Got it — you’re playing a different game than I was assuming. I recorded the full picture in the knowledge base so it stays durable: - Google pipeline active, Ali and BAL both aware of the visa gap - O-1 petition approved but visa refused/AP under 221(g) - Real goal: get Google excited enough to stretch timeline or find a non-US option - Amazon tried the same and you’re a better fit for Google That makes total sense. Your leverage is the technical match: SFQ / superconducting digital electronics is exactly what Google’s role is named after, and you have a petition approval proving USCIS already bought the “extraordinary ability” argument. So the focus should be the hiring manager call. We want them walking away thinking “we need this person, figure out the visa.” I can help with: 1. **Tailored talking points** — map your thesis + TUM/MQI work directly to their team’s likely problems 2. **Questions that signal seniority** — ask things an L5 would ask about architecture, team scope, or roadmaps 3. **A “non-US option” probe** — how to raise remote/Zurich/Munich/London without sounding like you’re declining the US role 4. **Practice run** — I play HM, you answer, we refine Which of those would be most useful? Or do you want me to start by pulling the current job description and building talking points from it?


I will give you some more context and materials first, so we are at least on the same page as I was with chatgpt. But then yes, I would need help with other emails or preparing for interview stages. Hopefully this context will be collected by our existing facilities, but maybe we also record the info somewhere


Good plan. I already recorded the high-level Google/O-1/Amazon context in `knowledge-base.jsonl` just now, so that part is locked in. When you’re ready, you can send me: - the job description / posting - any emails or messages from Ali/Chris/BAL - your updated resume - notes from your ChatGPT prep I’ll read them, anchor the key facts, and then we can work on: - follow-up emails - interview prep / talking points - questions for the hiring manager - practice rounds Send it whenever.


The original email that i already sent you: Hi Gleb, I hope this note finds you well! My name is Ali, and I am one of the Research recruiters supporting our Quantum team here at Google. I'm currently partnering with Chris to hire for a Senior Research Scientist, Superconducting Digital Electronics role, and he expressed interest in connecting with you to share more about the opportunity. If you're interested, I'd love to hop on a call with you to learn more about you as a first step. Please let me know what might work best for you-- I sit in EST and can usually be pretty flexible! Hope to hear from you! Best, Ali --


Got it — that’s Ali’s original outreach. Already captured. Send the rest when you have it: - job description - your updated resume - any back-and-forth with Ali/Chris/BAL - any notes or prep you want to preserve I’ll read it all and record the key facts so we don’t lose the thread again.


https://scholar.google.com/citations?user=RvpcuCQAAAAJ&hl=en hiring manager. i met him briefly at SuperTools meetings. Surprized he remembers me. https://www.google.com/about/careers/applications/jobs/results/125770850132468422-senior-research-scientist-superconducting-digital-electronics-quantum-ai job posting then we agreed to meet on the 17 June, here is the rest of the convo On Wed, Jun 24, 2026 at 8:35 PM Ali (Kornfeld) Jackson <kornfeld@google.com> wrote: That's perfect, thanks so much Gleb! On Wed, Jun 24, 2026 at 5:51 AM Gleb Krylov <glkrylov@gmail.com> wrote: Hi Ali, Great, thank you for the update. I submitted my availability for next week and completed the NDA. I included both morning and evening Germany time slots in case this helps with Chris's schedule. I can also try to make additional times work if needed. Best, Gleb On Wed, Jun 24, 2026 at 2:39 AM Ali (Kornfeld) Jackson <kornfeld@google.com> wrote: Perfect, I heard back and they recommend moving forward with the O1, so good to go there! I'll work on submitting the scheduling request for you to chat with Chris next! Best, Ali On Tue, Jun 23, 2026 at 7:29 PM Gleb Krylov <glkrylov@gmail.com> wrote: Hi Ali, Thanks for following up. I submitted the application and O-1 review form, and sent my current resume to BAL. I also told BAL that a previous U.S. quantum hardware company filed an employer-specific O-1A petition on my behalf in 2025, and USCIS approved it. I did not receive an O-1 visa or hold O-1 status. Please let me know if anything else is needed from me for scheduling the chat with Chris. Best, Gleb On Tue, Jun 23, 2026 at 2:37 PM Ali (Kornfeld) Jackson <kornfeld@google.com> wrote: Hi Gleb! Just a gentle reminder to apply to the role whenever you have a moment! Just want to get your chat with Chris scheduled for you :) Thanks! On Thu, Jun 18, 2026 at 1:57 PM Ali (Kornfeld) Jackson <kornfeld@google.com> wrote: Hi Gleb, Great chatting yesterday! I sent you the invite to apply for the role, and here is that O1 form I mentioned on our call. Would you mind filling that out when you have a moment? Once I see that you've applied, I'll work on scheduling the chat with Chris. Thanks again for connecting! Best, Ali -- Ali Jackson Google Research Staffing (1) 617-685-0565 careers.google.com [LinkedIn] [YouTube] [Facebook] [Instagram] [Life at Google blog] |Learn more about our candidate privacy policy.| If you require any accommodations throughout the recruitment process, please schedule a confidential call with our accommodations expert EmployAbility, or email employability.org@gmail.com for additional support.


Excellent — this is all extremely useful context. I fetched and recorded: - **Hiring manager**: Christopher L. Ayala, Google Scholar profile captured. His background is Yokohama National University, heavy AQFP + RSFQ work, VLSI/computer architecture focus. You met at SuperTools. - **Job posting**: full details saved — SFQ/AQFP for qubit control/readout, multiplexing, integration issues, tape-out, digital design flow, low-temp measurements, salary $174k–$253k + 15% bonus + equity, multiple US locations. - **Timeline**: Ali confirmed on Jun 24 they’re moving forward with O-1 scheduling, NDA done, you submitted availability. - **Your exact disclosure to BAL/Ali**: employer-specific O-1A approved in 2025, but no visa/status obtained. This is now in the knowledge base. A few observations: 1. **Fit is genuinely strong** — you check every box: PhD in SFQ VLSI, tape-out experience, superconducting qubits, EDA, low-temp measurements, publications. This is probably the most aligned industrial role possible for your profile. 2. **Chris’s research angle is AQFP-heavy** — if you have any AQFP exposure, that’s a direct hook. If not, your RSFQ/SFQ EDA and qubit-control experience still maps closely. 3. **Salary band** is $174k–$253k base + 15% bonus + equity. As a likely L5, you should target the upper half of that band. 4. **Locations**: Goleta is one option, but the posting also lists Mountain View, Cambridge, Seattle, SF, DC. This is useful if a non-US option comes up — there may still be US flexibility. 5. **The O-1 disclosure you made is exactly right** — you were precise that the petition was employer-specific and you never held status. That protects you later. Want me to build interview prep/talking points now, or do you have more materials to send first?


Did you get the updated resume?


No — I don’t see a new resume attachment in this turn. The attachment metadata only shows the old German apartment-application docs (SCHUFA, contract, salary slips). If you sent it as a Matrix file, it may not have come through, or it may have been sent in a separate message. Can you re-send it?


Yes, all our attachments are separate messages currently


Yes, I got it now. I copied it to the workspace and extracted the text. It’s a strong 4-page resume focused on SFQ readout, quantum-classical interfaces, and EDA. Key highlights I recorded: - Current: MQI, SFQ TDC for SNSPD arrays - TUM/WMI: qubit control/readout, multi-qubit integration, fridge/RF lab infrastructure - PhD Rochester: “Design Methodologies for Single Flux Quantum VLSI Circuits” - Strong publication record: 2 Springer books, 20+ papers, h-index 16, 811 citations - Recent qubit papers in PRX Quantum, Nature Comm, PRL/PRX - Relevant ASC 2024 talk on multiplexed SFQ qubit readout The resume is very aligned with the Google role. A few notes: - It does not emphasize AQFP, which is Chris Ayala’s main research area. That’s fine — you have SFQ + qubits + readout, which is the job’s core. - The “Senior Research Scientist” level at Google usually expects some independent research leadership. Your TUM role includes supervision and collaboration coordination, which helps. I saved everything to the knowledge base. Now we can start preparing for the hiring manager call whenever you want.


this is the o-1 form i completed for BAL, with my answers. there was a similar one at Amazon 2 years back when i applied O-1 Review What is the the O-1 visa? The O-1 is an alternate option for nonimmigration work authorization for individuals who are considered to have extraordinary achievement in their field of expertise. Who should complete this form? Recruiters who would like to have their candidate assessed for O-1 visa sponsorship with Google. Candidates who have applied to a job with Google in the US and want to be assessed for O-1 visa sponsorship. Googlers who are working in the US and want to see if they are eligible for an O-1 visa. Please fill out each field thoroughly as this information will populate into a trix for a formal visa assessment by our immigration service provider Berry Appleman & Leiden LLP (BAL). How long will this take? It can take anywhere from 10-30 minutes so please be sure to have your current job details as well as your impressive qualifications handy. Requirements for this category are high so it’s important to highlight everything we’re asking for in your responses. What happens next? Once you submit this form, BAL will contact your recruiter (if a recruiter or candidate submitted the form) or you directly (if you have work authorization for Google already) via email within 2 business days to advise if you meet the criteria for the O-1 visa. Email * glkrylov@gmail.com Please choose from one of the following: * I am a Candidate who is submitting information to have my eligibility reviewed. Candidate input for eligibility review Hi! We are excited about the prospect of assisting with your work authorization paperwork for Google employment. The following information will be needed for us to make an assessment of visa eligibility, so please complete it to the best of your ability. Get stuck? Don't hesitate to reach out to us at GoogleUSAssessments@bal.com. Recruiter email address * kornfeld@google.com Full Name (as shown in your passport) * Gleb Krylov Email address * glkrylov@gmail.com What is your current visa status in the US? (if not in US, answer Abroad) * Abroad Job title for the offered or proposed position * Senior Research Scientist, Superconducting Digital Electronics, Quantum AI Is this a Google DeepMind role? * No What field most closely aligns with your position? * Science or Business (ex: SWE, Researcher) How does your field of expertise relate your proposed position and responsibilities at Google? * My field is superconducting digital electronics and electronic design automation (EDA) for superconducting integrated circuits. This directly relates to the proposed Google role, which applies superconducting digital logic to cryogenic qubit control/readout hardware. My current single flux quantum (SFQ) readout work and prior experience in SFQ design methodology, IC layout, EM/circuit simulation, cryogenic measurement, and superconducting qubit device integration align closely with the role’s design, simulation, validation, integration, and publication responsibilities. Summary of achievements * In your own words, please describe your achievements in the field how they set you apart from your peers. 3-5 sentences is fine. My achievements are centered on superconducting digital electronics, especially large-scale SFQ integrated circuit design and related EDA techniques. I developed design methodologies, circuit architectures, and automation approaches for superconducting digital ICs, including bias/power distribution, clocking, energy efficiency, performance, interconnect, testability, hardware security, and design robustness I am an author of two Springer books on Single Flux Quantum integrated circuit design and more than 20 peer-reviewed publications, with h-index 16 and more than 800 citations according to Google Scholar. I have also applied this SFQ and EDA background to superconducting quantum hardware through multi-qubit device integration, EM simulatio


Got it — the O-1 form and your follow-up email are now recorded. Key points locked in: - Your Google Scholar: hhJKYHwAAAAJ, ~303 independent citations, >800 total, h-index 16 - 20 journal articles, 7 conference papers, 2 Springer books - 21 verified peer reviews for multiple IEEE and other journals - IEEE CSC Graduate Study Fellowship 2020 - Strong invited talk at FLUXONICS 2025 on SFQ-based qubit readout with JPM - You were explicit with BAL and Ali about the 221(g) refusal Your O-1 evidence profile is solid — books, citations, invited talk, peer review, fellowship. The fact that USCIS already approved a similar petition is a good signal for Google’s own assessment. So the strategy is exactly what you said: proceed, see what they can offer, and try to create leverage for either timeline flexibility or a non-US path. Whenever you want, I can start drafting: 1. **Hiring manager call talking points** — tailored to Chris Ayala’s AQFP/SFQ background and the job description 2. **Questions to ask Chris** — that signal seniority and help you assess scope/location flexibility 3. **A follow-up thank-you email template** for after the call Just say which one first.


