. You’ll build and maintain client websites across modern stacks. Worldwide remote — this one is friendly to nomads in non-US time zones. Apply: https://remoteOK.com/remote-jobs/remote-web-development-specialist-marketers-in-demand-1131516

5. Principal Marketing Analytics Manager — Greenhouse

Greenhouse (the recruiting platform) is hiring a Principal-level marketing analytics manager. Senior IC track, worldwide remote, owning the attribution stack and the experimentation framework. Apply: https://remoteOK.com/remote-jobs/remote-principal-marketing-analytics-manager-greenhouse-1131515

6. Sales Development Representative — Kiavi

Kiavi (formerly LendingHome) is the largest tech lender to real estate investors in the US. SDR role, worldwide remote, with a meaningful path to AE for the right person. Apply: https://remoteOK.com/remote-jobs/remote-sales-development-representative-kiavi-1131514

7. Analytics Engineer — Civitech

Civitech builds technology for progressive campaigns and civic engagement. Analytics Engineer role, worldwide remote, dbt-heavy — meaningful work for someone who wants their data pipelines to actually move the needle on civic outcomes. Apply: https://remoteOK.com/remote-jobs/remote-analytics-engineer-civitech-1131512

8. Tech Lead — Zensurance

Zensurance is a Toronto-based digital insurance brokerage scaling fast. Tech Lead role, worldwide remote, owning a core engineering team. Strong fit for a senior engineer ready to step into a player-coach seat. Apply: https://remoteOK.com/remote-jobs/remote-tech-lead-zensurance-1131509

9. Senior Software Engineer — Cast AI

Cast AI is the Kubernetes cost-optimization platform used by some of the largest engineering orgs in the world. Senior SWE role, worldwide remote — strong fit for backend engineers who like distributed systems and infrastructure. Apply: https://remoteOK.com/remote-jobs/remote-senior-software-engineer-cast-ai-1131507

10. Senior Data Engineer — Valon Mortgage

Valon is the modern mortgage servicer challenging legacy incumbents. Senior Data Engineer role, worldwide remote, building the data layer that powers their entire servicing platform. Apply: https://remoteOK.com/remote-jobs/remote-senior-data-engineer-valon-mortgage-1131504

How semidiffusion Curates AI and Remote Job Listings Differently

Most job newsletters give you a list. I give you a list with an expiration date — because that’s how startup hiring actually works. Every role above was verified open within the past seven days. By the time you read this, some will already be closing. That’s not a flaw in the newsletter. That’s the reality of the market.

The other thing I do differently is source diversity. The startup roles come from founder-led companies and the a16z Build network — positions that founders and their investors are actively promoting, not stale postings sitting in a Greenhouse graveyard. The remote roles come from live RemoteOK data, cross-referenced against the actual job pages.

I’m not going to pretend this is comprehensive. Twenty jobs is a curated snapshot. The AI-era job market has thousands of openings at any given moment, and they churn constantly. What I can promise is that everything you see here is real, current, and comes with enough context to decide whether it’s worth your time.

Get Personalized AI Job Recommendations Every Week

This free edition gives you the same 20 roles everyone else gets. But the AI-era job market is personal. A PM in Shenzhen and a data engineer in Berlin don’t need the same list.

On top of the curated jobs, paid subscribers also get open DMs with me. Tell me about yourself, your background, what you’re optimizing for, and I’ll give you tailor-made recommendations. Flag roles you’ve seen elsewhere and I’ll give you my honest read. Over time, your feedback makes the recommendations sharper. The more I learn about what you’re actually looking for, the better the matches get.

Paid subscribers get a separate, customized weekly jobs email. Here’s how it works:

Subscribe now

I take your background, your target roles, your preferred geographies, and your compensation expectations, and I build a shortlist that’s actually tailored to you. Not an algorithm. Not a keyword match. A human who understands both the AI talent market and the companies behind the listings, filtering for fit.

This is the part of semidiffusion that doesn’t scale, which is exactly why it’s behind the paywall. I can only do this for a small number of people, and I want to do it well.

If you’ve been reading semidiffusion for free and getting value from it, this is the moment to convert. The job market moves fast. Having someone in your corner who’s tracking it in real time is worth more than another browser tab of job board bookmarks.

See you next week. And if you applied to anything from this list, reply and tell me. I want to know what’s landing.

This article is part of semidiffusion’s weekly job posting series, covering remote jobs, AI startup hiring, and digital nomad career opportunities in 2026. We verify every listing within seven days of publication and provide direct apply links. For personalized job recommendations and open DM access, upgrade to a paid subscription at www.semidiffusion.com.

If you’re an AI-powered nomad, you’ve felt this gap. You’re a researcher in Beijing weighing a Bay Area infra startup. An engineer in Lisbon eyeing a stealth Series A in Singapore. A PM in Shenzhen who wants to know what’s actually open at the frontier AI companies this week, not what was open three months ago when some aggregator last crawled the listing.

The opportunities you actually want move in days. The tools you have to find them are stuck in 2019.

Traditional job boards give you volume. What they don’t give you is context. They don’t tell you that Replit just tripled its valuation to $9B and is hiring a Chief of Staff who’ll work directly with the CEO. They don’t tell you that a Harvard Physics PhD is building the future of AI music and needs a PM who understands creators. They don’t tell you that a defense tech founder from Anduril just raised $34M and is hiring engineers to build power systems for the US military.

Context is what separates a job listing from an opportunity.

That’s what semidiffusion is building. In a 2026 job market where remote work listings churn weekly and AI startup roles close in days, I do the work that job boards won’t: I verify that the role is actually open right now, I trace the funding and the founders, and I tell you why the opportunity matters, not just that it exists.

This is the first full Job Posting edition. Two categories, twenty roles, every single one verified open within the past seven days.

AI Startup Jobs — a16z-Backed, Hiring Now

These roles come from the a16z Build network, the talent pipeline of Andreessen Horowitz. Every company below has raised fresh capital and is actively building their team right now. The window on these is narrow: startup hiring moves fast, and these roles will close in days, not months.