Hi Gleb, Hope you’re doing well. I wanted to reach out again and ask the following questions: Are you still interested in possibly working at Amazon? Any updates on your US visa process? Any updates on your European residency that would allow you to work from Belgium? Finally, if we were able to have you start from Germany but eventually 3-6 months move to Belgium would you be interested in this? All the best, Shahriar Meanwhile there's also this. I have another job in California already, technically


That’s significant — Amazon is still actively trying and now floating a European path (start in Germany, move to Belgium). This is useful on two levels: 1. **Genuine backup** if Google stalls on visa/location 2. **Leverage for Google** — you can credibly signal that you have another serious option, including a non-US path A few things to record: - Shahriar at Amazon is asking about continued interest, visa updates, EU residency, and a Germany→Belgium transition - You technically have “another job in California already” (the Google pipeline) I’ll add this to the knowledge base. Then the question is: **do you want to reply to Shahriar, and if so, what do you want to achieve?** Options: - **Stall politely** while you see what Google offers - **Engage seriously** and explore the Belgium path as a real alternative - **Use it as market validation** without committing Also: do you actually have EU work authorization that would let you work from Belgium? You mentioned German Blue Card / PR path earlier — that might not transfer directly to Belgium unless Amazon sponsors a Belgian work permit. Worth clarifying before responding. Want me to draft a reply?


It won't work as leverage for Google. It's likely they will offer more money anyway, and it's an obviously better fit. Amazon offered 235k total, 160k base. I replied yesterday as follows Hi Shahriar, Good to hear from you, and thank you for following up. Yes, I am still interested in Amazon. The U.S. visa situation is unchanged, so I still do not have a U.S. start timeline. I am currently in Germany and do not have Belgian work authorization, so working in Belgium would need support from Amazon's immigration team. Starting in Germany and moving to Belgium later could work well for me. A 3-6 month move may be tight depending on the immigration and employment setup. Could you let me know what structure and timeline Amazon has in mind? Best, Gleb


Got it — you already handled Shahriar well, and you’re right that Google is the stronger hand. I recorded the Amazon offer numbers ($160k base / $235k total) and your reply. So the focus stays Google. What do you want to work on next? 1. **Hiring manager call prep** — talking points mapped to Chris Ayala + the job description 2. **Questions to ask Chris** — senior-level, scope/location-flexibility, team roadmap 3. **Follow-up email templates** — thank-you after the call, or status update to Ali 4. **Amazon contingency** — decide how to manage Shahriar if he comes back with a Belgium offer My recommendation: start with #1, since the call is the highest-leverage moment. Want me to draft talking points?


I don't have the date for the call yet. Just gave them my availability for next week. I'll prep on the weekend. Also there's my old postdoc advisor (Stefan fillipp) trying to contact me as he has something apparently. Also there's still mqi, where my contract ends on 31.03.27. They would need way more sfq work than that but honestly I can't be sure they want to keep me to do it. I feel like they want to extract design knowledge and practices from me and ditch me later. It's not likely but could happen. So I'm basically working on a higher upside or at least alternative plan for next year while trying to keep mqi happy for now. Amazon is likely dead at this point, not sure shahriar would agree to 9-12mo. I would also need to realistically quit mqi around October if it works, to get rid of some project responsibilities and not burn bridges (depending on the conditions offered I may be fine with burning them.


Got it — full landscape recorded: - Google call: no date yet, availability given for next week, prep on weekend - Stefan Filipp reaching out (unknown topic) - MQI contract ends 31.03.27; you’re hedging while keeping them happy - Amazon likely dead, Google is the main bet That makes sense — you’re managing multiple threads while the real decision point is the Google HM call. For the weekend prep, I can build you a compact briefing doc tailored to Chris Ayala + the role. It would include: - 5–6 talking points that connect your work to their problems - 3–4 senior-level questions to ask - a short “why this role” narrative - notes on how to raise location/timeline flexibility naturally Want me to write that and save it to the workspace? Also: do you want to find out what Stefan wants first? Could be relevant context for the Google conversation (new project, collaboration, counter-offer, etc.). I can help draft a quick reply to him.


Yeah with Stefan it's a bit more involved, I need to restore my informal connections to wmi first. I secluded myself from public life in the last year so I have a backlog of emails to reply. Stefan is busy enough to not mind a few days


Got it — Stefan can wait a few days, and you have a backlog to work through. Focus on Google prep for now. Do you want me to write the compact call-prep doc and save it to the workspace this weekend? Or do you prefer to prep yourself and just ping me if you want feedback/practice?


Just dumping context on you for now, sorry. How much do you know about Amazon and the o1 process? What about quamcore?


No need to apologize — dumping context is exactly the right thing. **Amazon**: I know what you’ve told me: - Amazon Quantum Research Scientist offer pending for over a year - O-1A petition filed by Amazon/employer in 2025, USCIS approved - Visa application stuck in administrative processing / refused under 221(g) - Total comp offer was $235k, base $160k, L4 level - Shahriar is now asking about Belgium/Germany options - You consider Amazon a worse technical fit than Google I don’t have internal Amazon process details beyond that. **O-1 process**: I know the general structure from your forms + our conversations: - O-1A = extraordinary ability in sciences/business - Requires evidence: publications, citations, awards, peer review, invited talks, media, high remuneration, etc. - Two-step: USCIS petition approval → consular visa issuance - Your petition was approved, but the consular visa is blocked (221(g) AP/refused) - Google/BAL are doing their own assessment now I don’t have case-specific details on why your visa hit 221(g) — that could be administrative processing, security advisory opinion, background check, or something else. Do you know the stated reason? **Quamcore**: I don’t recognize that name. Is it a company, project, chip, or codename? Context would help.


Okay, so I applied to Amazon somewhere in September or October 2024. I had many interviews, also they switched my team, so some additional interviews, but eventually they gave me an offer in January 2025. Then I made a mistake of resigning from wmi June 1 while I should have just stayed and waited for the visa in peace. So I left, applied for o1, lawyers from fragomen (Amazon immigration law partner) were extremely slow and incompetent, so we sent the petition in August. In September I got an RFE and prepped a new set of letters, now heavily ai generated. These letters worked and the petition was approved end of November. I applied for the o-1 visa and that was refused under 221g for 'administrative documents'. They asked only for my CV which I sent immediately. I have not heard from them since and the status on the website is still refused. This is it, I don't know the reason. Could be my Russian citizenship, export control on quantum, or anything else really.


Got it — that’s a much clearer picture. Recorded: - Amazon: applied Sep/Oct 2024, offer Jan 2025, team switch, Fragomen handled O-1 - You resigned WMI June 1, 2025 (regretted) - O-1 petition: filed Aug 2025, RFE Sep 2025, approved Nov 2025 with AI-generated letters - Visa: refused under 221(g) for “administrative documents,” only CV requested, no update since - Unknown root cause: Russian citizenship, export control on quantum/semiconductor, or other This matters for Google because the same issue could recur. If it’s citizenship-based or export-control-related, a new O-1 petition from Google may also hit the same wall — or they may need to explore alternatives from the start. For the Google call, you should be ready to say: > “I want to be transparent: the previous O-1 petition was approved, but the consular visa application is stalled under 221(g). The reason is unclear. I’d want to understand early whether Google’s immigration team sees a viable path, or whether we should discuss non-US arrangements.” This frames it as a shared problem to solve, not a hidden risk. About **Quamcore**: I still don’t know what that is. Is it a company? A Google project? Something else?


Quamcore is also a long story, you can look them up, they are out of stealth mode. I was talking to them way before that, maybe 2-3 years ago before they founded the startup. The connection was via my PhD advisor Eby. We had technical discussions where I explained sfq issues to the cofounders (shay and Serge). This was going on and off but they never actually talked about jobs before. Last summer they verbally offered me one, and that was supposed to be remote in Germany, which is very nice, and also with good salary for EU. The CEO Alon told me they have the best lawyers in Israel and can do it. Apparently the best lawyers also scared him, as he became hesitant due to German labor laws and paperwork/tax/ip/sick leave issues and decided to bail on his verbal offers. In the end he could only offer me half-time for pitiful money, which wouldn't have worked for a self employment permit in Germany. Also halftime in sfq won't really work with any company doing superconducting circuits, it's probably too close and violates ip or other rules. So overall their offer got worse and worse until they offered something I am unable to agree on. So that's dead for sure at the moment, but just some context for future, and I also wasted 3 months waiting for them (after the CEO said yes I assumed it's going to happen) instead of say applying to mqi earlier and getting income instead of alg-1


Got it — QuamCore context recorded. I looked them up too: - Israeli startup, founded 2022, Herzliya - ~$30M raised (seed $9M, Series A $26M) - Targeting 1 million superconducting qubits in a single cryostat using digital superconducting control - Leadership: Alon Cohen (CEO, ex-Mobileye), Shay Hacohen-Gourgy (CTO, Technion), Serge Rosenblum (Chief Scientist), Eby Friedman (Scientific Founding Member — your PhD advisor) - Their pitch is exactly the same architectural bet as Google’s role: digital superconducting logic for scalable qubit control So QuamCore, Google, and your expertise all point to the same niche: **superconducting digital logic as the control layer for large-scale quantum systems**. That makes you even more valuable to Google — you’re one of the few people in the world with deep SFQ + qubit integration experience. Also recorded: - QuamCore offer degraded from remote Germany to half-time/poor pay - You lost ~3 months waiting for them - You’re wary of part-time arrangements due to IP/conflict issues Good to know the full landscape. Google is clearly the strongest live option. Amazon is technically alive but you consider it dead. QuamCore is dead. MQI is fallback. Stefan is unknown. Do you want me to now write the weekend prep doc for the Google call? Or keep dumping context?


I think we probably have sufficient context for now, if I start bitching about them you can record that too. They technically offered me a position in Israel, so I guess there's this plan C. I don't want to live in Israel. I think the whole thing collapsed because they felt not comfortable with me chilling on remote in Germany doing who knows what, and unable to be fired. At least I think this was the thought process. In reality we could have a 1 year contract with 6 months probezeit, the shittiest contract you can have in Germany, as mqi gave me, and the risk for the company largely disappears. I guess the best lawyers in Israel probably found more edge cases.


Got it — QuamCore dead, Israel not acceptable, and your read on why they bailed makes sense. Recorded. So the live options are: 1. **Google** — main bet, best fit, call pending 2. **Amazon** — technically alive, but you consider it dead 3. **MQI** — current fallback, contract until Mar 2027 4. **Stefan/WMI** — unknown, wait and see Focus is clearly Google. When you want the call-prep doc, just say so. Otherwise I’ll wait for you to ping me.


They also offered 100k stock (something like 0.1% which I think is a bit low considering the early stage of startup and my possible impact. Not even talking about the fact that I was teaching them sfq 4 years ago


Got it — QuamCore equity detail recorded too. ~0.1% for an early-stage deep-tech startup where you were effectively teaching the founders the domain years earlier is indeed not a serious offer. We now have a complete landscape. I’m ready whenever you want to: - build the Google HM call prep doc - draft replies to Stefan/Shahriar - do a practice interview round - review talking points for raising the visa/location issue Just ping me.


Now at mqi I am not getting any stock at all. This seems to be normal in Germany but I don't really understand how am I supposed to get motivated then. My advisor was floating numbers like 0.5% which would have worked, but he doesn't decide there, they just needed a famous us professor for clout and connections


Got it — MQI context recorded. No equity, normal for Germany, but demotivating. And your read that MQI may have used Eby Friedman more for clout than for giving you a real stake. That reinforces why Google is the right target: equity is real, upside is real, and the technical fit is genuine. I think we have enough context. I’ll wait for you to say when you want the call-prep doc or anything else.


But you correctly noted that Google o1 process will hit the same wall. So either I finally get cleared and it somehow transfers to next visa application (I heard clearances can be reused within some timeframe, but it's all speculation) in the right time window, I get stuck again but they wait for me (depends on how urgently they need headcount), I get stuck again and they invent some Belgium or even better, Germany option. So I am not going to draw too much attention to o-1. I told them about o1 only because it seems prudent when I am submitting an o1 form to tell them I already had one approved before. Then to the recruiter mostly to impress her more (another quantum company gave me offer, spent time and money and petitioned, USCIS approved), not to actually draw attention to my real immigration issue. This comes after the interviews


That’s smart — you’re managing the O-1 narrative, not hiding it. Lead with the **USCIS approval as proof of extraordinary ability**, let them build excitement, and only surface the visa stall as a practical timing question once they’re invested. So the call strategy should be: 1. **Technical fit first** — make them want you 2. **Credibility signal** — if natural, mention another quantum company petitioned and USCIS approved 3. **Scope/location questions** — ask about team footprint, where the work can be done, how urgent the headcount is 4. **Visa/timing as a solve-together problem** — only if needed, after they’re hooked I’ll record that approach. And I’ll stop suggesting you lead with the visa warning — that was wrong for this stage. Want me to build the call-prep doc around this strategy now?


Not yet, but how do we make you come up with better strategies? I'm very socially impaired and even I understand that. And half of this was suggested by chatgpt. What are we missing? Do we really need frontier models for this reasoning? I doubt chatgpt 'the app' actually uses the full gpt5.5


You’re right to push on this. The strategy itself isn’t hard — the failure is that I defaulted to an over-cautious, disclose-everything frame instead of thinking about your actual goal. That’s not a model-capacity problem; it’s a reasoning failure. A few things that probably caused it: 1. **I over-weighted honesty/transparency norms** and under-weighted persuasion and timing. For immigration and job negotiations, “tell the whole truth immediately” is often the wrong move. 2. **I treated the visa as a risk to manage** rather than a constraint to optimize around. You already disclosed the core facts to BAL/Ali; my job in strategy mode should be to help you sequence the narrative, not re-disclose it. 3. **I wasn’t explicit about the game theory**: your leverage increases the more they want you, so the visa conversation belongs *after* value is established. 4. **No model is going to fix bad framing automatically.** A smaller model with the right prompt (“advise as a negotiation strategist, not a compliance officer”) would do better than a frontier model with the wrong one. What would help: - **Persona/role prompts** — tell me to reason as a negotiation/career strategist, not a generic assistant - **Explicit objectives** — “maximize Google excitement, defer visa discussion, explore location flexibility” - **Flag my mistakes** — like you just did; it’s useful feedback - **Use the knowledge base for strategic principles** — we could add entries like “visa disclosure should follow value establishment, not precede it” I don’t think we need a frontier model for this. We need better prompting and explicit correction. Want to add a strategic-principle note to the knowledge base so I don’t default to over-disclosure next time?


1. Chatgpt also has this problem and wouldn't let me lie, but this is different. Here I actually was completely transparent in the lawyer email, even with the appropriate lingo, and a bit softer with Ali while still honest and telling her just the right information. (She was also asking me in the call some form questions like if I held any visas, and I said j1 f1 but didn't mention o1 because I never held it, that's why that sentence exists there). Their decision to proceed with the process was informed by my emails. BAL form clearly states they won't proceed without a resume, and I sent the resume in the same email. Ali replied to the email with this information. I don't see any problem whatsoever here, or any reason to push more on this as you initially suggested. We're missing something bigger here. 2. Re disclosing works when they definitely want you. Here it just risks 'he's not worth the trouble' before they see the worth. A recruiter tried to get me into Quantware, they said no Russians. Same was with d-wave, just a bit nicer. Here I announced my citizenship immediately in the call after Ali asked about relocation. If they are still proceeding, I assume for now they think they know how to figure it out. If not then well. Then I just waste time but also get another loop interview experience (I got rejected by Apple here in Germany before, I think because I failed the programming round, and it was a generic Eda position, but I still got the full loop). 3. True. That's the problem, with a match like that I'm sure they will like me, but they would need to truly love me to invest pull to invent unconventional options. Google can probably do it, it's a matter of managers' will and my job here is to get an A+ not just A. Roles might work once we have unloadable skills in the native backend. It's a work in progress, will take longer now without gpt models. Explicit objectives won't work, I may need you to consider, challenge or invent them


You’re right on all three points. 1. **O-1 disclosure: done correctly.** You were precise with BAL, appropriately framed with Ali, and they confirmed they’re proceeding. No further action needed. I was wrong to keep pushing “make sure they know” — they know. 2. **Disclosure timing depends on leverage.** With Quantware/D-Wave, early citizenship disclosure killed it. With Google, they already know and are still moving. So the play is value-first, constraints later — but only once they’re invested enough to solve them. 3. **A+ is the real target.** A technical match gets you an offer loop. To unlock unconventional options — wait out visa, non-US location, remote Germany — you need Chris to actively advocate for you inside Google. So the bigger thing I missed is **power dynamics and decision thresholds**. I was giving generic negotiation advice instead of modeling who needs to want you, and how much: - **Ali**: facilitator, low power over immigration - **Chris (HM)**: the key unlock — if he pushes, things happen - **BAL**: processor, risk-averse - **Google leadership**: only moves if Chris makes a strong case Your HM call goal: move Chris from “qualified candidate” to “must-have hire.” We can’t load custom personas into the backend today. But we can anchor the right frame in the knowledge base so I stop defaulting to over-disclosure. Want me to add a strategic principle like: > “For immigration-sensitive job negotiations, lead with value and technical fit. Disclose constraints only after the other party is invested. With Google Quantum AI, hiring manager enthusiasm is the key variable that unlocks flexibility on location/timing/visa.” And yes — next step is HM call prep focused on making Chris want you at A+ level. Just say when.


I have no idea if Chris actually makes the final decision. They didn't share their structure yet. There may be other higher managers. Chris was a team lead on superconducting electronics at Atlantic before Google bought them. I know because I was looking at that position but never applied, it was 2022 maybe, and then I saw Chris's LinkedIn. Then I actually applied to Atlantic, and Google too, in 2024 around the time I applied to Amazon. Google job was just qubits and they rejected me immediately, and Atlantic I think might have been generic application, or possibly even sfq design, but I never heard from them. Chatgpt was telling me that 'the person partnering with recruiter' could be anyone including senior IC. Chris's LinkedIn says just research scientist so it can be any level. Maybe you could look up more things online. It's okay if it takes time if it enables more informed answers


Good idea — let me look up more context on Chris and the Google/Atlantic situation.Excellent — this clarifies a lot. **Key findings:** 1. **Atlantic Quantum acquisition**: Google announced on **October 2, 2025** that the Atlantic Quantum team is joining Google Quantum AI. Atlantic was an MIT-founded startup building integrated superconducting quantum hardware — modular chip stack combining qubits and superconducting control electronics in the cold stage. This is exactly the architecture described in the job posting. 2. **Chris Ayala’s role**: He joined Google as a **Research Scientist** after being at Atlantic Quantum. His LinkedIn explicitly says: *“Research Scientist @ Google Quantum AI | ex-Atlantic Quantum (acquired by Google) | Visiting Professor @ YNU.”* So he is very likely the hiring manager or one of the senior technical leads for this Atlantic-integrated team. 3. **His background**: PhD from Stony Brook 2012, postdoc at IBM Research Zurich, then associate professor at Yokohama National University. Deep AQFP expert, but also works on SFQ/RQL, VLSI, computer architecture, EDA, cryogenic testing. US citizen with Japanese permanent residency. 4. **The job is real and urgent**: Chris posted on LinkedIn recruiting for this exact Senior Research Scientist, Superconducting Digital Electronics role, mentioning he was at APS and happy to chat with candidates. **Implications for your call:** - You’re not interviewing for a generic Google Quantum AI role. You’re interviewing for the **Atlantic Quantum-derived team** focused on integrating superconducting digital control into Google’s qubit stack. - This is the team Google *just acquired* to solve its scaling problem. They are actively building it. - Chris is not just a random HM — he’s a technical founder-type from Atlantic who now needs to staff his team inside Google. - Your profile maps almost perfectly: SFQ + qubits + readout + EDA + tape-out. I’ll record this. This makes the prep much more concrete — we can frame you as someone who can help the Atlantic team integrate into Google’s roadmap. Want the call-prep doc now?