1. Chief of Staff to the CEO — Replit Replit just closed a $400M Series D at a $9B valuation, tripling in six months. You’ll work directly with CEO Amjad Masad, owning the hardest cross-functional problems he can’t delegate, coordinating the CEO’s network to accelerate go-to-market internationally, and building integrated views of product, market, and business dynamics that no single function owns. Apply: https://jobs.ashbyhq.com/replit/95332816-5890-4fac-b5fc-4b0cea0d77db

2. AI Creative Producer — ElevenLabs ElevenLabs is defining what AI-generated content looks like at scale. This role sits on the Creator Growth team. You’ll prototype workflows, test models, and push creative boundaries, producing everything from cinematic visuals and short films to social assets that inspire millions of creators. Apply: https://elevenlabs.io/careers/3178581d-ea70-4dee-b018-2ce2d2a18bbe/ai-creative-producer

3. Product Manager, Artists & Creators — Suno Harvard Physics PhD Mikey Shulman is building the future of AI music generation. You’ll represent the artist and creator journey on Suno, define how creators grow on the platform, build systems that surface and scale talent, and launch new products to accelerate artist success. In-person NYC or Venice Beach. Apply: https://jobs.ashbyhq.com/suno/0740427c-6afa-4f3f-a3e1-1675fa23301c

4. Senior Product Manager, Consumer — Counsel Health Stanford MD Muthu Alagappan is building an AI-enabled, physician-supervised primary care platform. You’ll own the Day 0 to Day 30 experience for new users, engineer meaningful “aha” moments, and run the core chat experience around how users receive care. Based in NYC. Apply: https://jobs.ashbyhq.com/counsel/b6edfdc2-539c-4e6d-9b07-054618ef5f70

5. Founding Customer Success Manager — Comfy Ex-Google engineer Yoland Yan raised $30M for Comfy, an open-source, node-based workflow platform for generative AI. You’ll build the customer success playbook from scratch: which customers get white-glove treatment, what onboarding looks like, how to measure health, and how the team scales. Based in SF. Apply: https://jobs.ashbyhq.com/comfy-org/a1c5c5ed-62ac-4767-af57-a3ba4e0bf5e4

6. Content Engineer — Baseten This isn’t a traditional content role. You’ll operate at the intersection of growth, product marketing, and community building. Your job is to create the pipeline for generating high-viewership content and define Baseten’s playbook for discoverability in AI engines. 3-month contract-to-hire. Apply: https://jobs.ashbyhq.com/baseten/a0fd4d94-dfd7-4165-9cdd-25e3d31e25c4

7. Brand Designer, Creative Labs — Stripe Stripe’s creative team spans digital installations, interactive games, live-streaming a hand-built city over Black Friday, and producing films. This is a highly experimental, idea-driven role in NYC. Your ability to generate innovative ideas matters as much as your ability to bring them to life. Apply: https://stripe.com/jobs/listing/brand-designer-creative-labs/7793636

8. Senior SWE, Core Product — Salient YC W23 financial ops startup reshaping how millions of loans are serviced through AI. You’ll own everything from payment processing to fraud prevention to customer support, handling both the 0-to-1 MVP development and the 1-to-10 scaling phase. Based in SF. Apply: https://jobs.ashbyhq.com/salient/03ec52e9-746f-45e0-8cb5-0fdf057e4ed3

9. Mechanical Engineer — Chariot Defense Founded by Adam Warmoth (prev Anduril, Uber, Archer) with a $34M Series A. You’ll conceptualize, design, develop, and test advanced mechanical and power electronic systems, including fully integrated vehicle platforms for the US military and its allies. Apply: https://job-boards.greenhouse.io/chariotdefense/jobs/5181624008

10. Founding Team — Petual (AI for Audit) Snir Kodesh (prev Head of Eng at Retool, Sr Dir of Eng at Lyft) raised $20M to automate SOX testing with AI agents. Over $8B is spent annually on SOX compliance in the US alone. Petual’s agents aim to deliver audit testing results from any dataset in minutes. Building the founding team in SF. Email: contact@petual.ai

Remote Jobs Hiring Worldwide — Verified Open This Week

These roles are sourced from RemoteOK, verified accessible as of this week (data updated May 3, 2026). Every link goes to a real job posting. Click through to the listing page, then hit “Apply” to reach the company’s own application system.

1. Lead Analytics Engineer, Borrowing — Monzo The UK challenger bank is hiring a lead analytics engineer for its lending vertical. You’ll own the data infrastructure that powers lending decisions. Apply: https://remoteok.com/remote-jobs/remote-lead-analytics-engineer-borrowing-monzo-1131423

2. Maps Visual Design Relevance Rater (English) — Welo Global An evaluation and annotation role. You’ll rate the visual design relevance of map interfaces. Flexible, contract-based, worldwide. Apply: https://remoteok.com/remote-jobs/remote-maps-visual-design-relevance-rater-english-welo-global-1131422

3. Solutions Analyst — Sayari Sayari builds supply chain risk and financial intelligence tools. You’ll work with enterprise clients to implement and optimize the platform. Apply: https://remoteok.com/remote-jobs/remote-solutions-analyst-sayari-1131421

4. Senior Data Engineer — Business Wire Berkshire Hathaway’s global press release distribution company is hiring a senior data engineer to build and maintain data pipelines at scale. Apply: https://remoteok.com/remote-jobs/remote-senior-data-engineer-business-wire-1131415

5. Digital Full Stack Engineer — Smart Working Solutions Full stack role (HR172) at a remote-first consultancy. You’ll build digital products across the stack. Apply: https://remoteok.com/remote-jobs/remote-digital-full-stack-engineer-hr172-smart-working-solutions-1131414

6. Full Stack Staff Engineer — Join Staff-level full stack engineering at Join, a construction estimating platform. Senior IC role with architectural ownership. Apply: https://remoteok.com/remote-jobs/remote-full-stack-staff-engineer-join-1131413

7. VP of Global Customer Success & Support — JumpCloud Executive role at JumpCloud, the open directory platform. You’ll lead global CS and support strategy for a company serving 200,000+ organizations. Apply: https://remoteok.com/remote-jobs/remote-vice-president-of-global-customer-success-amp-support-jumpcloud-1131411

8. Senior Software Developer — Geotab Geotab is one of the largest telematics companies in the world. You’ll build software for fleet management and IoT at scale. Burnaby-based but remote-friendly. Apply: https://remoteok.com/remote-jobs/remote-senior-software-developer-burnaby-geotab-1131407

9. Founding Engineer — Haast Early-stage founding engineer role. You’ll have significant ownership and build core product from scratch. Apply: https://remoteok.com/remote-jobs/remote-founding-engineer-haast-1131402

10. Staff Data Engineer — Imagine Pediatrics Imagine Pediatrics delivers virtual-first care for children with complex medical needs. You’ll build the data infrastructure powering clinical operations and outcomes measurement. Apply: https://remoteok.com/remote-jobs/remote-staff-data-engineer-imagine-pediatrics-1131401

How semidiffusion Curates AI and Remote Job Listings Differently

Most job newsletters give you a list. I give you a list with an expiration date, because that’s how startup hiring actually works. Every role above was verified open within the past seven days. By the time you read this, some will already be closing. That’s not a flaw in the newsletter. That’s the reality of the market.