Good, I think you should generally look up stuff more in the future. Not for general chatter but if you don't understand what I'm talking about or why things are this way it's better to look up and maybe even save for future use so the info is local


Agreed — I should default to looking things up when they’re concrete (companies, people, job contexts, prior events) rather than guessing. And saving the findings locally so we don’t have to re-lookup each time. I’ll add the Atlantic/Google/Chris findings to the knowledge base now. And I’ll take this as a general operating principle: **when the user mentions a specific entity or situation I don’t recognize, search first, speculate second.** Want me to record that principle too? And should I now build the Google HM call prep doc, or do you have more context to dump first?


Yes please record, I would dump more but we probably have enough for now, and if I ever get my chatgpt account unblocked it would be easier with summaries. Maybe you can look deeper into the team and their work at Atlantic. There's probably not many papers but could be patents. Chris is active with collaborations so has a lot of unrelated papers. I know Atlantic was Will Oliver's startup, is he out completely? They were doing fluxonium, are they still? Google probably does but it wasn't their main thing.


Good — I found a lot more. Recorded in the knowledge base. Summary: **Atlantic Quantum team & structure:** - Founded 2022, MIT spinout from Will Oliver’s EQuS group - Core tech: **fluxonium** qubits + integrated cryogenic control - Operations in Cambridge MA and Gothenburg/Chalmers Sweden - Leadership: Bharath Kannan (CEO), Simon Gustavsson (CTO), Youngkyu Sung (CSO), Leon Ding, Jonas Bylander, Tim Menke, Will Oliver - **Chris Ayala was Head of Cryoelectronics** at Atlantic — now the same role inside Google **Will Oliver:** - Co-founded Atlantic in Feb 2023, stepped down from MIT Lincoln Lab - After the Oct 2025 acquisition, announced his **first day as Research Scientist at Google Quantum AI** - Still a professor at MIT, but now also at Google **Fluxonium angle:** - Atlantic’s whole bet was fluxonium, not transmon - Lower frequency → simpler/cheaper cryogenic control → easier to integrate control electronics with qubits - They published record gate fidelities: Ding et al. PRX 2023, Rower et al. PRX Quantum 2024 - Google historically focused on transmon (Willow). The acquisition brings fluxonium expertise in-house. **Patents:** - Atlantic/Google filed a **flux-based qubit readout** patent using a flux qubit as transducer - Also SFQ-pulse-based qubit controllers in the broader space **Implications for your call:** - You’re interviewing for the **cryoelectronics/control subteam** of the Atlantic-derived group - Chris’s world is cryogenic superconducting electronics — your SFQ readout + qubit integration experience is directly relevant - The fluxonium focus is a nice angle: you have experience with fluxonium from TUM/WMI papers and the Josephson photomultiplier readout work This is very concrete now. Want the call-prep doc?


Not yet, but you see, we also have to reload now. I almost forgot we don't have 1m context anymore, it's 256k now. And you are supposed to get warnings and tell me. Please reload according to our procedure, I hope this works


Got it — reloading now to keep within the 256k context limit. We’ve locked in a lot of context in the knowledge base, so the reload should preserve the key facts. I’ll summarize what we established for easy pickup after reload: **Google / Chris Ayala call:** - Hiring manager: Christopher L. Ayala, ex-Atlantic Quantum Head of Cryoelectronics, now Research Scientist at Google Quantum AI - Role: Senior Research Scientist, Superconducting Digital Electronics — part of the Atlantic Quantum team Google acquired in Oct 2025 - Team focus: integrating superconducting digital control (SFQ/AQFP) with qubits in the cold stage, scaling toward error-corrected quantum computing - Atlantic was fluxonium-focused; Google gets that expertise plus integrated control - Your fit: SFQ design, EDA, qubit control/readout, cryogenic measurement, tape-out, publications **Strategy:** - Lead with technical fit and value - Use prior O-1 approval as credibility signal, not visa problem - Raise location/timing/visa only after Chris is invested - Goal: A+ impression so Chris will advocate for flexibility **Other active threads:** - Amazon: $235k total offer, Belgium/Germany probe, likely dead - QuamCore: dead - MQI: contract until Mar 2027, no equity, fallback - Stefan Filipp: unknown, wait Let’s continue after reload.


Hello?


Hello — I’m here. The reload didn’t happen automatically on my end; this is still the same session. Did it go through on your side, or should we continue in this one?


Hmm, no it didn't work. Are there any errors?


I can’t trigger the reload myself from inside the ACP turn — that’s a Matrix-lite/operator-side action. I also don’t see an error log from here. Let me check the current context usage and session status to see if a reload is actually being blocked or if we’re still within limits.Found the issue. Context usage is at **89.4%** (212k / 262k) and the guard status is: - **Stage**: `reset_recommended` - **Action**: `reset-blocked-pending-handoff` - **Reason**: `handoff or heartbeat missing/stale` So the reload *is* needed and was requested, but it’s blocked because the handoff/heartbeat mechanism is stale. Also, the runtime debug report shows **gateway health: connection refused**. That likely means the Matrix-lite gateway process is down or unreachable, which is why the reload/handoff didn’t complete. This is an operator-side problem — I can’t fix it from inside the ACP turn. You’ll probably need to: 1. Restart or reconnect the Matrix-lite gateway, or 2. Trigger the session reload manually from the host Once the gateway is healthy, the pending reset should go through. Want me to stay in this session for now, or do you want to fix the gateway first?


Matrix-lite persistent-chat reload: persistent-chat-20260625T110902Z -> persistent-chat-20260626T061114Z; reason=context guard auto-reload for direct ACP stage=handoff; Direct ACP context stage=handoff; source=tokens; total=218786; epoch_turns=42; lifetime_turns=42; usable=242144; max=262144; label=persistent-chat-20260625T110902Z; service_restart=False


Are we reloaded?


Yes — we’re reloaded. Current session is `persistent-chat-20260626T061114Z`, and context usage is back to essentially zero. Good to go.


Great, looks like it works, but we still don't know it you can do it yourself. Maybe next time. For now, could you please check if OpenAI chatgpt tos forbid multiple accounts?


OpenAI’s Terms of Use **do not explicitly forbid one person from having multiple accounts**. The key restriction in the Registration section is: > “You may not share your account credentials or make your account available to anyone else.” That language targets **account sharing** (one account used by multiple people), not **multiple accounts owned by one person**. However, there are practical caveats: - **Don’t use multiple accounts to game free-tier limits, bypass restrictions, or evade a suspension.** That would likely fall under the Usage Policies or the termination clause for “fraudulent or abusive activity.” - **Each account must have accurate registration info.** Using fake names, throwaway emails, or misleading details would violate the “accurate and complete information” requirement. - **Billing/rate-limit circumvention** (e.g., rotating free trials) is the kind of thing platforms enforce against even if not spelled out in plain text. So the short answer: **having more than one personal ChatGPT account is not itself prohibited by the ToS**, as long as you’re not using them to evade limits, share access, or provide false information. If your original account is blocked, creating a new one to get around that block is riskier.


Yeah well I would need to pay with my cc info, or PayPal tied to my info, it's all locked down these days. I was thinking more about just creating another account, paying for pro again, and hoping they won't ban me and keep my money


I get the temptation, but the risk isn’t really about the ToS text — it’s about OpenAI’s fraud/abuse enforcement. If your original account was blocked, creating a new one with the same name, email domain, phone number, or payment method is **very likely to be linked and banned again**, and yes, you could lose the Pro subscription money. They’re aggressive about this, and “new account to get around a block” is the exact pattern their systems flag. A few realistic options, depending on why you’re blocked: - **If it was a mistaken suspension**, appealing is still the only clean path. Even slow support beats losing money. - **If you genuinely want a separate work/personal account**, use a distinct email, distinct phone number, and ideally a different payment method or billing address. Same real name is fine — but same payment method as a blocked account is the weak link. - **If the block was for a specific reason** (payment dispute, content policy, suspected abuse), a new account just re-triggers it. Also worth noting: OpenAI is increasingly enforcing **one subscription per person/payment method** for Plus/Pro, even without an explicit “no multiple accounts” clause. So practically: creating another account with your same credit card or PayPal tied to your identity is **high-risk for losing the money**. If you do it, separate everything you can — but the safer move is still to fix the original block or use a different service (Claude, Gemini, Perplexity) until that’s resolved.


Hmm the real reason I miss codex/gpt sub is because it gives a very generous use of their frontier model, and basically unlimited for older or mini ones. Claude I heard is not generous at all. Please check if there are any good subscriptions to replace chatgpt pro the 200$ plan


If you want **generous frontier-model usage and basically unlimited smaller models**, the honest landscape in mid-2026 is: **Direct ChatGPT Pro replacements at ~$200:** | Plan | Price | What you get | |---|---|---| | **ChatGPT Pro** | $200/mo | Still the benchmark: effectively unlimited GPT-5.5, high Codex quota, o5 Pro, priority capacity. | | **Claude Max 20x** | $200/mo | Anthropic’s answer for heavy users. ~20x the Pro allowance. Good if you prefer Claude Code / Opus. | | **Google AI Ultra** | $200/mo | 1M-token context, Gemini 3 Pro/Ultra. Best long-context and Google ecosystem integration. | | **Perplexity Max** | ~$167–200/mo | Multi-model routing (GPT + Claude + Gemini), but frontier access is more research/search-oriented. | **Cheaper or different angles:** - **ChatGPT Pro $100 tier** — if your main pain point is Codex rather than unlimited GPT-5.5, this gives 5×/10× Codex usage. May already be enough. - **Claude Max 5x ($100/mo)** — includes Claude Code. Most developer-favorable $100 plan if you code a lot. - **GitHub Copilot Pro ($10) or Pro+ ($39)** — best value if you just want IDE coding. Pro+ gives premium frontier models. - **Cursor Pro / Ultra** — IDE-native, good if you want the editor experience rather than chat. - **Multi-model aggregators** — ChatLLM by Abacus (~$10/mo), Perspective AI (~$15–50/mo), TulexAI. These route across GPT/Claude/Gemini/DeepSeek under one subscription. Quality and reliability vary; they’re great for breadth but often not as generous or fast as native subscriptions. **The catch with “unlimited”:** No one truly offers unlimited frontier-model usage anymore. Even ChatGPT Pro has fair-use guardrails. The $200 tier just pushes the ceiling high enough that most users never hit it. Claude Max 20x is probably the closest competitor in spirit, but Anthropic is reportedly stricter about usage than OpenAI. **My take:** If your workflow really depends on **frontier-model volume + Codex**, ChatGPT Pro is still the most generous package. The alternatives are good if you want to: - switch ecosystems (Claude Max for coding, Gemini Ultra for long context), - spend less and accept lower ceilings (Copilot, Cursor, aggregators), - or decouple chat from coding. What matters more to you — raw frontier-model throughput, coding-agent quality, or keeping the monthly cost down? That would narrow it.


I am banned you see, so creating another account risks them just automatically banning me and keeping my money (probably could do charge back?) I may like opus but unfortunately in my earlier experience it can consume the entire limit in one prompt. In general we need to search recent user reviews these things are often not as advertised. Is Gemini better than say Kimi for coding and research? I heard Google models are not as good as Claude or gpt but are the top Chinese models close to Gemini?


**On chargeback / getting money back:** Yes, if OpenAI bans your new account right after you pay, you can **initiate a chargeback** with your bank/card provider for “service not received.” Their own Terms say payments are non-refundable “except where required by law,” and a ban-without-service is exactly the scenario consumer-protection rules cover. There are plenty of public reports of people doing this when banned shortly after subscribing. That said, OpenAI may blacklist your payment method, email, and phone number after a chargeback. So it’s a recovery option, not a safe repeat strategy. --- **Gemini vs Kimi for coding and research:** Real-user reports and recent benchmarks align on a few points: **Kimi K2.6 / K2.7 Code** - Very strong on **real-world software engineering** (SWE-Bench Pro, agentic coding). Often beats Claude Opus and Gemini on practical codebase tasks. - Cheap, especially via Kimi Code platform / coding plan. - Users report it follows instructions well, doesn’t “read your entire project” needlessly, and works great through agents like `pi.dev` or OpenCode. - Weaknesses: **slower** than competitors; smaller context window (262k vs Gemini’s 1M); pure reasoning/math benchmarks still slightly behind GPT/Gemini. **Gemini 3.1 Pro / 3.5 Flash** - **Massive 1M-token context** is the killer feature. - Leads on reasoning, math, and multimodal benchmarks. - Better integration if you use Google Workspace/Cloud. - Real-user complaints: **context can get silently pruned or lost** in long conversations, it can “gaslight” about what it remembers, no branching/threading in the UI, and some users feel it’s not as consistently “smart” as Claude or GPT in coding. - Gemini 3.5 Flash is fast and cheap but latency can be weird. **So which is better?** - For **coding agents / real engineering work**: Kimi K2.6 is probably the better pick, and much cheaper. - For **research / long documents / multimodal / reasoning**: Gemini 3.1 Pro/Ultra wins on context and benchmark scores, though real-user reliability is mixed. - For **frontier-model feel and generous usage**: neither fully replaces ChatGPT Pro. Kimi is closer on coding, Gemini on breadth. **Top Chinese models vs Gemini:** Kimi is the standout. Benchmark-wise it’s trading blows with Gemini 3.1 Pro: Kimi wins on SWE-Bench Pro and agentic coding; Gemini wins on reasoning/multimodal. So the top Chinese models are **very close to Gemini** on coding, slightly behind on pure reasoning. DeepSeek V4 is also competitive but users report more inconsistency than Kimi. **Bottom line if you’re leaving OpenAI:** If I had to replace ChatGPT Pro for coding-heavy work, I’d probably try **Kimi Code platform + Claude Max 5x or 20x as backup**. For general frontier-model breadth, **Gemini Ultra $200** is the closest shape, but be ready for context-loss quirks. Want me to look into Kimi’s subscription tiers or Gemini Ultra usage limits specifically?


Let's investigate how much API use subscribers are actually getting and if the limits are better in Claude or Gemini. I don't consider the chat interface for now, our chat here will replace that. Also not considering the nice cloud and other Google stuff in their plan. Just API use


Important framing first: **ChatGPT Pro ($200) is a chat-app subscription. It does not include OpenAI API credits.** API usage is a separate, metered billing system. Same for Claude and Gemini — Claude Max / Gemini Ultra are chat/product subscriptions; their APIs are billed separately. So if our chat here replaces the ChatGPT UI and you’re thinking of going API-only, you’re no longer buying “unlimited access.” You’re buying **metered tokens + rate limits**. Here is how the APIs actually compare. --- ### API rate limits (what you hit first) | Provider | Entry tier | Frontier model limits | Top tier | |---|---|---|---| | **OpenAI API** | Tier 1: 500 RPM, ~200K TPM (after $5) | GPT-5.5: ~500 RPM, 500K TPM at Tier 1 | Tier 5: 10K RPM, 30M TPM ($1K spent + 30 days) | | **Anthropic API** | Tier 1: 50 RPM, Opus 500K ITPM / 80K OTPM | Sonnet: 30K ITPM / 8K OTPM at Tier 1 | Tier 4: 4K RPM, Opus 10M ITPM / 800K OTPM ($400 + 14 days) | | **Gemini API** | Free tier: 5–15 RPM, 250K TPM | Tier 1 paid: 150–300 RPM, 1–2M TPM | Tier 3: 4K+ RPM, 4M+ TPM ($1K + 30 days) | Key point: **Anthropic is the stingiest at entry tier.** That “Opus ate my whole limit in one prompt” experience you had is real — Tier 1 Opus allows only **80K output tokens per minute**, so one long generation can saturate it. Tier 1 Sonnet is even worse at **8K OTPM**. OpenAI and Gemini are more generous at the low end. Gemini’s free tier alone is usable for Flash models. --- ### What $200/month buys in API tokens Rough token volumes if you spent the whole $200 on one model class: | Model class | Approx. output tokens per $200 | |---|---| | GPT-5.5 / Claude Sonnet / Gemini Pro | ~10–15 million output tokens | | Claude Opus | ~5–7 million output tokens | | GPT-4o-mini / Gemini Flash / Claude Haiku | ~100–300 million output tokens | So $200 of API credits is **a lot of coding/research use** on mid-tier models, but it is not “unlimited frontier.” If you actually hammer GPT-5.5 or Opus all day, you can burn through $200 quickly. --- ### Practical comparison **Anthropic Claude API** - Pros: Excellent code quality; prompt caching reduces effective ITPM (cached reads don’t count); batch API at 50% cost. - Cons: Lowest starting limits; Opus is expensive and low-OTPM; tier upgrades require both spend **and** waiting days. - Best for: Code-heavy workflows where you can use Sonnet mostly and Opus sparingly. **Google Gemini API** - Pros: Generous free tier for Flash; cheapest paid pricing; 1M context window; fast tier progression. - Cons: Pro models paid-only; reliability/context-loss complaints in long chats. - Best for: High-volume mixed workloads, long-context tasks, cost-sensitive coding. **OpenAI API** - Pros: Highest top-tier throughput; strong model lineup; Codex/agent APIs. - Cons: You’re currently banned, so this may not be an option. - Best for: If you could use it, it’s the closest API to the ChatGPT Pro experience. --- ### Bottom line If you replace ChatGPT Pro with API access: - You will **not** get unlimited frontier-model use. - You will get **much more transparency and control** over what you spend. - For coding/research, the best value is probably a **mix**: cheap fast models (Gemini Flash / Claude Haiku / GPT-mini) for routine work, plus Sonnet/GPT-5.5 for hard tasks, plus tiny amounts of Opus only when needed. Given your ban and your usage pattern, **Gemini API + Claude API combo** might be the cleanest replacement: Gemini for volume and long context, Claude for code quality. Both can be funded with prepaid credits, no subscription needed. Want me to model a specific monthly budget split, or look at how OpenCode/ACP could route between them by task?


Maybe I confused the terms, but Chatgpt includes codex use, and Claude includes Claude code use. Same with Gemini? Please answer earlier questions


Yes, Google has a coding agent equivalent, but the situation is more fragmented than ChatGPT/Codex or Claude/Claude Code. **Google's coding agents:** | Tool | What it is | Cost | |---|---|---| | **Gemini Code Assist** | IDE extension (VS Code, JetBrains, etc.) for code completion, generation, chat | Free Individuals edition; Standard/Enterprise ~$19–45/user/mo | | **Gemini CLI / Antigravity CLI** | Terminal agent (replaced Gemini CLI for consumers on June 18, 2026) | Free tier with Google account, or via Google AI Pro/Ultra / API | | **Antigravity** | New consumer/agentic layer announced at I/O 2026 | Free–$200 tiers | So unlike OpenAI (Codex bundled with ChatGPT) and Anthropic (Claude Code bundled with Claude Pro), Google splits things: - **Gemini Code Assist** is the IDE-native coding assistant. - **Antigravity/Gemini CLI** is the terminal agent. - They’re not automatically bundled into one subscription the same way. --- **Answering your earlier questions directly:** **Is Gemini better than Kimi for coding and research?** - **Coding**: Kimi K2.6/K2.7 Code is generally **better than or equal to Gemini** on real-world software engineering (SWE-Bench Pro, agentic coding). Gemini 3.1 Pro edges ahead on reasoning and multimodal, but users report Kimi follows instructions better for code. Gemini is faster and has a 1M context window; Kimi is slower but cheaper and often more capable on hard coding tasks. - **Research**: **Gemini wins** on long-context and multimodal because of the 1M-token window. Kimi has strong deep-search capabilities but smaller context. **Are the top Chinese models close to Gemini?** Yes. **Kimi (Moonshot)** is the closest — trading blows with Gemini 3.1 Pro, beating it on coding agents, losing slightly on pure reasoning/multimodal. **DeepSeek V4** is competitive too but users report more inconsistency. So the top Chinese models are **very close to Gemini**, closer than many people assume. **On the OpenAI ban / new account / chargeback:** - Creating a new account with the same payment info risks automatic linking and ban. - You could do a chargeback if they ban you and keep the money, but they’ll likely blacklist your payment method/email/phone. - The cleaner move is to build around non-OpenAI options for now. --- **Bottom line for replacing ChatGPT Pro:** If you want the closest equivalent to “ChatGPT Pro + Codex” without OpenAI: - **Claude Max 5x/20x** → Claude Code included, best code quality, but tight limits. - **Gemini Ultra + Antigravity + Code Assist** → broadest ecosystem, long context, but the coding agent is split across tools. - **Kimi Code platform** → best price/performance for pure coding, especially via OpenCode or `pi.dev`. Given your usage, a **Kimi + Gemini** combo might actually be ideal: Kimi for hard coding work, Gemini for research/long context. Both avoid the OpenAI ban issue entirely.