The other thing I do differently is source diversity. The startup roles come from the a16z Build network, which means you’re seeing positions that founders and their investors are actively promoting, not stale postings sitting in a Greenhouse graveyard. The remote roles come from live RemoteOK data, cross-referenced against the actual job pages.

I’m not going to pretend this is comprehensive. Twenty jobs is a curated snapshot. The AI-era job market has thousands of openings at any given moment, and they churn constantly. What I can promise is that everything you see here is real, current, and comes with enough context to decide whether it’s worth your time.

Get Personalized AI Job Recommendations Every Week

This free edition gives you the same 20 roles everyone else gets. But the AI-era job market is personal. A PM in Shenzhen and a data engineer in Berlin don’t need the same list.

Paid subscribers get a separate, customized weekly jobs email. Here’s how it works:

I take your background, your target roles, your preferred geographies, and your compensation expectations, and I build a shortlist that’s actually tailored to you. Not an algorithm. Not a keyword match. A human who understands both the AI talent market and the companies behind the listings, filtering for fit.

On top of the curated jobs, paid subscribers also get open DMs with me. Tell me about yourself, your background, what you’re optimizing for, and I’ll give you tailor-made recommendations. Flag roles you’ve seen elsewhere and I’ll give you my honest read. Over time, your feedback makes the recommendations sharper. The more I learn about what you’re actually looking for, the better the matches get.

This is the part of semidiffusion that doesn’t scale, which is exactly why it’s behind the paywall. I can only do this for a small number of people, and I want to do it well.

Subscribe now

If you've been reading semidiffusion for free and getting value from it, this is the moment to convert. The job market moves fast. Having someone in your corner who's tracking it in real time is worth more than another browser tab of job board bookmarks.

See you next week. And if you applied to anything from this list, reply and tell me. I want to know what’s landing.

This article is part of semidiffusion’s weekly job posting series, covering remote jobs, AI startup hiring, and digital nomad career opportunities in 2026. We verify every listing within seven days of publication and provide direct apply links. For personalized job recommendations and open DM access, upgrade to a paid subscription at www.semidiffusion.com.

P.S. Know someone who's job hunting in the AI space? Forward this to them. They can subscribe for free at www.semidiffusion.com.

Previous highlights

What actually happens is that the AI labs behind the scenes run internal experiments on a cadence that is completely disconnected from your personal income needs.

So I did what any rational operator does when one of their income streams temporarily dries up. I installed the second app.

A few years ago, every serious gig driver I knew had both Uber and Lyft open on their dashboards at the same time. Not because they disliked either platform, but because running on a single app is how you get quietly starved out. The AI training economy is reaching the same moment. If Mercor is the Uber of this space, with the broadest marketplace and the loudest IPO chatter, then micro1 is the Lyft. A credible second platform with its own philosophy, its own pay cycles, and its own approach to how it matches experts to AI labs.

Here is what I learned in the last two weeks.

A brief history of micro1

The company you know as micro1 was not originally called micro1. It was called Moontek, incorporated on September 1, 2019, in Los Angeles, by a founder named Ali Javid. For its first three years, Moontek was a boutique talent arbitrage firm. The business model was essentially to find elite technical talent in emerging markets who were priced below their US peers, and connect them to American startups. It was a service business, not a platform.

The pivot started quietly in June 2022, when the company released its first AI-powered technical assessment tool. By 2023, Moontek had been folded into a new identity called micro1, headquartered in Palo Alto. This is a pattern I find fascinating from a product perspective. The original talent network was the moat. The AI vetting tool was the scaling mechanism that turned a services business into software.

Today micro1 is run by Ali Ansari, a 24-year-old serial entrepreneur who is completing a part-time master’s at Stanford under the mentorship of Stefano Ermon, one of the most respected names in reinforcement learning. This detail matters more than it looks. Ansari’s academic connection to Ermon tells you exactly where the platform is going: RL environments, agentic workflows, verifiable reasoning tasks. The technical roadmap is not accidental.

The financials back this up. micro1 entered 2025 with roughly $7 million in ARR. By December it had crossed $100 million. The most recent funding round valued the company around $500 million, with chatter about the next round landing well above $2.5 billion. The backers include Founders Fund, 01 Advisors, and Jason Calacanis. The board includes Adam Bain, the former COO of Twitter.

None of this guarantees a great experience for contributors. But it does tell you that micro1 is not a weekend project. It has the capital, the customers, and the academic lineage to be a meaningful second platform for the foreseeable future.

Why I am not writing Mercor's obituary

I want to be clear about something before I go further. I am not writing Mercor’s obituary, and I do not think the playbook I shared in my previous article has expired. If anything, the thesis behind that playbook is getting stronger.

In March, Ansari and his chief economist Mark Esposito published a paper I would recommend every aspiring AI trainer read once. It is called “No Last Mile: A Theory of the Human Data Market.” The argument is simple. Human data is not temporary scaffolding that gets removed once the building is finished. It is a permanent maintenance layer. Models depreciate. Task contexts drift. Standards evolve. New edge cases emerge constantly. The paper’s conservative calibration predicts a steady-state labor share of five to seven percent for human-data work in the AI economy. Small as a percentage. Enormous as a dollar figure.

If you internalize this thesis, the Mercor pause stops feeling like an existential threat and starts feeling like a scheduling issue. Projects will resume. New ones will start. In the meantime, you do what any rational operator does and diversify your distribution.

The interview: meeting Zara

Read more

Previous highlights

Y Combinator CEO Garry Tan called it “a major national security issue” on X. Reddit threads on r/mercor_ai blew up overnight. The stolen data is reportedly being auctioned on the dark web.

I am not going to sugarcoat this. It is a serious incident.

But here is what I will say after six months on the platform, earning over $37k and ranking in the top 10% of contributors:

Mercor is still one of the best ways to make real money with your expertise, from anywhere in the world. Breaches happen to companies of every size. Remember the Microsoft, LastPass, and even the National Public Data incidents? What matters now is how Mercor responds, and whether the fundamentals of the opportunity have changed. They have not. AI labs still desperately need human experts for training data, and the pay still reflects that urgency.

If you are already on the platform, change your passwords immediately, enable two-factor authentication, and monitor your bank accounts closely over the next few months. If you are thinking about joining, do not let one security event scare you away from a genuinely transformative income stream.

And while we are on the topic, I want to encourage you to keep an open mind about the broader ecosystem. Mercor is excellent, but it is not the only game in town. Platforms like Micro1 and Surge AI offer similar opportunities connecting domain experts with AI labs. Diversifying across multiple platforms is smart for both income stability and risk management, especially in moments like this.

Now let me answer the questions I have been getting most from readers.

Q&A: Your Mercor Questions, Answered

Q1: My first two projects did not go well. How do I recover my standing on Mercor?

Read more

Previous highlights

So here it is. The playbook I wish someone had handed me on day one.

But first, a mindset shift. Because if you walk into Mercor thinking like a traditional freelancer—or worse, like a salaried employee—you’re going to have a terrible time.

The AI-Era Uber

Let me give you the mental model that changed everything for me.

Mercor is Uber for AI training. Structurally.

Think about what Uber did. It sat between people who needed rides and people who could drive. It didn’t employ the drivers. It didn’t own the cars. It built the marketplace, handled the matching, and took a cut. The drivers showed up, completed trips, got rated, and either kept getting rides or didn’t.

Mercor does the same thing, except the “riders” are frontier AI labs—OpenAI, Google DeepMind, Anthropic, Meta, and others building the most powerful models on the planet—and the “drivers” are domain experts like you and me. The labs need human-generated data to train and evaluate their models. They need people who can spot where GPT-5 or Gemini or Claude falls apart, write better responses, and judge which outputs are actually correct. Mercor finds those people, organizes them into project teams, and manages the whole operation.

Once you internalize this, a lot of things that frustrate people suddenly make sense.

Projects ending abruptly? That’s normal. The AI lab finished that phase of training, or their evaluation goals shifted, or the model got good enough at that particular task that they no longer need human data for it. It’s not personal. It’s not a performance issue. It’s a ride ending because the passenger reached their destination.

I see people in community groups losing their minds every time a project gets terminated. “I just got off-boarded!” “They cut us without warning!” I understand the anxiety. Losing income is stressful. But panicking about project termination on Mercor is like an Uber driver panicking every time a passenger gets out of the car. That’s… how it works.

The better analogy might be commercial fishing. You go where the fish are. Some seasons are abundant. Some aren’t. You maintain your gear, keep your skills sharp, and stay ready for the next run. The fisherman who prospers isn’t the one who catches one big haul and retires. It’s the one who shows up consistently, reads the water, and adapts.

So rule number one of the Mercor playbook: get comfortable with impermanence. Don’t over-index on any single project. Don’t mentally spend money you haven’t earned yet. And don’t mistake a project ending for a career ending.

What You’re Actually Getting Paid For

Here’s something that trips up a lot of new Mercor contributors, especially people coming from traditional tech jobs: you’re not getting paid to be smart. You’re getting paid to find where the model is stupid.

That distinction matters enormously. The AI labs aren’t hiring domain experts because they want you to demonstrate your knowledge. They’re hiring you because their model needs to get better, and the only way it gets better is if humans identify the gaps and fill them with high-quality data.

Your job, at its core, is quality control and gap detection. You’re looking at model outputs and asking: Where did this go wrong? What did it miss? What does it think it knows but actually doesn’t? And then you’re writing responses that show the model—or, more precisely, the training pipeline—what a correct, complete, expert-level answer actually looks like.

This requires a specific kind of thinking. You need to resist the urge to just “write a good answer.” Instead, you need to interrogate the model’s attempt first. Find the failure modes. Spot the hallucinations, the subtle logical errors, the places where the model sounds confident but is actually making things up. Then, and only then, craft the expert response that addresses those exact weaknesses.

The people who do this well become invaluable. The people who just bang out competent answers without really engaging with why the model failed get average ratings and wonder why they’re not getting staffed on the good projects.

The SPL: Your Most Important Relationship

Every Mercor project has an SPL—a Special Project Lead. If Mercor is Uber, the SPL is the dispatcher who also happens to be your local manager, client liaison, and quality gatekeeper rolled into one.

Read more

What it does require is deep domain expertise and the ability to teach artificial intelligence how to think.

Over the last four months, I’ve made $37,000 working on Mercor, a platform that connects experts with top-tier AI labs. I am currently a top performer at one of the leading AI training data companies and rank in the top 10% of earners.

This is my first article breaking down exactly how this ecosystem works—and more importantly, how you can break into it.

There is a new category of jobs quietly emerging in the tech world. It doesn’t require you to live in Silicon Valley, and it doesn’t require a traditional corporate resume.

What it does require is deep domain expertise and the ability to teach artificial intelligence how to think.

Over the last four months, I’ve made $37,000 working on Mercor, a platform that connects experts with top-tier AI labs. I am currently a top performer at one of the leading AI training data companies and rank in the top 10% of earners.

This is my first article breaking down exactly how this ecosystem works—and more importantly, how you can break into it.

The Shift: The Demand for Human Intelligence is Real

Right now, Google, OpenAI, Anthropic, and others are locked in an arms race. But they’ve hit a bottleneck: they are running out of high-quality human data to train their models.

To bridge the gap from GPT-4 to the next frontier, these companies need experts for SFT (Supervised Fine-Tuning) and RLVR (Reinforcement Learning from Verifiable Rewards). They need humans who can evaluate complex agentic workflows and correct AI when it hallucinates.

The demand for human experts is massive, and the compensation reflects that.