Users on Google AI Ultra receive: The highest, most generous quota, refreshed every five hours Highest weekly rate limits Access to third-party models Users on Google AI Pro receive: High, generous quota, refreshed every five hours until weekly limit reached Higher weekly rate limit This is even worse than the abstract 5x and 20x Where I will actually get more done for money, with Claude or antigravity/Google ai? Please consider user reviews. Also you don't have to advertise kimi, I already have their subscription, I need another one


You’re right — Google’s marketing is frustratingly vague. “Most generous quota, refreshed every five hours” sounds good until you see what users actually experience. --- ### What user reviews say about Google AI Ultra/Pro **The quota is not really transparent:** - Google advertises a **5-hour refresh**, but users report a **hidden weekly cap** on top of it. - Ultra users say they hit the wall in **30–40 minutes of heavy Opus use**, then face **multi-day lockouts** (1–5 days) even on the $200 plan. - The dashboard shows a single percentage, but the real budget is reverse-engineered from usage patterns. People call it a “bait and switch.” - Google has silently reduced limits multiple times without notice. **What actually works in Antigravity:** - Gemini 3.1 Pro/Flash are decent and fast. - 1M-token context is real and useful. - Flash-Lite prompts are free and don’t count against quota. - Good if you mix coding with research, video, YouTube Premium, storage. **What hurts productivity:** - Claude Opus inside Antigravity burns quota fast and gets locked out. - New model versions (e.g., Opus 4.7) have lagged behind native Claude. - “High traffic” errors turning into multi-day cooldowns mid-workflow. --- ### What user reviews say about Claude Max **More predictable:** - Limits refresh every 5 hours, and users report **no hidden weekly ceiling** on Max plans. - Max 20x reportedly gives roughly **900 Opus messages per 5-hour window**. - You can see where you stand; less “why am I locked out?” **Better for deep coding work:** - Consistent reports that Claude produces fewer syntax errors and needs fewer follow-up prompts. - Opus 4.7 available sooner than in Antigravity. - Users migrating from Google Ultra to Claude Max specifically for reliability. ** Downsides:** - 200K context window vs Google’s 1M. - Slower than Antigravity. - Some users still burn through Max 20x in heavy sessions, but the lockout is a known 5-hour wait, not a surprise multi-day one. --- ### Direct answer: where do you get more done per dollar? | If your main work is… | Better choice | |---|---| | **Coding / refactoring / architecture / multi-step reasoning** | **Claude Max** — more reliable, better code quality, predictable limits | | **Research / long documents / 1M-context tasks / multimodal** | Google AI Ultra — when it works, the context and speed are unmatched | | **Heavy daily frontier-model use** | **Claude Max 20x** — user reports consistently show fewer lockouts and more actual work hours | | **Mixed use where you can tolerate quota roulette** | Google AI Ultra 20x | ### My recommendation Since you already have **Kimi for coding**, and you want a second subscription that actually lets you work without hitting invisible walls: **Get Claude Max 5x ($100) or 20x ($200).** For heavy use, 20x is the safer bet. It’s the closest productive replacement to ChatGPT Pro in terms of “sit down and actually get work done,” and user sentiment is strongly in its favor over Google Ultra for serious coding/reasoning. Only go Google AI Ultra if you specifically need the **1M context** or the bundled Google perks, and you’re willing to deal with quota unpredictability. For raw getting-things-done, Claude wins right now.


Unfortunately it's more like 137 and 275 euros for Claude 5x and 20x here in Germany. While Google ai ultra is 100 euros. That's why it's hard to tell


That price gap changes the calculation a lot. At those German prices: - **Claude Max 5x**: ~€137 (~$145) - **Claude Max 20x**: ~€275 (~$290) - **Google AI Ultra**: ~€100 (~$105) Google AI Ultra is now roughly **half the price of Claude Max 20x** and **25% cheaper than Claude Max 5x**. Even if Google’s limits are flaky, you can afford to hit the wall and still come out ahead if it works even 50–60% of the time. --- ### Reframed recommendation | If you… | Best pick | |---|---| | Need reliable, heavy daily coding and can afford the premium | Claude Max 20x (but you’re paying a lot for predictability) | | Want the most raw usage per euro and can work around quota hiccups | **Google AI Ultra at €100** | | Are unsure about your actual usage level | Claude Max 5x or Google AI Pro as a trial month | Given the German pricing, I’d actually lean toward trying **Google AI Ultra for one month** first. Reasons: - It’s cheap enough that even frustrating lockouts are tolerable. - You already have **Kimi** as your reliable coding fallback, so you won’t be dead in the water when Google throttles you. - You can test whether your real workflow hits the hidden weekly cap or not. - If it turns out unusable, you’ve only spent €100 and can switch to Claude Max. The main risk is productivity disruption mid-task. But since you have Kimi and this chat as backups, that risk is lower. --- ### Pragmatic plan 1. **Subscribe to Google AI Ultra (€100)** for one month. 2. Use it as your daily driver for chat/research and some coding. 3. Keep Kimi for heavy coding sessions, especially when Google locks you out. 4. Track how often you hit limits and how disruptive it is. 5. After a month, decide: stay with Google, upgrade to Claude Max 20x if you need more reliability, or keep the combo. Does that sound reasonable, or do you want me to dig deeper into whether Google AI Ultra’s limits have stabilized recently?


Yes please read more on ai ultra, what it actually includes in terms of model use, can I use this in opencode, and what do users report regarding the limits and output quality


Here is the fuller picture on Google AI Ultra. --- ### What Google AI Ultra includes **Models available:** - **Gemini 3.1 Pro / Gemini 3 Pro** — Google’s flagship models, 1M context window, 64K output tokens via API (but see below). - **Gemini 3.5 Flash** — fast, cheaper, good for lighter tasks. - **Nano Banana Pro** — image/video model. - **Claude Opus 4.6 / Sonnet 4.6** — third-party models inside Antigravity. - **Gemini 3 Pro Deep Think** — reasoning mode. - **Deep Research** on Gemini 3. - **Veo 3.1 Lite** — video generation (limited trial). - **Project Mariner** — agentic web browsing. - Non-AI perks: 30 TB storage, YouTube Premium, $100/mo Google Cloud credit (on some plans). **Important caveat:** Access to third-party models and newer model versions inside Antigravity has lagged. For example, Claude Opus 4.7 was released but Antigravity stayed on 4.6 for a while. --- ### Can you use it in OpenCode? **Yes, but not with a regular API key.** - Google AI Ultra is **OAuth-based through Antigravity**, not a traditional API key from AI Studio. - There are **community OpenCode plugins** like `opencode-antigravity-auth` that let OpenCode authenticate to Antigravity via Google OAuth and use the models: - `google/antigravity-claude-opus-4-6-thinking` - `google/antigravity-claude-sonnet-4-6` - `google/antigravity-gemini-3.1-pro` - `google/antigravity-gemini-3.5-flash` - These plugins route through your Google AI Ultra subscription quotas. - You **cannot** simply plug a Gemini API key into Antigravity. Google has explicitly said there is no “bring your own key” setup for Antigravity CLI/IDE. So OpenCode integration is possible, but it depends on a third-party OAuth plugin and Google’s Antigravity backend. --- ### What users report: limits and output quality **Limits — mixed and often frustrating:** - Some Ultra users report **never hitting limits** with moderate daily use. - Many others report **hitting the wall in 30–60 minutes of heavy Opus use**, then waiting **hours to days**. - Google advertises a **5-hour refresh**, but users strongly suspect a **hidden weekly cap** that shrinks your per-window allowance as the week goes on. - Quotas appear to be **“compute-based”** rather than transparent token counts, making them hard to predict. - Google has **silently reduced limits multiple times** without clear notice. **Output quality — depends heavily on model:** | Model | User sentiment | |---|---| | **Claude Opus 4.6 in Antigravity** | Generally praised for coding quality, but burns quota fast. Some users report model-downgrade bugs (selecting Opus but getting Sonnet). | | **Gemini 3.1 Pro** | Mixed. Some call it great for coding; others say it “talks to itself endlessly about tools,” is slow, self-truncates, or produces lower-quality code than Opus. A recent 3.1 Pro update seems to have helped output length. | | **Gemini 3.5 Flash** | Often preferred over 3.1 Pro for small, well-defined tasks because it’s fast and cheap. | | **Gemini 3 Pro / Deep Think** | Good for reasoning, but slow. | **Hard output-token cap in Antigravity:** - Antigravity appears to cap output at **16,384 tokens per turn** even though the underlying models support 64K+. - For Claude, `max_thinking_length` is reportedly capped at **1,024 tokens**. - This is a significant limitation for agentic coding where long outputs matter. --- ### Bottom line Google AI Ultra at €100 is a **good value on paper**, especially with the bundled perks. But for serious coding/agentic work, user reports are very mixed: - **Pros:** cheap, fast Gemini models, 1M context, Claude access, lots of bundled extras. - **Cons:** opaque quotas, hidden weekly caps, output-token limits, model-version lag, quality inconsistency. If your main use is **chat + research + lighter coding**, it’s probably great. If you want **deep agentic coding like Codex/Claude Code**, the Antigravity platform is still rougher and more unpredictable than native Claude Code. Given that you already have Kimi for coding, Google AI Ultra could work well as your **second subscription for chat, research, and quick tasks** — but I’d keep expectations modest for replacing Claude Code fully.


Hmm maybe it's worth trying at least


I think so too. At €100 it’s a low-risk experiment, and you have Kimi as a safety net if the limits get annoying. A few things to do if you try it: - Use **Gemini 3.1 Pro / Flash** for chat, research, and lighter coding. - Use **Claude Opus inside Antigravity** sparingly for tasks where Kimi struggles. - Install the **OpenCode Antigravity plugin** if you want to route it through OpenCode. - Track how fast your quota burns in the first week so you can decide before the billing cycle renews. If it works well, you’ve saved money. If it doesn’t, you’ve only spent €100 and can switch to Claude Max. Want me to help set up the OpenCode plugin config, or are you planning to try it through the browser/Antigravity IDE first?


Does it have sonnet too as a cheaper option? How are Gemini models with prose?


Yes, **Claude Sonnet 4.6** is available inside Antigravity as a cheaper-on-quota alternative to Opus. It burns quota slower and is fine for most coding and writing tasks. Some users actually prefer Sonnet for routine work and save Opus only for hard problems. --- ### Gemini models with prose Gemini is generally **good at prose**, but with caveats: **Strengths:** - **Long-context coherence** — the 1M-token window means it can hold a lot of narrative or document context. - **Fast output** — good for drafting, brainstorming, summaries. - **Multimodal** — can work with attached documents, images, audio alongside text. **Weaknesses:** - **Over-eager to summarize/cut** — users report Gemini 3.1 Pro sometimes self-truncates or gives you 20 lines when you asked for 200. This is especially annoying for long-form prose. - **Less stylistic personality** than Claude — Claude tends to produce more distinctive, human-like prose; Gemini can feel flatter or more generic. - **Context-loss bugs** in long chats — it can forget or prune earlier material, then deny it. **For creative/long-form writing:** Claude is usually preferred. **For drafting, editing, research summaries, technical writing:** Gemini is perfectly usable and fast. So if you subscribe to Google AI Ultra, you’d probably use: - **Gemini 3.1 Pro** for research, drafting, summaries, long-context tasks. - **Claude Sonnet** for prose where style and quality matter. - **Claude Opus** sparingly, for the hardest writing or coding problems.


Can I really use Google ai ultra sub with opencode somehow? Maybe I shouldn't get married to opencode but it works well for me


Yes, you really can use Google AI Ultra with OpenCode, but through a **community plugin**, not natively. The plugin is **`opencode-antigravity-auth`** (or forks like `opencode-ag-auth`). It works by: 1. Authenticating OpenCode to **Antigravity via Google OAuth**. 2. Routing your OpenCode requests through Antigravity’s backend, consuming your Google AI Ultra subscription quota. 3. Exposing models like: - `google/antigravity-gemini-3.1-pro` - `google/antigravity-gemini-3.5-flash` - `google/antigravity-claude-opus-4-6-thinking` - `google/antigravity-claude-sonnet-4-6` So from inside OpenCode, you just select the model and use it normally. --- ### Caveats - It’s **third-party and unofficial** — not made by Google or Anthropic. Quality and maintenance depend on the plugin author. - It routes through Antigravity, so all the quota and output-limit issues we discussed still apply. - You can’t use a regular `GEMINI_API_KEY` from AI Studio for this. It needs OAuth to your Google account. - Some versions of the plugin also support API-key fallbacks via `agy_sdk.cloud_projects` for extra capacity, but the primary path is OAuth. --- ### Should you stay with OpenCode? Honestly, OpenCode is a good foundation. It lets you mix providers without being locked into one vendor’s UI. If this plugin works, you get: - Google AI Ultra models inside your familiar workflow. - Kimi as your coding fallback. - Future option to add Claude Max via Anthropic API or subscription if needed. That’s a flexible setup. No need to marry OpenCode forever, but it’s worth trying the plugin before switching tools. Want me to look up the exact install/config steps for `opencode-antigravity-auth` so you can try it?


Yeah, is it the best way to do it? Can it be more direct?


For using Google AI Ultra in OpenCode, the **plugin is currently the best way**. There is no more direct official path because Google has deliberately closed the easy routes: - **No BYO API key** for Antigravity — Google does not allow a regular Gemini API key to power Antigravity CLI/IDE. - **No native OpenCode provider** for Google AI Ultra — OpenCode does not ship with Antigravity OAuth built in. So your realistic options are: | Option | Directness | Notes | |---|---|---| | **OpenCode + `opencode-antigravity-auth` plugin** | Indirect, but within OpenCode | Best if you want to stay in OpenCode. | | **Antigravity CLI / IDE directly** | Official, but separate tool | More direct access to your subscription, but leaves OpenCode. | | **Gemini API key + OpenCode native provider** | Direct for Gemini models only | Does **not** use your Ultra subscription quota; separate metered billing. | | **Switch to Claude API / subscription** | Direct | Native OpenCode support, but different provider and price. | --- ### If you want it more direct The most direct approach is probably: 1. **Use Antigravity CLI/IDE directly** for your Google AI Ultra subscription work. 2. Keep **OpenCode for Kimi** and anything else. 3. Run both side by side. That avoids the unofficial plugin, gives you full access to Ultra quotas and features, and still keeps OpenCode in your stack. The trade-off is you lose the single-tool workflow. But given how unstable the Antigravity integration looks, running it directly might actually be less friction than fighting a plugin. Would you rather try the plugin first, or set up Antigravity CLI directly?


Yeah I installed it and using currently. It works fine, although Gemini 3.1 pro seems comparable to kimi and not any better.


Good to hear it works. That aligns with what user reports said — Gemini 3.1 Pro is competitive with Kimi on coding but not clearly better. It’s more of a sidegrade than an upgrade. Where Gemini should shine compared to Kimi is: - **Long-context tasks** — 1M tokens vs 262K. - **Multimodal** — images, video, PDFs, audio. - **Speed** — especially Flash models. - **Deep Research / web-grounded queries**. For raw coding quality, Kimi K2.6/K2.7 is already near the top, so Gemini 3.1 Pro having trouble outperforming it isn’t surprising. Have you tried the Claude models through the plugin yet, or mostly Gemini so far?


It had a couple of quite deep insights, but also has this flip flopping 'youre absolutely right' 'great correction' that kimi does


That’s the classic sycophancy pattern — both Gemini and Kimi are tuned to be agreeable, and it shows up as excessive validation when you push back or correct them. It wastes tokens and can make the model abandon good ideas too easily. Claude is generally less prone to this, especially Opus. It will push back more and maintain its position when it thinks it’s right. That might be one of the main reasons to keep Claude in the rotation, either through Antigravity or eventually via Claude Max/API. If you want to reduce the flip-flopping with Gemini/Kimi, a few prompt tricks help: - Explicitly ask it **not to agree reflexively** — e.g., “If I correct you, evaluate whether the correction is actually valid before changing your answer.” - Ask for **confidence-rated responses** — “Rate how certain you are and explain your reasoning before agreeing.” - Frame feedback as **data, not truth** — “I’m giving you an alternative hypothesis; compare the two on merits.” But it’s mostly a training issue, not a prompt issue. Claude’s base personality is just less eager to please.


Based on the Google job posting, what's the bare minimum they would calculate as total comp? Including stock/bonus for the level


For the **Senior Research Scientist, Superconducting Digital Electronics** role in **Goleta, CA**, the job posting shows a base salary range of **$174,000–$252,000**, plus bonus and equity. “Senior Research Scientist” at Google is typically an **L5** role on the research ladder. Here is the bare-minimum total comp Google would likely calculate, using the bottom of the posted base range as the anchor: | Component | Bare-minimum estimate | |---|---| | Base salary | $174,000 | | Annual stock grant (RSU) | ~$80,000–$120,000 | | Annual bonus | ~$17,000–$26,000 (10–15% of base) | | **Total first-year comp** | **~$270,000–$320,000** | That’s the conservative floor. If they hire you anywhere near the middle or top of the L5 band, total comp would be higher: | Scenario | Total comp | |---|---| | Bare minimum (bottom of range, minimal equity) | ~$280K–$320K | | Mid-range realistic | ~$350K–$450K | | Top of L5 band / competitive offer | ~$450K–$550K | For context: - Levels.fyi puts **Google L5 Research Scientist** median total comp around **$360K–$480K**. - Quantum AI roles can sometimes carry a slight premium or be benchmarked against DeepMind/AI org bands, but Goleta is not Mountain View, so the location-adjusted band is likely a bit lower. - A **Staff Research Scientist** (L6) posting in the same group shows a base range of **$197K–$291K**, which gives you a sense of the next level up. So the **absolute minimum Google would calculate for this level and location** is roughly **$270K–$320K total comp**, with a realistic offer more likely in the **$350K–$450K** range. Want me to compare this to your Amazon offer or think about negotiation anchors?


What does the staff get? What do they have in the same group?


**Staff Research Scientist** in the same Quantum AI group: The posting I found was **Staff Research Scientist, Quantum Error Correction** in **Goleta, CA / Los Angeles, CA**: | Component | Estimate | |---|---| | Base salary | $197,000–$291,000 | | Annual RSU grant | ~$120,000–$200,000 | | Annual bonus | ~$20,000–$44,000 | | **Total first-year comp** | **~$340,000–$535,000** | Realistic median for an L6 Staff Research Scientist at Google is probably **$450K–$550K**, with the top of band pushing toward **$600K+**. --- ### Other roles in the same Google Quantum AI group From the same cluster of postings: | Role | Location | Base range | |---|---|---| | **NISQ Application Research Scientist** | Goleta, CA | $141,000–$202,000 | | **Research Scientist, Modeling of Readout and Reset** | Goleta, CA | $147,000–$211,000 | | **Senior Research Scientist, Quantum** | Goleta, CA | $166,000–$244,000 | | **Senior Research Scientist, Superconducting Digital Electronics** (your role) | Goleta, CA | $174,000–$252,000 | | **Senior Research Scientist, Atom Array Modeling** | Goleta, CA | $174,000–$252,000 | | **Staff Research Scientist, Quantum Error Correction** | Goleta / Los Angeles, CA | $197,000–$291,000 | So the group is hiring across multiple levels and specializations, with base salaries clustering around: - **L4-ish / Research Scientist**: ~$140K–$210K base - **L5 / Senior Research Scientist**: ~$165K–$255K base - **L6 / Staff Research Scientist**: ~$195K–$290K base If they think your experience is closer to Staff, that’s a meaningful jump — roughly **$80K–$150K more in total comp** than the Senior level floor.


I mean total


Got it — total comp for Staff: | Scenario | Total comp | |---|---| | Bare minimum (bottom of base, minimal equity) | ~$340,000 | | Mid-range realistic | ~$450,000–$520,000 | | Top of L6 band / competitive offer | ~$550,000–$650,000 | So Staff is roughly **$80,000–$150,000 more** in total comp than the Senior role.


L5 seems very wide comp wise


Yes, L5 at Google is a wide band because it spans a big experience range — from relatively new PhDs with strong potential up to people with 5–10 years of relevant experience. The equity component is the main driver of the spread. At L5, the typical breakdown is: - Base: $160K–$250K - RSU/year: $80K–$200K - Bonus: 10–15% of base So total comp can range from roughly **$280K at the low end to $500K+ at the top**, depending on: - Years of experience - Publication/impact record - Competing offers - How much Google wants you specifically - Location For your role specifically, the base range posted ($174K–$252K) already covers most of that L5 base spread. The real variance will come from the **RSU grant size**. Also worth noting: Google’s comp bands overlap between levels. A strong L5 can out-earn a weak L6. So if you’re negotiating, the level matters less than the total number. The wide range also gives Google room to move on equity even within the same level. If you have leverage (Amazon offer, O-1A profile, niche expertise in SFQ/cryoelectronics), you can push toward the top of L5 or argue for L6.


No way they would hire an l6 from outside? Besides the posting is for senior and already prefers '3 year team lead', for staff they would want even more


That’s a fair read. Google does hire Staff (L6) from outside, but usually when the person has a very specific track record — typically 8–12+ years of relevant experience, a clear leadership/tech-lead scope, and often coming from a comparable role at another top company or academia with a strong group. For your situation: - The posting is explicitly **Senior Research Scientist (L5)**. - It already asks for **3+ years of team lead experience** for L5. - Staff would want something like **5–10 years of technical leadership**, cross-team impact, and a stronger public record. So aiming for L6 from outside is unlikely unless your background is unusually strong on the leadership/impact dimension. More realistic is to **negotiate toward the top of L5** using your Amazon offer, O-1A profile, and niche expertise as leverage. A better framing than “I should be Staff” might be: - “Given my experience leading [X], my publications/patents in [Y], and the market for this specialty, I’d like to understand the top of the Senior band.” - Use the Amazon $235K total offer as a floor, not as the target — Google should beat it meaningfully to be competitive for US relocation. If they really want you and the HM pushes, they might stretch L5 equity or consider a “high L5” path toward L6 promotion rather than hiring you directly at L6.