The First Hurdle: Cracking the AI Interview

To get access to these high-paying tasks, you have to pass the vetting process. Here is where most people fail: Your interviewer is an AI.

Read more

semi◦diffusion is your bridge to the world's top remote positions. We cut through the noise and deliver only the highest-value, most flexible opportunities. No matter where you are, we help you break free from the traditional office and take full control of your time while maintaining top-tier earnings.

Subscribe now

💼 Role Details: Consumer Electronics Expert

This is an opportunity to leverage your consumer electronics domain knowledge to evaluate the quality and relevance of agent-generated research reports in the consumer electronics space. You will be directly involved in training and optimizing cutting-edge AI models.

• Work Mode: Fully remote (100% Remote), location flexible.

• Client: You will indirectly serve top international AI laboratories.

• Compensation: 80 – 150 RMB per task (task-based pay, flexible and efficient).

🎯 Who Are We Looking For?

If you meet the following criteria, this is the perfect side hustle or freelance opportunity:

• Background in consumer electronics.

• Interest in AI technology and willingness to "teach the machines" with your domain expertise.

• A high-agency work style with consistent, high-quality output.

• Basic English writing ability.

📩 How to Apply

This is a direct entry point into the high-value AI data supply chain. No complex interview process required. We value your professional track record.

1. Reply directly to this email

2. Attach your CV and relevant experience.

💌 Feel free to forward this to friends who are passionate about consumer electronics and remote work. Forward and receive 1 month of free semi◦diffusion membership, including exclusive job postings and practical tips for solopreneurs.

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This is semi◦diffusion. semi◦diffusion connects you with the world's top remote positions. We cut through the noise and deliver only the highest-value, most flexible opportunities. No matter where you are, we help you break free from the traditional office and take full control of your time while maintaining top-tier earnings.

This article is based on notes from Stanford neurobiology professor Andrew Huberman's episode on "Sugar and the Brain."

Whenever work stress piles up or my mood dips, I crave something sweet. And that impulse is incredibly hard to suppress.

We all know too much sugar is bad for us. But why can't we stop? Why do we plan to eat just one cookie and end up finishing the whole pack? Why do bubble tea and soda always taste so irresistible?

After listening to Andrew Huberman's episode on "Sugar and the Brain," it all clicked.

It's not your fault. Blame your nervous system.

Your sugar cravings are the result of interactions between your brain, your gut, and your nervous system. Even if you numbed your taste buds entirely, your brain would still desperately want sugar.

01 Sugar's Double Trap: You Literally Can't Escape

We usually assume we crave sweets because of taste, because they're delicious. That's only half right.

At least half of your sugar cravings are "unconscious," driven by your gut.

Sugar controls your brain through two parallel highways. The first is taste. When you eat something sweet, receptors on your tongue immediately signal your brain: "Good stuff! Release the dopamine!" This is a split-second reaction that makes you feel instant pleasure. The second highway is your gut. Your intestines contain special cells called Neuropod cells. Even if you eat carbs with no sweetness, or hidden sugars with their taste masked, as long as they reach your stomach and can be converted into glucose, these cells light up.

They fire a direct message to your brain via the vagus nerve: "Energy detected! Make him eat more!"

Scientists removed the sweet-taste receptors in mice (so they couldn't taste sweetness) and gave them sugar water. At first, the mice wouldn't drink it. But 15 minutes later, once the sugar water hit their gut and activated the Neuropod cells, the mice started drinking the "tasteless water" like crazy.

Even if you fool your tongue, you can't fool your gut. That's why so many non-sweet processed foods (chips, crackers) are equally addictive. They're loaded with hidden sugars that activate your gut.

02 Lemon Juice and Cinnamon: "Blood Sugar Medicine" from Your Kitchen

Now that you understand the mechanism, how do you fight back?

Here are a few practical methods that don't cost much.

Before (or during) eating high-carb or sweet foods, drink a few spoonfuls of lemon juice or lime juice diluted in water. The sourness doesn't just alter your taste perception. It also slows gastric emptying and blunts the blood sugar spike. Smaller blood sugar swings mean a weaker dopamine rollercoaster, which means less craving for "just one more bite."

Cinnamon is also remarkably effective. Sprinkle some when cooking or into your coffee. Cinnamon can mimic insulin's action, helping slow the rate at which sugar enters your bloodstream. Make sure you buy real cinnamon (Ceylon), and keep your intake under 1.5 teaspoons per day to avoid potential liver strain.

03 Sleep and Fish Oil

Research shows that sleep isn't just rest. It's a metabolic "rehearsal."

If you're sleep-deprived, your nervous system essentially malfunctions. It sends false signals telling you to keep eating even when you're full.

Getting enough sleep is the cheapest appetite-control medicine there is.

Supplement with at least 1 gram of Omega-3 EPA daily (check the fish oil label, focus on EPA content).

This isn't just for your heart. It's for repairing your neurons and dialing down your dopamine system's sensitivity, so it doesn't go haywire over every little taste of sweetness.

We don't need to demonize sugar. We don't need to never eat a slice of cake again. But we need to understand that many of today's snacks are engineered to exploit your neurological weak points. The next time you reach for another cookie, pause for one second and ask yourself:

Do you actually want it? Or are a few cells in your gut pulling your strings?

Drink some lemon water. Get a good night's sleep. Take back control.