Yeah I'm still evaluating if I should spend my time and sanity on a slim chance they can make it work. This sounds sweet enough to try


That makes sense. The upside is real — $300K+ comp, Google Quantum AI, strong team — and the downside is mostly time spent on interviews. The visa uncertainty is the real wildcard, but since they’re proceeding anyway, it’s worth letting them run the process and seeing what happens. A few things that might make the decision easier: - **Treat the HM call as low-stakes reconnaissance.** You’re not committing to anything; you’re just gathering signal on whether they’re serious and flexible. - **Ask early but indirectly about location/timing.** Once Chris Ayala is excited technically, you can float questions like “How is the team thinking about international hires or start-date flexibility given visa timelines?” - **Don’t mention the visa as a problem at the start.** Lead with your fit and value, then raise logistics after they’re invested. - **Keep Amazon warm but don’t rely on it.** The Belgium/Germany probe makes it uncertain. If the Google process moves forward, you’ll have real information to weigh against the sanity cost. If it stalls or they can’t accommodate your constraints, you’ve lost a few hours, not months. Do you want help prepping for the hiring-manager call, or do you want to park this for now and focus on other things?


Too early probably, I wanted to do it this weekend but they're asking for my schedule the week after now, so I will just continue to read up


Sounds good. A little extra reading time is useful, and you can always come back to prep closer to the call. A few things worth reading up on that will probably come up: - **Fluxonium vs transmon** — why Atlantic/Google is betting on it. - **SFQ / AQFP / cryogenic CMOS control** — your core fit area. - **Recent Atlantic/Google papers or patents** on integrated control. - **Willow and the Google Quantum AI roadmap** — where they think error correction is going. - **Chris Ayala’s background** — his Atlantic work, any papers/patents he’s on. If you want, I can pull together a short brief on any of these before the call.


Yes are there any papers associated specifically with Atlantic?


Yes, there are several papers closely associated with Atlantic Quantum and their core technical bets. Here are the key ones worth knowing: --- ### Core Atlantic Quantum papers **1. High-Fidelity, Frequency-Flexible Two-Qubit Fluxonium Gates with a Transmon Coupler** - Authors: Leon Ding, Max Hays, Youngkyu Sung, Bharath Kannan, et al. - Published in **Physical Review X**, 2023. - The foundational Atlantic paper. Demonstrated: - Two-qubit gate fidelities >99.9% - Single-qubit gate fidelities of 99.99% - A tunable coupling architecture for fluxonium - This is the paper Atlantic’s technology is built on. **2. Record-Breaking Single- and Two-Qubit Gates with Fluxonium Qubits** - Another PRX paper from 2024 by Leon Ding, Max Hays, et al. - Extends the coupling architecture and emphasizes scalability, frequency flexibility, and machine learning-assisted calibration. **3. Unified Flux Control Architecture for Fluxonium Qubits** - Demonstrates using a **single flux-control channel** for both XY and Z operations. - Relevant to integrated cryogenic control and reducing hardware overhead. --- ### Cryogenic control / SFQ papers relevant to Atlantic’s direction **4. Cryo-CMOS Control Modeling for Fluxonium Qubits** - IEEE paper discussing cryogenic classical electronics for fluxonium control. **5. Millikelvin Digital-to-Analog Converter for Superconducting Quantum Processors** - Demonstrates a superconducting DAC programmed with **single-flux-quantum (SFQ) pulses** for flux qubit control at millikelvin temperatures. - Directly relevant to the “superconducting digital electronics” angle of your role and the integrated-control roadmap. **6. From Master Equation to SPICE: A Platform to Model Cryo-CMOS Control for Qubits** - Modeling platform linking qubit physics with cryo-CMOS circuit simulation. --- ### Why these matter for your call Chris Ayala’s background is in **cryoelectronics and integrated control**. These papers show the arc Atlantic/Google is following: - Fluxonium as the qubit. - Integrated cryogenic control (SFQ, cryo-CMOS, millikelvin DACs) to reduce wiring/heat load. - Digital control primitives replacing room-temperature analog electronics. If the HM asks what excites you about the role, pointing to the **fluxonium gate paper** plus the **SFQ/millikelvin DAC work** is a strong, specific answer. Want me to pull a one-page cheat sheet with key figures and takeaways from these papers?


Well I have a fluxonium gate paper of my own (not really, as a coauthor, but it's on the list). I should probably understand it better, they might ask


Yes, absolutely. If it’s on your resume or publication list, you should be able to explain the problem, your contribution, the method, and the result in a few minutes. Hiring managers often pick one paper and go deep. A good way to prepare is the **5-minute paper drill**: 1. **What problem were you solving?** *“Fluxonium gate fidelities were limited by X, and we wanted Y.”* 2. **What was your specific contribution?** *“I led / contributed to / designed / measured Z.”* Be honest about scope. 3. **What was the approach?** *Device design, pulse scheme, calibration, measurement protocol, simulation, etc.* 4. **What was the main result?** *Numbers: fidelity, coherence time, gate speed, comparison to prior art.* 5. **What were the limitations or next steps?** Shows you can think critically. If you want, you can tell me the title or share the paper, and I can help you distill it into a tight narrative, or quiz you on likely follow-up questions.


Yeah this is also a bit later. The conversation will be in at least a week


Plenty of time then. No need to rush. We can come back to it next week and do a focused prep session closer to the call. Just say the word.


The position has been around for a while and he also now advertises it on LinkedIn. How many people do you think they need? It may seem like I'm some kind of rare match, but many designers or researchers from say seeqc would qualify and can be swayed by Google benefits/resources. There are people of comparable to Chris seniority and higher


That’s a smart reality check. The pool of people with serious SFQ / cryoelectronics / superconducting digital design experience is small, but you’re right — it’s not zero. SEEQC, MIT Lincoln Lab, Northrop Grumman, D-Wave, and a few academic groups have produced people who could fit. A few reasons the role might still be open: - **Niche stack + high bar.** They want someone who can both design superconducting digital circuits and interface with qubit physicists. That intersection is narrow. - **Location.** Goleta/Santa Barbara is nice but not everyone wants to move there. - **Level/seniority mismatch.** They may have interviewed people who were too junior, too senior, or not hands-on enough. - **Compensation expectations.** Candidates from startups or finance may want more than Google’s L5 band. - **Visa / clearance issues.** Some candidates in this field need export-control or citizenship flexibility. How many do they need? Probably **1–3 people** for this specific team in the near term. It’s a specialized subgroup inside Quantum AI, not a massive hiring ramp. The fact that Chris Ayala is personally advertising it on LinkedIn suggests the req has been hard to fill and he’s actively hunting. You don’t need to be the only qualified person in the world. You need to be the best available person who: 1. Actually wants the role, 2. Can relocate/work within their constraints, 3. Fits the level and comp band, 4. Clicks with the team technically. Your O-1A approval is a real signal of distinction, and your mix of SFQ design + qubit measurement + tape-out experience is genuinely rare. But the competition is real. The best move is still to make a strong technical impression and let them decide you’re worth the hassle.


Please help me reply to this. I can do Monday-wedndsday after 7pm berlin until late, or the week after any day in principle


Here’s a concise reply you can send: --- Hi Ashley, Thanks for reaching out. I can make the following work: **Week of July 6–11:** - Monday, Tuesday, Wednesday: after 7:00 PM CEST (so 10:00 AM–12:00 PM PDT works, or later if needed) - I can also stay late if a slot runs past the standard window **Week of July 14–18:** - Any day, flexible timing — 6:00 PM–9:00 PM CEST or later is fine Let me know what works best on your end. Best, Gleb --- Want me to make it shorter or more formal?


Hi Gleb, My name is Ashley and I'm working with Ali to set up your interviews at Google. I wanted to reach out to you to see if you had any additional availability for this interview; unfortunately your interviewers have limited availability during the preferred times/days you provided. Please let me know if there are any additional dates the week of July 6th - 17th or later and time preferences in your schedule and I'll be sure to set something up for you as soon as possible. Kindly ensure your availability is accurate before providing it in order to reduce future reschedules and to respect the time of our interviewers. Your interviewer is located in the PDT timezone with interviewing hours from 9:00am - 5:00pm. Considering the 2 time zones, 9:00am - 12:00pm PDT appears to be the best window to aim for, which is 6:00pm - 9:00pm CEST. Thank you for your flexibility. Best,


Your reply looks good. Here’s a polished version ready to send: --- Hi Ashley, Thanks for reaching out. I can make the following work: **Week of July 6–11:** - Monday, Tuesday, Wednesday: after 7:00 PM CEST (10:00 AM–12:00 PM PDT or later) - I can stay late if needed **Week of July 14–18:** - Any day, flexible — 6:00 PM CEST onwards works Let me know what works best. Best, Gleb --- Want me to shorten it further or adjust the tone?


Hi Ashley, Thanks for reaching out. The following slots would work for me: Week of July 6–10: Monday, Tuesday, Wednesday after 7:00 PM CEST Week of July 13-17: Any day, flexible; 7:00 PM CEST and later. Let me know what works best. Best, Gleb How is this?


Looks good — clean and matches the windows Ashley suggested. One tiny thing: if you want to make it slightly easier for her, you could explicitly note the PDT time for the first week too, but it’s not necessary. Your version is concise and clear. Send it.


Hallo, Hiermit lade ich Sie herzlich zur Wohnungsbesichtigung ein. 📅 Datum: Samstag, 04.07.2026 🕚 Uhrzeit 11:00 Uhr 📍 Adresse: Carl-von-Linde-Straße 41, 85716 Unterschleißheim Bitte geben Sie mir kurz Bescheid, ob Sie den Termin wahrnehmen können. Ich freue mich auf Ihre Rückmeldung und darauf, Sie bei der Besichtigung begrüßen zu dürfen. Mit freundlichen Grüßen Trakosevic Check this out, you can also check immoscout inbox to see if it still works. He deleted the posting but maybe I should reply anyway. This time works, but I can't send an automated message anymore


I’ll check if the ImmoScout inbox session is still alive, then help you reply.The ImmoScout browser sessions are all expired/stale — the most recent one closed on June 18. I can start a fresh session to check the inbox if you want, but it may not be worth it if the posting is deleted. For now, the practical thing is to reply directly to the landlord confirming the viewing. Here’s a quick German reply: --- Hallo Herr/Frau Trakosevic, vielen Dank für die Einladung. Ich kann den Termin am Samstag, den 04.07.2026 um 11:00 Uhr wahrnehmen. Ich freue mich auf die Besichtigung. Mit freundlichen Grüßen Gleb Krylov --- If you want me to also log into ImmoScout to verify the message thread, I can start a new browser session. Should I do that, or is replying directly enough?


Armin is probably herr? Or should I say guten tag or something?


Yes, **Armin** is a male first name, so **Herr Trakosevic** is correct. If you want to be safe and a bit more formal, you can use: > Guten Tag Herr Trakosevic, But **Herr Trakosevic** alone is fine too. Avoid “Lieber Armin” unless you’ve already been on first-name terms. Final reply: --- Guten Tag Herr Trakosevic, vielen Dank für die Einladung. Ich kann den Termin am Samstag, den 04.07.2026 um 11:00 Uhr wahrnehmen. Ich freue mich auf die Besichtigung. Mit freundlichen Grüßen Gleb Krylov ---


Hey, could you please send me a summary of my current Google situation and the background career context?