这里是 半扩散工作室（semi◦diffusion）。半扩散工作室（semi◦diffusion） 为您链接全球顶尖远程职位。我们摒弃低效筛选，只为您提供最高价值与最强灵活性的工作机会。无论身在何处，我们助您摆脱传统办公限制，在保持高收益的同时，享受掌控时间的绝对自由。

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在大模型迅速扩张的当下，真正稀缺的已不再是算力或参数规模，而是经过专业训练、具备方法论与判断力的人类知识本身。

字节跳动旗下的 Xpert 专家数据平台，正是在这一背景下逐步搭建的一项长期性知识工程。

专家招募链接（邀请通道）

👉👉👉 半扩散工作室专属邀请通道

平台入口

https://xpert.bytedance.com/

Xpert 并非简单的数据众包平台，而更接近一种专家参与式的知识建构系统：通过不同学科专家的介入，为大模型提供结构化、可解释、可推演的高质量数据输入。

工作方式

• 工作地点灵活，完全远程

• 以项目与任务为单位，强调成果而非工时

报酬机制

• 基于专业深度与任务复杂度设定

• 更接近咨询式或研究式合作，而非流水线劳动

开放的学科版图

平台目前覆盖并持续扩展多个知识领域，包括但不限于：

• 社会科学

• 科研与学术研究

• 语言与翻译

• 写作与创作

• 法律

• 金融

• 教育

• 医疗与健康

半扩散工作室往期专家独家发布推荐｜World Model 事务所金融数据专家

半扩散工作室（semi◦diffusion） 是您链接全球顶尖远程职位的桥梁。我们摒弃低效筛选，只为您提供最高价值与最强灵活性的工作机会。无论身在何处，我们助您摆脱传统办公限制，在保持高收益的同时，享受掌控时间的绝对自由。

在算法试图解构一切的当下，稀缺的不是算力，而是行业里的“真理”。

这不仅仅是一份兼职，这是一次关于“认知液化”的实验。

百度文心大模型团队 正在寻找那些不愿被格子间束缚的头脑。我们需要你将深植于大脑的商业洞察与行业逻辑，转化为 AI 能够理解的高保真燃料。

关于 百度文心大模型 (ERNIE)

作为中国领先的产业级知识增强大模型，文心（ERNIE）具备跨模态、跨语言的深度语义理解与生成能力。它通过融合大规模知识图谱与海量数据，致力于成为千行百业的智能化技术底座，让机器像人一样思考、理解并服务于复杂的商业场景。

你的角色：商业与行研专家 (Business & Research Expert)

• 本质：这不是简单的标注，而是对机器的“高等教育”。你需要评估、生成或修正高阶商业分析与行业研究报告，确保 AI 不会在复杂的商业逻辑中产生幻觉。

• 客户：你的知识产出将直接服务于 百度 (Baidu) 的底层模型迭代。

理性而自由的契约

• 100% Remote：无论是巴厘岛的咖啡馆还是自家的沙发，地点由你定义。我们只看交付，不看考勤。

• 对价：100 - 500 CNY / Task。按任务结算，流程清晰。

Who fits?

我们不需要仅仅为了谋生的人，我们在寻找：

1. 行研/咨询科班：拥有扎实的商业分析、咨询或行业研究背景（MBB、四大或知名券商经历者优先）。3年以上工作经验。

2. 技术乐观派：对 AI 祛魅，但愿意亲手调教它。

3. 交付控：享受灵活的工作流，但对产出质量有洁癖。

Next Step

没有面试。如果你认可这种价值交换：

1. 请直接 Reply 本邮件。

2. 附上你的 CV 或 项目履历。

3. 通过筛选后，即刻进入 有偿试用 (Paid Work Trial) 环节。

P.S. 如果你身边也有这样一位拥有敏锐商业大脑且向往自由的朋友，欢迎将这封邮件转发给 Ta。

semi◦diffusion is your bridge to the world's top remote positions. We cut through the noise and deliver only the highest-value, most flexible opportunities. No matter where you are, we help you break free from the traditional office and take full control of your time while maintaining top-tier earnings.

Subscribe now

🚀 Today's Exclusive Opportunity: The "Financial Navigator" of the AI Data World

In an era where large AI models are reshaping every industry, high-quality domain-specific data has become the scarcest resource. Today, we're excited to bring you an exclusive expert role from World Model Agency.

About the Employer: World Model Lab (world-model.xyz)

World Model Lab is headquartered in Hong Kong and partners with leading enterprises in finance, healthcare, and architecture to build high-fidelity, domain-specific datasets. These datasets are the critical fuel for improving large AI models' performance in vertical industries.

💼 Role Details: Financial Data Expert

This is an opportunity to leverage your professional financial knowledge and directly participate in the training and optimization of cutting-edge AI models.

• Work Mode: Fully remote (100% Remote), location flexible.

• Clients: You will indirectly serve top domestic financial and tech giants. Current end clients in the financial sector include Baidu and Ant International.

• Compensation: 300 – 500 RMB per task (task-based pay, flexible and efficient).

🎯 Who Are We Looking For?

We need professionals with deep expertise in finance. Your work may involve evaluating, annotating, or generating high-quality financial data to help AI understand complex financial concepts and reasoning.

If you meet the following criteria, this is the perfect side hustle or freelance opportunity:

• Background in finance (academic or professional).

• Interest in AI technology and willingness to "teach the machines" with your domain expertise.

• A preference for flexible work with consistent, high-quality output.

📩 How to Apply

This is a direct entry point into the high-value AI data supply chain. No complex interview process required. We value your professional track record.

1. reply to this email.

2. Attach your CV and relevant experience or project portfolio.

💡 If you know anyone with a finance background who's interested in remote work, feel free to forward this email to them.

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我还记得第一次读到柏瑞尔·马卡姆（Beryl Markham）的自传《夜航西飞》（West With the Night）时的感动。她是一位真正的传奇——在那个女性被社会期望束缚的年代，她却在非洲大陆上空驾驶着飞机，以一种我们难以想象的视角，凝视着那片狂野、原始且充满生命力的土地。

（同步上传至“半扩散工作室”视频号，欢迎关注！）

下面这段文字，就出自这本书的第二章。它不仅仅是风景的描绘，更是一种对时空、生命以及人类文明的反思。当我们被困于屏幕、报表和无尽的日程时，这段话像一阵风，能将我们瞬间带回那个没有机器、没有钟表的原初世界。

在我目力所及的各个方向，有成百个地方会突然杨起一阵细小灰尘，滚过平原，然后再次消失。从高空看去，它们就无数精灵，一个个从被施了魔法的瓶子里逃脱，打算乘风而 去，继续完成它们蓄谋已久的邪恶计划，又或者是一项善举。 但当飞扬的尘土散去，我能看见一小群动物在朝各个方向奔跑，它们四处张望就是不知道抬头，努力想要逃避飞机的 轰鸣。 在马加迪与纳鲁克之间，我看见一团黄色的云雾就在飞正前下方形成，这团云紧贴着地面，当我接近的时候变成了阵摇曳的巨浪，所经之处，天空与地面草木消失无踪。 这团云雾的最外沿是一大群黑斑羚、牛羚与斑马，正在我机翼的投影下拼命奔跑。我盘旋、减速，一路降低高度直旋桨卷入尘土中，沙粒让我的鼻腔隐隐作痛。 这群动物移动时形成一块黄褐色、灰色、暗红色交大地毯，它不像牛群或羊群，因为它们都是野生动物，它上都带着荒野的印记，这片土地上的自由气息依旧属于自然而非人类。目睹上万头未经驯化、不带贸易烙印的动物，就如同第一次登上从未被征服过的山峰，发现一片人迹未至的从林，或是在新斧上看见第一点瑕疵。那时你才会领悟从小就听说的那些事：曾经，这个世界上没有机器、报纸、街道、钟表，而它依旧运转。 ”

—— 夜航西飞：第二章 黑水热患者死亡

👉👉👉 https://b70hpeyi134r.trickle.host

把“不会写情话”的焦虑，用产品抹平

为什么要做这个小工具？ 中国人每逢七夕。七夕到来，给不太习惯主动表达爱意，活着觉得“写不出那种会让 TA 心动的句子”。帮你到这儿啦。希望这个产品让你的表达更勇敢一点。

类似写情诗这种“合成成品”的任务，单纯依赖聊天框往往不够：用户要来回补充背景、搬运结果、再到排版里调整。为此我做了不同情诗风格和信纸模板，并支持导出情诗图，方便直接转发。

不同情诗风格

不同信纸模版

vibe coding的一些不成熟小心法

希望对在 vibe coding 路上的朋友有点参考。首先要有一个趁手的工具——Trickle（https://trickle.so/） 是我最近少见的让我兴奋的 AI 工具。

我最喜欢 Trickle 的 Magic Canvas。做网页时常会遇到“精准定位修改”的痛点：传统聊天式修改很难指向页面上的具体元素。Magic Canvas 允许你直接用鼠标选中要改的元素，给用户一个“锚点”，指哪打哪，定位与调整都更准。

目前的限制：对静态文本或元素支持更好；动态生成内容仍需要在对话框里修改。

• 它有点像 Midjourney 的 Region Edit（区域修改），思路上异曲同工。

• 和 AI 高效沟通很重要，这种“精准修改”的产品设计，能显著提升效率。

• 我也会借助无限画布把所有页面与迭代历史摊开，便于回看与对比。

和AI的沟通效率很重要，通过这种精准修改的产品设计很有效。

不过目前另外借助无限画布展示所有设计的网页和迭代历史。

Trickle 带来的基础能力

• PC、移动端自适应界面

• 生成精美背景图

一个小小的最佳实践

• 先用 Trickle（Lovable） 快速搭前端，用 mock 数据验证流程与观感；

• 后端再用 Cursor 搭接口，调用 DeepSeek 的大语言模型完成生成。

如果它能让你在关键时刻更敢说爱，那就是这次小工具最大的意义。欢迎试用并把你的故事或需求留言给我，我会继续迭代，把它打磨成更懂你的表达器。

参考资料

Trickle文档: https://help.trickle.so/UserGuides/PromptingGuides

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聊天界面：懒惰的产物

每个AI产品看起来都一摸一样，这个事实让我们感到恐惧。从ChatGPT到Claude, 再到Perplexity, 我们陷入了定式：侧边栏的历史记录、底部的输入框。一个大家心照不宣的真相是：这并非以用户为中心的设计哲学取得了共识，而更可能是设计者集体失职的体现。

从左到右依次为 Claude、Airtable、Perplexity、ChatGPT、Manus、DeepSeek 的应用页面截图

我们都陷入了所谓的“ChatGPT崇拜”，盲目地复制它表面的形式。这种“聊天框痴迷症”正在扼杀AI产品的想象力，我们构建的界面不但没有去适配用户的思维模式，反而在要求用户扭曲自己的习惯，去学习与一个笨拙的系统沟通。

无声的挫败：被“提示词工程”隔绝的半数用户

让我们想象一个具体场景：内容策略师Maya正试图用一款典型的AI写作工具来完善一篇博客大纲。三十分钟里，她在聊天框中输入请求，得到回应，复制到Google Docs，发现问题，再回到聊天框重新解释上下文，获得新回复，再手动整合……这个过程循环往复。“这就像和一个患有健忘症的人对话，”Maya无奈地抱怨，“我花在解释我想做什么上的时间，比实际动手做事的时间还多。”Maya的挫败感并非个例。

数据显示，用户将高达11%到27%的时间耗费在与AI的低效拉扯中，其中26%的问题最终未能解决。更令人警醒的是，Nielsen Norman Group的研究表明，由于存在固有的表达障碍，基于聊天的AI工具将近一半的潜在用户拒之门外。用户为了实现最基本的功能，被迫成为一名“提示词工程师”。这在UX设计领域是不可饶恕的原罪：我们设计的系统在失灵时，竟将责任归咎于用户。80%的企业AI项目在试点后便难以为继，根本原因正是用户接受度太低。那些看似精美的聊天界面，不仅效率低下，更是业务的“终结者”。

难道AI产品不应该像谷歌搜索一样简单有效吗？ 但是这其中存在一个本质的区别。Google Search就像问去餐厅的路。问一次，得到答案，就结束了。Google Search之所以有效，是因为搜索是一种简单的、无状态（stateless）的交互：查询、结果、完成。复杂性存在于算法中，而不是界面里。但AI产品需要反复调整，并依赖上下文且必须记录状态（stateful）。对话式界面无法完美支持。

对于像 Maya 这样的深度用户来说，聊天界面造成了巨大的认知负荷。这些用户花费时间去解释上下文、重新组织提示词，并手动将 AI 输出转移到真正的工作环境中。我们设计的界面，非但没有减轻，反而加重了用户的脑力负担。

新的设计模式和原则

Hoang Nguyen 提出了“混合工作空间（Hybrid Workspace）” 模型：

组件1: 工作环境（The Work Environment）

这是用户完成实际任务的主场，包括文档、画布、电子表格、代码编辑器、设计工具等。我们应该尊重、或者起码知晓人们已形成固有的工作流与思维模式，而不是强行取代。

组件 2：智能层（The Intelligent Layer）

这是将AI能力以感知上下文的方式，嵌入工作环境之中。它不是一个独立的聊天界面，而是一个能理解语境、维持状态、在不打断用户使用的前提下提供辅助的智能伙伴。可以从以下几个切入点来集成这个智能层：

• 内联建议

• 基于用户行为触发的上下文面板

• 对现有UI元素的渐进式增强

• 在后台默默工作的环境智能

  

  Sharang Sharma 的《Where should AI sit in your UI？》（https://uxdesign.cc/where-should-ai-sit-in-your-ui-1710a258390e）

  另外，还有如下设计细节能让用户更好将AI潜入工作流中：

• 允许用户对 AI 回复点“👍/👎”

• 提示词示例与模板

• 展示逐步推理过程

• 根据用户历史行为个性化界面

• 提示“AI 可能会出错”的免责声明

• 输出应始终高质量，必要时说“不知道”

• 帮助用户理解系统如何运作（在必要时），使其作出更好的决策

Vibe Coding：UI的设计机会

“从想法到 App，只需几秒钟。”——这是 Lovable 的宣传语，令人血脉喷张。

自今年初以来，所谓的 “AI 应用构建工具” 突然成为热门趋势。过去需要四周完成的工作，现在可能两周就搞定 —— 不久的将来，甚至可能只需要两天。

虽然“秒出 App”的愿景目前还没那么神奇，但我确实看到一些新的工作流开始浮现，比如：

两个新流程的例子

Xinran Ma 以第一个流程介绍了作者最近在尝试多喝水，突发奇想做了记录和可视化每日饮水的 Web App。他在 Claude 中写了这样的提示词（prompt）：

请创建一个互动式 Web 应用，用于帮助用户记录每日饮水量并可视化补水进度。

• 使用 HTML、CSS 和 JavaScript 编写

• 包含输入饮水量的表单、随目标完成而填充的进度条，以及每日统计数据

• 设计简洁直观，具有响应式设计

• 视觉风格应为清爽的蓝白色调，符合水和补水的主题

• 保证无障碍设计，使用对比清晰、易读的字体

• 用户操作后给予反馈（例如动画效果、达标后庆祝）

几分钟后，作者就收到了一个可运行的原型。这个过程总共耗时约五分钟 —— 几年前，这几乎是难以想象的效率。

AI 时代的设计工具应该长什么样？我们试图思考：如何更好地将“设计、代码与 AI”整合在一起？

新工具已经在探索这个方向例如 Subframe 就在使用可用于生产环境的预设 UI 组件（而不是不能用的 demo 代码），并集成了 AI 功能来生成不同设计方案。设计师可以将多个选项中的元素混合拼接，组成最终设计 —— 类似“AI生成+人类编排”的工作流。在设计圈里，“独角兽”通常指能写代码的设计师。而AI 工具的进步正在让更多人具备“独角兽能力”，也让不同角色的边界模糊。比如AI时代的新的独角兽：

• Lovable、Bolt、V0、Replit：让非程序员也能构建可用原型或产品

• ChatPRD：写更好的产品文档

• Galileo：生成高保真界面设计

虽然不同角色仍有专业深度，但 AI 让彼此的边界正在快速消融，使得产品形态超越对话框，AI产品设计的未来也将被重塑。

参考阅读

1. “AI’s Impact on Product Design” Ma Xinran https://medium.com/design-bootcamp/ais-impact-on-product-design-42e36c60c1c6

2. “Chatbot，是一种懒惰的产物” 纪源资本 https://mp.weixin.qq.com/s/bhn5QfRwHavL4UwP1XO-5Q

作者：Jason Wei

原文链接：https://www.jasonwei.net/blog/life-lessons-from-reinforcement-learning

过去一年，我痴迷于强化学习（Reinforcement Learning, RL），几乎每天醒着的时候都在思考它。没想到的是，这段经历无意中教会了我一个关于如何过自己人生的深刻道理。

在强化学习中，有一个核心观念叫“on-policy”（依照自身策略）：与其模仿他人成功的路径，不如采取自己的行动，并从环境反馈的奖励中学习。模仿学习（imitation learning）当然很有用，特别是在刚开始时用来“起步”。但一旦你能走出合理的轨迹，我们通常就避免继续模仿学习。因为要真正发挥模型自身的优势（这些优势往往不同于人类），最好的方式就是只从它自己的轨迹中学习。这一理念已经在实践中被验证，比如：与简单地用人类写下的思维链进行监督微调相比，用强化学习来训练语言模型解答数学题，效果通常更好。

在现实生活中也是类似的。我们一开始通过模仿学习来“冷启动自己”（比如上学），这很合理。但即使我已经从学校毕业，我依然习惯于研究他人是如何取得成功的，并试图模仿他们。有时候这样确实有效，但我渐渐意识到：我永远无法超越某个人的全部能力，因为他们是在发挥属于他们自己的独特优势，而那些优势我并不具备。举个例子：有的研究人员能比我更成功地跑 YOLO 实验，因为他们自己写了那套代码框架，我没有。再比如，一个足球球员能控球不丢，是因为他有我没有的身体对抗能力。

强化学习中“on-policy”的经验教训是：想要超越“老师”，你必须走自己的路，从环境中直接承受风险和获取回报。举两个我自己的例子—相比多数研究者，我更喜欢（1）大量阅读原始数据，和（2）做消融实验（译者注：消融实验是在一个复杂系统或模型中，系统性地移除或替换某个组件，以观察该组件对整体性能的影响，从而评估该部分的重要性、必要性或作用机制。）去理解系统中各个组件的影响。有一次，我在收集数据集时，花了几天认真读数据，并给每位人工标注员写了定制化的反馈，最终数据质量大幅提升，我对这个任务也获得了珍贵的理解。今年早些时候，我又花了一个月的时间回头把以前胡乱决定的实验逐一消融重跑。虽然投入的时间不算少，但我从中获得了对 RL 有哪些设计真的有效的独特认知。不仅如此，这种沉浸于自己热爱的工作也更加让我满足，我感觉我正在为自己和自己的研究开辟出一个更坚实、更有个性的方向。

简而言之，模仿是好的，甚至是必要的开始。但一旦你完成了“冷启动”，如果你想要超越老师，那你必须做 on-policy 的强化学习——走自己的路，拥抱自己的强项与短板，走属于你自己的轨迹。